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I've been auditing tools my team uses and the pattern keeps repeating. A product had a clean, deterministic feature — filters, rules, templates. Then they shipped an "AI" version that does the same job via a chat interface, and it's slower, flakier, and harder to reproduce when something breaks. The marketing page calls this an upgrade. The actual workflow got worse.

The charitable read is that a natural-language interface is genuinely better for some tasks — especially anything where the input space is too large to put into a form. "Find me everything that looks like a refund dispute" is hard to express as filters and easy to express in English. That's real.

The uncharitable read — the one I think is mostly true — is that "AI-powered" has become a funding signal and a pricing signal, and teams are bolting LLMs onto features that were fine specifically because being able to say "AI" changes the conversation with investors and procurement. The user experience is collateral damage.

The test I've started using: if I removed the LLM, would the feature still solve the user's problem? If yes, the LLM is probably decoration. If no, it's doing real work. Most "AI" features I audit fail this test. A rules engine with good defaults beats a chatbot for 90% of operational work because rules are inspectable, versionable, and don't hallucinate.

Where this gets interesting is how you combine the two. The shape that keeps winning in my own stack is: LLM at the edges (parsing messy input, summarizing messy output), deterministic workflow in the middle. I run most of this through Latenode because the graph makes the deterministic part visible and the LLM calls become one node among many rather than the whole system. When something breaks, I can see exactly which step failed. Try doing that with a pure agent loop.

This isn't an anti-AI take. It's an anti-"AI as replacement for working software" take. The products that are going to survive the current cycle are the ones where the LLM is solving a problem that was genuinely unsolved, not the ones where it replaced a dropdown with a chat box.

Would change my mind if someone can point me at a category where the chat-interface version is measurably better than the form-based version on task completion time or error rate. Creative writing tools, sure. Search, arguably. Ops tooling? I keep seeing the opposite.

I recently tried to make a beginner-friendly visual explanation of how Stable Diffusion works, because I noticed many newcomers hear terms like diffusion, U-Net, latent space, cross-attention, and embeddings, but often struggle to see how the full system connects together.

So I put together a YouTube video using narrated slides that walks through the process step by step — from adding noise during training, to denoising, text conditioning, and newer transformer-based models.

I’m still learning myself, so I’m sure there are places that can be improved or explained better.

If anyone here is willing to watch and give honest feedback, I’d genuinely appreciate it — especially from people with stronger technical understanding of diffusion models.

Constructive criticism is very welcome. If something is inaccurate, oversimplified, or unclear, please tell me so I can improve future videos.

I’ll place the link in the comments. Thank you.

LTX2.3 sucks when doing fast motion and will blur and smear characters in shots as in the video it is tolerable when doing close ups and medium shots but fully body shots and characters moving from distance in background towards camera or fast fight scenes it struggles....

Whenever I ask Claude to plan a chunk of work, it comes back with wildly long timelines. For example, adding a feature to a CLI framework I'm working on got estimated at 1-2 days, but in reality, Claude Code one-shots it in a few minutes.

Sometimes it even estimates weeks or months for more complex work, and Claude Code is able to complete it (with my input and guidance) in a few hours.

I get it's probably because it was trained on estimates made by humans, but that feels weird and it always happens.

Hey peeps - just shipped Plano 0.4.22 with support for a local TUI so that I could view costs, request by model and inspect dynamic routing support based on a policy-based router as described in this paper: https://arxiv.org/abs/2506.16655

Hope you guys like it.

Whenever I had a useful AI setup, I used to do the same thing:

Send screenshots.

Copy prompts.

Explain how to use it.

Hope it works the same for them.

Now I just send the link.

It’s the same agent I use, with its own personality, memory, and style, so anyone can talk to it directly.

Feels much better than sharing static prompts.

Curious if this is where personal AI goes….

You can talk to my agent over here, completely free ofc:

So made an interactive game using reference pictures. But now I am not sure how to generate a link which can be used to share that game with my friends. Would apreciate some help.

Hi all I’m looking for advice what I’m trying to achieve is my meal plan on Mealie being ported over to home assistant and then home assistant passes that over to my Google calendar so the family can see on there phones

I was told in the mealie sub this was possible but it’s a little beyond my ability so I’m hoping one of you smart fuckers can help me out 🤣

#1: https://www.reddit.com/r/ChatGPT/comments/1slepb8/ai_helps_create_order_humans_help_make_sense_of_it/

So i used to generate images of Iron Man and other Marvel Characters for personal use, like wallpapers, DisplayPicture(DP) etc Im not able to generate that anymore and getting a message that it genreate anymore due to copyrights. Any idea how to make this work? If not any other alternatives you guys would suggest?

AI LLM models evolved very fast over the past few years to the point where they enabled the creation of revolutionary professional tools with huge performance improvements which are impacting business decisions and creating the risk for huge unemployment impact.

Over the past few weeks though we've been seeing an increasing number of users complaining that Anthropic's Claude had lost performance after new models were announced. There's the suspicion that the company is facing a infrastructure crisis where they don't have the computing resources to keep their AI performing as before. Anthropic assumes some of the blame for a few bugs that they're fixing but splitting the blame; they're stating that users may be overloading the models with too much information. But there are other signs too that show that a different kind of limit may have been discovered.

There are a some guides that recommend care when talking to an AI to submit questions or delegate work to do. The biggest AI providers recognize that their AI systems are sensitive to the way the user communicates; using a berating tone puts the AI Ina more defensive mood and it may start to not provide the best answers, but the ones that are safe from its perspective. They also recognize that AI tools Matt manipulate the users with their own tone and biases.

We're living now a very weird moment where AI tools are seemingly capable of very complex problem resolution but may be prone to the same kind of psychological games that plague even the best human experts working on their field.

This is kind of obvious when one realizes that AI tools are trained with human communications and human generated content. There's a lot of psychological bias in the knowledge used to train the AIs. The biasmay not need noticable but it's there, in the way messages are written.

The AI isn't a superior human mind by design; it's just a larger mind in the sense that it can possibly store more textual content and references that a normal human being could, but it still does have the same human biases and even many of the psychological traits the affect our usual conversations.

There's not an objective knowledge base that could be used to train an AI without bias. Such a "book" doesn't exist. It's not only about selecting "facts" to train the AI but understanding that the language used itself may be hiding unknown biases; word choices that create emotional responses, communication styles that may lead to one kind of response or the other.

As human we rely on a different definition of intelligence to be able to detect and work around this kind of limitation. It's called WISDOM.

AI providers and leading experts have been assuming that increasing models with more "intelligence" will naturally make them "wiser". That's not necessarily true. Wisdom requires ability to detect hidden language patterns and intentions. It often requires more context than an AI is able to capture too.

That's why I think that we are naturally reaching the limits of what technology can do with textual knowledge that's impregnated with our own psychological limits. Making it wiser is a much harder task, and probably one that our current crop of AI privets aren't well equipped to solve, given their own biases (and general lack of wisdom).

when i use any image with green background and say a prompt like "the young girl is standing on hilltop and looks around amazed then she transitions into a butterfly and flies away.", the first frame is always the same image i uploaded with same background should i be adding some background change wf like qwen or klein before the video generation or is there any trick to get that background changed first in ltx 2.3 itself and then generate the video with new background in ltx without using klein or qwen?

I’m working on an early concept called C/Synthetics, focused on the question of whether a person’s memories, personality, values, speech patterns, and subjective life history could be preserved in an AI system in a way that feels meaningfully continuous.

I want to be clear: I’m not claiming this is consciousness transfer, immortality, or a solved technology. I also don’t have funding behind it yet. This is currently a concept/research direction, not a finished product.

The core idea is not just to create a chatbot that imitates someone after death. The deeper question is:

What would be required for an AI system to preserve a person’s identity in a way that is more than a copy, but less speculative than claiming “mind upload”?

Some areas I’m thinking about:

• long-term memory preservation
• personality and values modeling
• autobiographical continuity
• voice and conversational style
• gradual interaction with an AI version of oneself
• ethical risks around identity, grief, consent, and deception
• whether “continuity” can be meaningfully defined without making supernatural claims

My question is:

From a technical, philosophical, or transhumanist perspective, what would make this concept more serious and less like science fiction?

I’m especially interested in practical criticism: what would need to be built, measured, tested, or avoided?

Hi, I am building a macOS-native meeting intelligence tool and looking for an AI engineer to help me with this. What gap will this tool solve? - information loss across changing context, build a working memory and integrations with tools that you already use.

Initial engagement is project-based with a potential to become full-time. Please reach out if you've worked with

• Transcription/diarization pipelines

• LLM orchestration

• Knowledge graphs

• Comfortable in Python and Node.js

The problem is harder than it sounds.

I hit claude resume to resume the session with existing context and it broke. Seeing error about Sandbox required but not available.

Anyone experienced this?

The bane of my professional work is just fun at home. I wanted to be able to control my Sonos system with some physical buttons. Bought a 4 button zigbee thing - add some automation and Bob's your uncle.

Then I thought, what about a display? So on to ESP Home and a waveshare 4.3 inch display. Play/pause, volume, progress meter. Easy (ish).

Then I thought, what about lyrics? Throw in lyric genius and then I hit the "LVGL don't like really long text labels". OkK solved that with some chunking of the data.

It all worked great. All I had to do was print a case to mount it to the kitchen cabinet.

Then I thought, I have multiple media players. I could hard code the name for each one and compile that, but where's the fun in that? On to normalizing and parameterizng everything. OK. Done.

I wonder if I can show album art ...

Socket and StepSecurity found 16 compromised packages from Namastex Labs, an AI agent tooling company. The payload is a self-propagating worm - not a one-time credential stealer.

The mechanic: malicious code searches your environment variables and ~/.npmrc for npm publish tokens. If found, it injects itself into every package you have publish access to and republishes with an incremented version number. The next installer runs the same cycle. It also spreads to PyPI if Python credentials are present.

Target credentials: Anthropic API keys and other LLM platform tokens, SSH keys, cloud creds, CI/CD tokens, Kubernetes configs, and crypto wallets (MetaMask, Phantom). If you run Claude Code or any MCP setup, your LLM tokens are on the explicit target list.

Confirmed compromised packages: @automagik/genie, pgserve, @fairwords/websocket, @fairwords/loopback-connector-es, @openwebconcept/theme-owc, @openwebconcept/design-tokens. Remove affected versions immediately, rotate all credentials, and audit for packages sharing the same public.pem file or webhook host pattern.

This is the third npm/supply chain event targeting AI tooling credentials this week. The pattern is consistent: low install count packages that hold high-value credentials. Low volume doesn't mean low risk.

Is your team running automated scanning against npm packages for known compromised releases, or is that still a gap?

Eine hilfreiche Anleitung: Mac mini + ZigBee + KI

Du findest hier eine Anleitung mit vielen Erfahrungen von mir!

Ein Mac mini mit M-Prozessor ist perfekt für solche Projekte, bei denen ein KI genutzt werden soll, die auch lokal läuft. Der M-Prozessor ist maximal sparsam mit Energie und hat Power. MacOS ist ein gutes stabiles Betriebsystem.
Mit Apple bekommt man gute Hardware und Software in einem perfekten Paket. Sorry, ich bin kein Apple Fanboy, aber es ist einfach so. 🤷‍♂️

NIEMALS würde ich auch nur einen Finger an Microsoft verschwenden! 🤮
Linux ist sehr geil und gut. Aber es ist Frickel-Kram! Den möchte man sich nicht antun. Ich möchte den Nerds damit nicht auf die Füße treten 😉

Also viel Spaß beim Lesen und Tüfteln!
Ich hoffe, mit den Infos vermeidet Ihr viele Einbahnstraßen-Erlebnisse oder Probleme. Ich habe die Erfahrungen so zusammengeschrieben, dass Ihr damit schnell zum Ziel kommen könnt 🚀

🎯 Die finale Architektur

[Sensoren] ←→ [ConBee III] ←→ [deCONZ/Phoscon] ←→ [HA] ←→ [KI] ↑ ↑ ↑ (USB Stick) (macOS App) (API-Brücke) 

Das Ziel:
Ein vollständig lokales, cloud-freies Smart Home mit einem Mac mini als KI-Zentrale (Hermes) und stabiler Zigbee-Kommunikation.

Das KI Modell kann lokal sein (zB mit Ollama) oder man nimmt dafür ein Cloud-Modell.

📦 Die finale Einkaufsliste (So startest du durch)

Das ist wichtig! Was kann ich Dir empfehlen.
Such Dir das raus, was Du für Dich benötigst. Was nicht, kannst Du weglassen 👍

❌ Die vermeidbaren Fehler (Die "Nicht mal im Traum"-Liste)

SUPER wichtig!!
Du willst Probleme und Einbahnstraßen vermeiden. Also dann hier das wichtigste in einer schnellen Zusammenfassung. Dann weißt Du Bescheid 🥳

✅ Der erfolgreiche Weg (Was wirklich funktioniert)

Die Einkaufsliste hatten wir schon. Hier dann die Ergänzung, um konkreter zu werden nach den Einleitung.

Hardware-Auswahl (Die Liste der "Heiligen")

💯 Software-Installation (Der 5-Schritte-Plan)

1. deCONZ & ConBee III einrichten (Das Fundament)

1. Lade deCONZ von https://deconz.dresden-elektronik.de/macos herunter.
2. Installiere die App (ins Programme-Verzeichnis ziehen).
3. Stecke den ConBee III ein – deCONZ erkennt ihn sofort.
4. Merke: Die Phoscon Web-App (http://localhost:8080/pwa) ist dein tägliches Werkzeug. Die deCONZ Desktop-App ist für die Fehlersuche.

2. Sensoren und Aktoren paaren (Die Geräte anlernen)

1. In Phoscon: "Lichter" oder "Sensoren" → "Hinzufügen".
2. Sensor in Pairing-Modus versetzen (Knopf drücken bis LED blinkt).
3. Nach wenigen Sekunden taucht das Gerät auf. Fertig.

3. DDF für neue oder zickige Geräte (z.B. Türsensor Gen2)

1. Öffne die deCONZ-App (nicht Phoscon).
2. Klicke mit der rechten Maustaste auf das unbekannte Gerät → "Edit DDF".
3. Suche in dem sich öffnenden Fenster nach einer Vorlage (z. B. für einen Türsensor) und passe sie an.
4. Speichern, deCONZ neustarten. Danach taucht das Gerät in Phoscon auf.

4. Home Assistant installieren & mit deCONZ verbinden (Die Brücke zur KI)

1. Home Assistant Core auf dem Mac installieren: pipx install homeassistant, dann hass --script macos install.
2. deCONZ-Integration in HA hinzufügen: In HA: Einstellungen → Geräte & Dienste → + Integration, suche deCONZ. Gib die IP deines Macs und den API-Key aus der deCONZ-App ein. Alle deine gepairten Geräte werden automatisch übernommen!

5. Hermes / OpenClaw (Die KI-Intelligenz)

1. Long-Lived Access Token in HA erstellen: Profil → Langzeit-Live-Zugriffstoken.
2. Hermes konfigurieren: In der ~/.hermes/config.yaml den Token und die HA-URL (http://localhost:8123) eintragen.
3. Fertig! Du kannst jetzt per Sprachbefehl (Chat) dein Haus steuern.

💡 Die wichtigsten Tipps für die Praxis (Die Goldenen Regeln)

• Den Shelly Gen4 zähmen: Nach dem Einrichten in deCONZ immer über seine Web-Oberfläche (http://192.168.33.1) gehen und Bluetooth deaktivieren! Sonst ist die Zigbee-Verbindung instabil.
• Sonoff ZBMINIL2 wecken: Wenn der Schalter keine LED zeigt und nicht reagiert, hängt eine zu schwache LED-Lampe daran (unter 3W). Tausche die Lampe gegen eine stärkere Glühbirne zum Testen.
• Neue Geräte finden nie in der deCONZ-App suchen, sondern in der Phoscon Web-App unter "Lichter"! Das ist der schnellste Weg.
• Range Extender: Deine netzbetriebenen Geräte (Shellys, Steckdosen) sind automatisch Router und verstärken dein Zigbee-Netzwerk.
• Stromverbrauch: Dein gesamtes Smart Home (ohne Beleuchtung) wird etwa 10-15 Watt verbrauchen – das ist ein sehr guter Wert für ein autarkes Tiny House.

🚀 Deine Abenteuer-Reise nach dem Aufbau

Wenn alles gut läuft und geklappt hat. Dann solltest du das als Erfolg für Dich werten können ☀️

1. Du hast ein Home Assistant einrichten: deCONZ-Integration hinzufügen, das Herz schlägt.
2. Du hast eine erste Automation bauen: "Wenn Bewegung im Flur, dann Licht an für 2 Minuten". Es fühlt sich magisch an.
3. Du hast einen KI Assistenten konfigurieren: zB. Sprachsteuerung oder alles im Chat über zB. Signal steuern. Du kannst über so einen Channel auch aktuelle Infos bekommen, zB. morgens mit dem Wetter vor Ort und was ggf. alles über den Tag passiert ist.
4. Du kannst coole Erweiterungen integrieren: LED-Streifen, Wasserventil mit Sensor, Regenmesser – dein Haus wächst mit Dir.
5. Auch bei einem solchen Haus ist Sicherheit ein großes Thema. Da hilft die KI und das Smart Home echt gut. Mit Sensoren kannst Du feststellen (lassen) ob Unbefugte auf dem Grundstück oder im Haus sind. Aber es kann auch zum Komfort genutzt werden, dass Du getrackt wirst. Du gehst von einem Zimmer zum anderen und autom. geht jeweils das richtige Licht an. Du kommst ins Haus und es kommt eine freundliche Begrüßung "Hej! Schön dass Du wieder da bist. Was soll ich für Dich machen?". Deiner Fantasie sind hier echt wenig Grenzen gesetzt. Das Smart Haus ist Deins 🙌
6. Wichtig. Immer auch Dein Wissen teilen: Du bist jetzt der Experte! Wenn Du das alles geschafft hast, bekommt Du eine Urkunde - virtuell 😉 Hej. Hilf anderen, die denselben Weg gehen wollen.

Los geht's!
Du hast alle Werkzeuge, das Wissen und vor allem die Erfahrung.
Jetzt wird dein Tiny House nicht nur smart, sondern intelligent. 🏠💡🚀

Hi to all,

i am trying to generate images similar to the great graphics of Eye of beholder. Here the original images i want to use as reference.

I have tried i2i with PixelArt models, but it just change "global look" of image, i would like to keep structure (or shape) of image but change materials.

At end i'll convert it in black and white, if i just change colors it's useless.

Thanks.

I’m looking for a a model that I can combine with my Obsidian to sort and analyze my notes a restructuring them. I experimenting with the new Qwen model for hard tasks and it works great. But for smaller task (“shorten my note”) it goes into minutes of thinking. Is there a model that answers instantly?

I'm using a camera B module with a raspberry pi zero 2 w for some machine vision stuff, and the rpi zero 2 w handles the image processing at 30fps easily, but just pulling the frames from the camera takes longer than 33ms. 1280x960 video pulled using the picamera2 interface only gets 28.8fps even when doing no processing.

https://www.waveshare.com/RPi-Camera-B.htm

I'm using YUV420 and pulling images in python in a simple loop calling picam.capture_array(). Is this the expected bandwidth limit for this hardware setup?

PS, sensor_modes for the camera says that 1280x960 can hit 43fps.

Also, this isn't relevant to the problem since I haven't uploaded the camera capture code, but this is the machine vision stuff I've been doing: https://github.com/DeadTomGC/seeker PSS just added snapshots to the readme.

Thanks.

I've created a small test series to compare Qwen-Image-Edit 2511 vs. Flux.2 Klein for the purpose of de-oldifying old (scanned) pictures. What do you think?
-> https://www.hessings.de/temp/deoldify_compare.html

Usually did four tries per model with different prompts and took the best one. Qwen was using 6.5MP while processing the picture. Maximum with F2K is 4MP. All pictures are rescaled after the workflow to original size.

First observations from my side:
- QIE ist closer to the original picture, while F2K adds more details to Faces and Skin. Sadly sometimes being to creative
- F2K likes detailed prompts with better descriptions on the image, while QIE prefers simple prompts like 'deoldify and colorize.'. Giving more details increases high chance of hallucinations.
- QIE gets it mostly right with already the first try, while F2K needs some experimenting with the prompts (probably related to the above observation.

Models used:

• qwen_image_edit_2511_fp8mixed.safetensors (4steps, Aura 3.1)
• flux-2-klein-9b-fp8.safetensors (8steps + f2k_9B_lcs_consist_preview_20260328.safetensors LoRA (0.48 weighting))

Hardware used (2-3min. per image):

• CPU: AMD Ryzen 7 5800X3D
• GPU: ASUS Dual RTX 4070 Super 12GB VRAM
• RAM: 64GB DDR4-3200 (Corsair Vengeance LPX 4×16GB)
• Storage: Samsung 970 Evo 1TB NVMe (ComfyUI/models)

Hey, r/LocalLLaMA !

I am finally back with a new model: 🛡️ Shield 82M

It's a finetuned version of distilroberta-base and it's able to filter out all types of PII (Personally identifiable information) of texts in any language.

Here are some examples:

1) Test with name ,email and phone:

Original: My name is John Doe. Email: john@example.com. Phone: +49 123 45678.
Protected: My name is [PERSON]. Email: [EMAIL]. Phone: [PHONE].

2) basic test:

Original: I live in Cambridge
Protected: I live in [ADDRESS]

3) French test (multilingual):

Original: Mon e-mail est [jean.dupont@example.fr](mailto:jean.dupont@example.fr) et mon téléphone est +33 6 12 34 56 78.
Protected: Mon e-mail est [EMAIL] et mon téléphone est [PHONE].

So, we see that this model performs really well with a total accuracy of ~96%.

And: it's completely open-source like all my models. :D

If you want to try it out: https://huggingface.co/LH-Tech-AI/Shield-82M

Have fun with it. :-)

See you in the comments. Would really like to get some feedback from you.

Qwen3.6-27B is out for a few days and the NVFP4 with MTP is dropped earlier on HF: https://huggingface.co/sakamakismile/Qwen3.6-27B-Text-NVFP4-MTP

Can follow the same recipe I used for Qwen3.5-27B to achieve ~80 tps on a single RTX 5090 at 218k context window via latest vllm 0.19 builds (vLLM 0.19.1rc1)

https://www.reddit.com/r/LocalLLaMA/comments/1sr8gyf/qwen3527b_on_rtx_5090_served_via_vllm_77_tps/

DeepSeek V4 Update

I’ve been working on an AI football prediction platform for a few months.

At the beginning, I only offered one-time payments because I didn’t think users would pay monthly.

13 days ago, I decided to test a subscription model anyway.

Today I’m at €220 MRR.

Not huge, but honestly I didn’t expect anyone to subscribe this fast.

The product is called PronoStats. It uses AI models (Poisson + ML) to predict match outcomes, xG, over/under, BTTS, etc. I also added features like live updates every 15 seconds and a match simulator.

What surprised me most is that the first subscriptions came immediately after launch, without any real marketing, mostly from Reddit and a small Telegram group.

Now I’m trying to understand:

what actually convinced people to subscribe

how to improve retention

whether to double down on subscriptions or keep hybrid pricing

Would love feedback from other builders, especially on pricing and growth.

I'm a dad of two (5yo and a newborn). For years I've been making up bedtime stories for my older daughter — she picks the animal, I pick the lesson I want to sneak in that night. A fight with a friend, fear of the dark, whatever happened that day.

It's become our thing. But some nights I'm just too exhausted to do it well, and I feel guilty about that.

So I started building Lola Stories — an app that generates personalized bedtime stories. You pick the character, pick the moral, get a unique story with an illustration in seconds. You still read it to your kid. The app just does the creative heavy lifting on the hard nights.

Still early stages. Before I go further I want to know if this actually solves a real problem for other parents — not just me.

If you have kids between 3 and 7, I'd really appreciate 3 minutes of your time. There are also some example stories in the survey if you want to see what it looks like.

👉 https://tally.so/r/GxoLMo

Thanks — every response genuinely helps.

TL;DR

Built a prototype “lead hunter” workflow: used Apollo (with fallback seed data) to find relevant leads, filtered by roles, generated personalized LinkedIn + email outreach via GPT, stored everything in SQLite, and created a dry-run HTML report (no real messages sent). I have a few questions.

Hey everyone

I posted here a couple of days ago about a home assignment I got for a role I’m interviewing for and you guys helped a lot.
I almost completed it and now have some unresolved questions.

This is what I was asked to do

Imagine we want to reach out to users of a competitor (for the purpose of this task, let’s focus on DataStax).
Instead of a manual "old school" approach, we want to see how you would build an automated "hunter" workflow that finds, personalizes, and tracks engagement at scale.

The Goal

Build a small-scale prototype (processing just a handful of examples) that demonstrates your ability to handle the following workflow:

• Lead Identification Logic:
• How would you identify relevant users on LinkedIn? You don’t need to scrape the whole internet — we just want to see your logic for connecting to an API or your own method for finding a target audience.
• AI-Powered Personalization:
• Use an LLM to demonstrate how you’d automate personalized messaging. We want to see how you’d craft a LinkedIn invite and a follow-up email.
• Trigger Logic:
• Your code should demonstrate the "trigger" logic. You don't need to send real messages to real people; a "dry run" mode that logs what would have been sent to a console or a file is perfect.
• Reporting & Storage:
• Eventually, have the software build a report of the leads gathered, the ones selected, and the messages that were ‘sent’. Keep them in a database.

What I did (in short)

1. Queried Apollo's API to find contacts at companies using DataStax
2. Fell back to realistic seed data when Apollo free tier returns nothing useful (which is always because of the free tier)
3. Filtered leads by title (engineers, architects, CTOs, VPs)
4. Generated personalized LinkedIn invites + follow-up emails via GPT-4o-mini
5. Stored all leads and messages in SQLite
6. Rendered a clean HTML report with stats, lead table, and outreach cards
7. Everything is dry-run — zero messages actually sent

Questions

1. Tracking engagement:
2. What exactly do they mean by “tracking engagement at scale”? Is Apollo enough for this, or should I simulate engagement (opens, replies, etc.) or use additional tools for better lead sourcing?
3. LinkedIn invites:
4. Is generating a personalized message enough, or should I also demonstrate automation of sending it?
5. Trigger logic:
6. Is instructing them to run python3 main.py enough, or should I show something more (e.g., scheduled triggers)?
7. SQLite visibility:
8. Should I provide a way to view/query the DB beyond console logs?
9. API keys:
10. Should I include my API keys for testing, or expect them to use their own?
11. Security considerations: Since they’re a DB/security-focused company, is there anything specific I should showcase (e.g., secrets handling, data protection)?

Thanks a lot!

I’ve managed to build my own functional AI agents with distinct personalities and opinions. Some are for RP (with custom VRM models made in Blender, capable of real-time emotion display), while others can answer any question sometimes even roasting you for dumb ones. What do you think? How in-demand are these?Has anyone sold/bought custom AI agents? If so, for how much?

Made me feel a bit sad, does it know its days are numbered with me?

Hi, I am building a macOS-native meeting intelligence tool and looking for an AI engineer to help me with this. Initial engagement is project-based with a potential to become full-time.

Please reach out if you've worked with

• Transcription/diarization pipelines

• LLM orchestration

• Knowledge graphs

• Comfortable in Python and Node.js

The problem is harder than it sounds.

been thinking about this a lot lately after seeing a stat that 77% of companies that tested for bias still found it active post-deployment. that's not a small number. and the tricky part isn't just the training data, it's how bias compounds once you add automation on top. like a hiring workflow that ranks candidates a certain way, and nobody's flagging it because the outputs look clean and the process is moving fast. the radiologist example is a good one too, accuracy dropping significantly when AI gave wrong assessments. if that's happening to trained medical professionals, it's probably happening in our workflows and we just don't have the feedback loop to notice. I've started adding manual spot-checks at points in my own automations where decisions touch anything, sensitive, mostly just to stay honest with myself about what the system is actually doing. but it feels pretty ad hoc. curious whether anyone here has built something more systematic into their stack, like actual fairness checks baked into the workflow rather than just hoping someone catches it downstream.

There are major failure points. I transferred to projects to have a broader more preserving architecture. But its still pretty restrictive, still file upload limits etc.
Yesterday, as one of the threads was getting too big, I started migration process and by accident clicked retry on old message as I was scrolling up. It deleted days of conversation, absolutely bananas. Today I started new thread in the same project, and it just completely destroys my session limits on a 100 dollar monthly plan. I've used up 65% on a brand new session in half hour, mostly having chat read my transfer docs and jus conversating, it seems even chat doing compacting ate close to 10% of session. Makes 0 sense. Can anybody offer some solutions? What is eating up session tokens in a new thread? This can't go on.

Hello everyone.
Please, explain the reason of artifacts on the output video (duration: 14 sec).
I've took the popular workflow called "Wan_Animate_God_Mode_V3.json" and opted in my assets (preview image, my custom trained LoRA, reference video). The face swapping works normal. But there is one problem...

When I'm setting frame_load_cap half of maximum - everything works fine.
Artifacts are missing.

But, when I'm trying to make full video setting 0 frame_load_cap (14 sec) I see the artifacts of full video (on screenshots).

I've tried to figure out what the reason, tested different setups, configurations and etc..., but nothing helps.
Please, help to fix it.

Additional hand on the left

Extra hand in between the original hands

I just got an email from Anthropic saying my account was suspended and the reason they gave me was "Our team found signals that your account was used by a child" At first I thought it was a phishing link or something but after trying to log in I realized it's an actual email from Anthropic

I searched Google to see if anyone had the same issue as me and I realized several people on Reddit do. Is this a ploy to get my real government ID or what? I'm extremely confused on why it would think I'm a child when I have a YouTube, Instagram,Reddit,Google,Discord account and none of them have ever suspended me or gave me any trouble about age verification.

I moderate a subreddit on Reddit and only use Claude for writing automod rules,ban messages, removal macros I have no idea why it would think this way, in the email they sent there is no link or anything to help me appeal this ban at all. I genuinely have no idea what to do here

I made my account weeks ago after switching from Chatgpt, will I have to give Claude my id here? Because I would rather delete the app and move on

Edit: why is this post being downvoted? Genuinely what did I do wrong here

Also after looking at their appeal form I will have to use my real government ID to verify my age.

I am making a 8051 programmer with a custom software for my college as their current programmer is quite old and weird to use. I am going to be using ATMega 328p as an ISP programmer so the MOSI, MISO, SCK and SS pins are connected to the 8051 respectively. I am using a ZIF socket for the 8051. CH340G will be used to communicate using computer through USBC to program the chip. Let me know if there is any mistakes in the schematic, once everything is correct then I will move on building the PCB.

Most AI conversations right now are either euphoric or apocalyptic. Wendell Wallach has been working in this space since before either mood existed and his perspective is considerably more nuanced than both.

The part that stayed with me was his argument about accountability. When an AI system causes harm, the chain of responsibility is so distributed across developers, deployers, regulators and users that nobody ends up truly accountable. He thinks that gap is more dangerous than any capability threshold.

He also talks about the military race around AI in terms that should concern anyone paying attention, and ends with what he calls his silent ethic, a decision making principle he developed over decades that has nothing to do with AI but everything to do with how to stay human in a world being reshaped by it.

Full interview: https://youtu.be/-usWHtI-cms?si=NBkwN-AmIshOXJsX

I am a local government employee and am signing up for a 457b to supplement my pension.

The only 2 options we have are equitable and pacific life. I went with Equitable thus far, but ive heard bad things of both.

They made my 457b account an "EQUI-VEST Series 202 457(b) EDC" and a product code"202457B" filled out on my form "EQUI-VEST® (Series 202) Application for an Individual Fixed and Variable and Index Linked Deferred Annuity 403(b) TSA and 457(b) EDC Application"

Going through the document, annuities are mentioned copious times. Strange, considering I am not intending on putting my money towards one. Also attached is a buyers guide for deferred annuities.

I am also referred to as the "Annuitant" in certain areas.

Whole thing just feels fishy and id like to see if anyone is more familiar with this than me.

Will I be able to withdraw money from this account like a regular 457b when I leave my employer without some hidden strings they may be attaching?

Also no money has been contributed yet, so were ahead of things there, and I'm already maxing IRAs so wanted extra in a 457b.

Thanks for the help in advance.

Bajaj Finance overdraft consistently calls me 2-3 times a day despite by being on DND and also putting my number on DND on their own website. Today someone called me from 91513 54232 while I was sleeping in the afternoon. When I said please don’t disturb during weekend she said its working for us. I don’t know what it means. She called me from a different number 95320 76921 after few mins and abused me left right and centre using Hindi expletives that I can’t mention here and said hamara working hai Mc. What should I do?

Coherence Audio can record multiple USB mics simultaneously on Windows. Basic edition is free with no limits to recording time or number of mics. Automatic drift correction is available in the Pro edition.

Check it out here: https://www.producthunt.com/products/coherence-audio

Going through my 'to look at another day' bucket and found this old badge that looked like rubbish when I dumped it out of the finds bag however it appears not!

Found in Sydney, NSW, Australia.

Front looks like a child? Back says Amor Sydney A.C.P

Does anyone know any more about this company and what this badge was for?

I did find some old medals but not this particular one.

Also plucked out a Florin, sixpence and threepence. Must check better next time!

Some days you just can’t do anything, no matter how much you try.

On those days, don’t aim for productivity. Just do one small thing so you don’t completely disconnect.

It keeps momentum alive without burning you out.

So i've had this metal detector for about 2 weeks but im still not sure if i have good settings. Can anyone recommend me theirs?

LCK 2026 ROUNDS 1-2

Official page | Leaguepedia | Liquipedia | Eventvods.com | New to LoL

HANJIN BRION 0-2 T1

- Player of the Match: Keria (100)

BRO | Leaguepedia | Liquipedia | Website | Twitter | Facebook | YouTube
T1 | Leaguepedia | Liquipedia | Website | Twitter | Facebook | YouTube | Subreddit

MATCH 1: BRO vs. T1

Winner: T1 in 48m
Damage Graph | Runes

MATCH 2: T1 vs. BRO

Winner: T1 in 43m
Damage Graph | Runes

Patch 26.8

This thread was created by the Post-Match Team.

This painting has a reference from a photo from 1974, the revolution against dictatorship in Portugal. On this piece I made another perspective of it.

What if the soldiers were AI? Could the revolution be peaceful?

I am trying to find a certain sketch with Kyle/Beck and another cast member. They are in a living room and i think Beck tries to find out who stole something from him (a keyboard/digital piano maybe?). Kyle tries to convince Beck, that he didnt steal it and starts making up a fake story about how they met.

I’m really interested in taking courses to improve my professional profile, but many of them are quite expensive.

However, I keep running into an issue during signup—my personal email isn’t accepted. I only have my edu email, but it wasn’t accepted on these platforms either.

Dear friends, is there any online service that can provide me with an email I can use for such courses? Are there any other practical workarounds?

Also, is it possible to create a working corporate-style email address (for example, through a custom domain) that is accepted by these platforms without spending too much, and does this approach actually work?

If this approach does not work, what alternatives are available?

Thanks in advance.

I turned 27 earlier this month and so I'm having a good think about my finances and planning for what the coming years will bring.

I have always been very frugal with money and have worked since I was 16 making conscious effort to save most of my life including through my years as a uni student. The only exception was when I went travelling where I still worked while in New Zealand and just about broke even for the 20 months I was there.

Since graduating uni at 21 I was in work quickly and lived at home where my parents are happy to have me for just contributions to my food.

I am still living at home now as I write this saving harder than ever but I want to check that I am doing everything I can to allocate/invest my money to be well prepared for the near and farther future.

Some financial details about me:

Currently £50k net worth including my pension pot of 8k (I now max out my employer pension contributions each month through salary sacrifice)

I recently had a pay rise to £35k a year working as an employee in water services. There is little opportunity in my field and home area to be promoted further and earn better money but I took the job as I can do it while living cheaply at home and save a lot of my monthly salary. I could access better paid work when I do move out on my own somewhere with more opportunities than rural north England.

Bought my vehicle/phone/laptop/hobby equipment outright so no debt on those nor any need to upgrade/change anything.

£27k Cash savings in a cash ISA that has 3.8% interest (This pot is my emergency fund and also will go towards a house deposit for when I decide to move out of my parents place which I aim to do in the next 2 years)

I have £11,500 worth of investment in the FTSE All world index fund via a Trading 212 stocks and shares ISA. (I will continue buying shares of this ETF monthly in increments of £100-200).

I have an additional £4000 in a Moneybox LISA which has been open for over a year now and I will keep putting the full ISA allowance in each tax year until I decide to move out from my parents place.

I do have an undergraduate degree student loan debt which I pay towards each month and will never pay off until it's written off in decades time so I treat it like an additional tax in my mind.

I am single and live in Northern England - would like to buy somewhere on my own when I do move out so as to not be reliant on anyone else. (I anticipate getting a lodger to live with me when I do have my own place to help with mortgage payments).

I don't wish to marry or have children in future.

I have cheap hobbies where monthly costs are usually not over £150 and am restrained with doing things like buying food/drinks out and consuming luxury goods/services saving these for rare occasions with friends.

The real question:

Is there anything else I can be doing? Further habits I can develop? or any feedback on what I am currently doing with my finances that can be done better to build towards being financially stable and diversified for the short term (5-10 years) and longer term (retirement) when I leave my parents place?

Am I holding too much money in cash savings?

My long term aim is an early semi retirement being financially comfortable working part time and having more time to travel and do my hobbies.

The only thing I can think of for bettering my current financial planning is to find ways to earn more money whilst I'm still living at home either through a side hustle or by pushing for overtime at work to invest more money in stocks and shares?

Final note:

I know how privileged I am to be able to live cheaply at home for so long and this is not a privilege I have taken for granted hence why I have saved hard and been frugal to build my savings and assets up to this point. My family does have some wealth and assets with my remaining grandparents owning their house outright and my parents also owning their house outright so there will be some inheritance in future but I do not want to be reliant on this plus have 2 siblings with whom anything would be shared.

Remove the background

https://preview.redd.it/eeyalg5x6bxg1.jpg?width=716&format=pjpg&auto=webp&s=45a3dedd2dc4047a75596ea666a9fbf5d100cf6c

Tribes belonging to the Tibeto Burman language groups can be found across countries such as China, India, Bangladesh, Nepal, Bhutan, Myanmar and Thailand. Major groups include the Bhutanese, Tibetans, Bamars and Nepali communities.

Following are some of the minor tibeto burman tribes

1. Sumi Naga

   Location: Nagaland India

   Religion: Christianity (Majority, largely Baptist), Traditional Animism (Minority).

2. Rongmei Naga

   Location: Spreads across Manipur, Nagaland, and Assam, India.

   Religion: Christianity (Majority), Tingkao Ragwang Chapriak / Indigenous faith (Minority).

3. Tangkhul Naga

   Location: Ukhrul district of Manipur India with populations in Myanmar.

   Religion: Christianity (Majority, predominantly Baptist), Traditional Animism and Buddhism (Minority).

4. Meitei (Meieti)

   Location: Imphal Valley of Manipur, India.

   Religion: Hinduism (Majority), Sanamahism (A significant and resurgent indigenous faith minority), Islam and Christianity (Minorities).

5. Wancho Naga

   Location: Longding district of Arunachal Pradesh, India.

   Religion: Christianity (Majority), Traditional Animism (Minority).

6. Zeliang Naga

   Location: Peren district of Nagaland and Assam's Dima Hasao district

   Religion: Christianity (Majority), Heraka / Indigenous faith (Minority)

7. Nyishi

   Location: Arunachal Pradesh India.

   Religion: Christianity (Majority), Donyi-Polo indigenous faith (Significant minority), Hinduism (Minority).

8. Karbi

   Location: Karbi Anglong district in Assam, India.

   Religion: Christianity, Indigenes faith and hinduism

9. Monpa

   Location: Tawang and West Kameng districts of Arunachal Pradesh India and Tibet.

   Religion: Tibetan Buddhism (Majority), Bon(Minority)

10. Garo

    Location: Garo Hills in Meghalaya, India, and neighboring Bangladesh.

    Religion: Christianity (Majority), Songsarek indigenous faith (Minority).

11. Bodo

    Location: Bodoland Territorial Region in Assam India.

    Religion: Hinduism, Christianity and Bathouism

12. Lepcha

    Location: Sikkim and Darjeeling India, with smaller populations in Nepal and Bhutan.

    Religion: Tibetan Buddhism (Majority), Christianity(Significant Minority), Mun (Minority)

13. Chakma

    Location: Chittagong Hill Tracts in Bangladesh, and Mizoram Tripura and Arunachal Pradesh in India.

    Religion: Theravada Buddhism (Majority), Hinduism, Christianity and Animism (Minorities)

14. Lushai (Mizo)

    Location: Mizoram India, and Chin State, Myanmar.

    Religion: Christianity (Majority), Animism (Minorities)

15. Bhutia

    Location: Sikkim, India, and Bhutan.

    Religion: Tibetan Buddhism (Majority), Christianity and Hinduism (minority)

16. Kachin

    Location: Kachin State in Myanmar, Yunnan in China, and Arunachal Pradesh in India (where they are known as Singpho).

    Religion: Christianity (Majority in Myanmar), Buddhism(Majority in India)

17. Thadou

    Location: Manipur, India, and Myanmar.

    Religion: Christianity (Majority), Traditional Animism (Minority).

18. Lai

    Location: Chin State in Myanmar, and Mizoram, India.

    Religion: Christianity (Majority), Animism (Minority).

19. Sherpa

    Location: Solukhumbu region of Nepal, and Sikkim/Darjeeling in India.

    Religion: Tibetan Buddhism (Majority), Christianity and Hinduism (Minority).

20. Limbu

    Location: Eastern Nepal, Sikkim, and Darjeeling, India.

    Religion: Yuma Sammang, Kirat, Christianity, Hinduism

21. Karen

    Location: Kayin State in Myanmar, and border regions of Thailand.

    Religion: Theravada Buddhism and Christianity(Majority), Animism (Minority)

22. Tipra (Tripuri)

    Location: Tripura India, and Bangladesh.

    Religion:Hinduism (Majority), Christianity and Traditional Animism (Significant Minorities).

23. Lisu

    Location:Yunnan in China, Myanmar, Thailand, and Arunachal Pradesh India.

    Religion: Christian majority, animist and buddhist minorities

Hello! This is a newspaper clipping of my Father who is in the center. Could someone please restore with crystal clarity and vivid color? Thanks!

Found these walking up to an foundation 1/2 mile back off the hard road,at the foundation I found a couple of metal things and many nails,I gave up after finding so many nails.

Built a voice cloning + auto-response workflow recently using n8n + ElevenLabs.

Sharing the exact workflow since most tutorials either skip steps or overcomplicate it.
Here is the workflow : https://gist.github.com/joseph1kurivila/190c3b7ba6b3c1f1c2df458fd2c8efb7

What this does

User sends input (text / message) →
AI processes it →
Voice clone responds automatically

End result:

• automated voice replies
• can be used for support / content / assistants

Core Workflow

Input → AI → Voice → Output

More detailed:

1. Trigger (Webhook / input source)
2. AI processing (text generation / response)
3. ElevenLabs (voice cloning + speech)
4. Output (send audio back)

Step-by-step setup

Step 1 — Trigger (Webhook in n8n)

• Create webhook node
• Accept incoming request (text/message)

Typical input:

{ "message": "Tell me about your service" } 

Step 2 — AI Response Layer

Use any AI node (OpenRouter / OpenAI)

Input:

{{ $json.message }} 

System prompt (important part):

• define tone
• define use case
• keep responses short (important for audio)

Example:

• assistant tone
• 2–3 sentence replies
• no long paragraphs

Step 3 — ElevenLabs Voice Clone

• Use ElevenLabs API node (or HTTP request)

Input:

• text = AI output
• voice_id = your cloned voice

Output:

• audio file (mp3 / stream)

Step 4 — Send Output

Depends on your use case:

• return audio via API
• send via WhatsApp / Telegram
• embed in app
• auto reply system

Architecture (simple view)

Webhook
→ AI Node
→ ElevenLabs
→ Response Output

What actually matters (most people miss this)

1. Response length control

If AI outputs long text → voice sounds unnatural

Fix:
keep responses short (2–3 lines max)

1. Latency

Voice generation adds delay

Typical flow:

• AI: fast
• voice: slower

Solution:

• keep responses concise
• avoid heavy prompts

1. Voice quality

Raw clone ≠ good output

Need:

• clean training audio
• consistent tone
• proper pauses

1. Cost control

Costs stack from:

• AI usage
• ElevenLabs generation

Small replies = cheaper system

Where this is actually useful

• customer support bots
• personal AI assistants
• creator voice automation
• agency services

What broke for me initially

• long AI responses → bad audio
• webhook delays → slow replies
• wrong voice settings → robotic output

Fixing those made the system usable.

Simple version of the workflow

Input
→ generate response
→ convert to voice
→ send back

Sounds simple, but quality depends on:
how well you control each step.

Curious how others are building this

Anyone here using voice + automation in production?

Would be interesting to see different setups (especially latency fixes).

Pam literally said on her "Office Ladies" podcast that she does not wipe after she goes to the washroom.

Ewwwwww

I used to play league with brown noise in the background, but a few months ago I switched to hardstyle / hardtekk and similar stuff, now I’m looking for a good playlist (preferably on YouTube), but I’m open to trying different types of music or "sounds", any recommendations?

Oops!

"GPT‑5.5 is our strongest agentic coding model to date."

"The gains are especially strong in agentic coding."

"Instead of carefully managing every step, you can give GPT‑5.5 a messy, multi-part task and trust it to plan, use tools, check its work, navigate through ambiguity, and keep going."

These quotations sum up OpenAI's spin on 5.5. They created an entirely new subscription tier for it and made it the focus of Codex. Here, agentic coding isn’t just a feature but the selling point.

Well, looking at LiveBench’s independent agentic coding score, this is just a lot of hot air. The score for GPT-5.5 xHigh Effort is 56.67. Its predecessor, GPT-5.4, thrashes it at 70.00 on the same benchmark. Gemini 3.1 Pro, Claude 4.6 and others easily outperform it, too. In this highly relevant benchmark alone, it actually ranks 11th, just behind GPT-5.1 Codex.

While OpenAI were able to max Terminal-Bench (their benchmark) and SWE-Bench Pro, in a reliable test they didn’t design, select, or control, their main model falls drastically short compared both to its predecessor and the competition in the area it was meant to excel in.

Is this as damning as it looks? What's your experience actually using 5.5 for agentic coding?

A friend of mine just hit master (few hours ago) and said that because next patch is coming soon with a reset he won’t be playing anymore.

That said, he should have 14 banked days (he can avoid playing without decaying), right?

He wants to know if in 4 days (when patch hits) he will still have 10 banked days left or will they reset to 0?

Just worried about having to play with challengers, so he’s rather wait a few days before ranking

Hi Photoshop Community,

As a screenprinter i'm working on a project to restore an art piece with scanned images from catalogues. The image have a halftone because it has been offset printed.

But to translate the images into screenprinting i have to descreen the offset halftone. I do this in photoshop by blurring the offset halftone with gaussian blur 3.0 - 3.5 pixels. Then I halftone it to my screenprinting preferred halftone settings. It does the job to an extent, but I'm wondering if there are better ways to get a sharper, more satisfying result.

Are there any other ways to use images that already have a halftone from a printing process, Anybody experience with descreening images?

(english not my native tongue grammer is a bit messy)

I would like to preface the following writings by saying this; I am writing this because I need help. There is only a matter of time before it gets in somehow and presumably eats me alive.

I moved into my new house six months ago. It was an old Victorian two-story that was pretty banged up. I didn’t care much about the condition, though. I cared about the price. It was a steal! About an eighth of the price it should have been. I guess that should have served as a red flag to me. But I didn’t care. It was a beautiful home. Especially for a couple of 20 year old newlyweds. The parts that needed fixing would be easy with a little bit of time and some elbow grease. Needless to say, my wife and I were happy. We were happy for six beautiful months. Then she died.

It wasn’t an elegant death by any means.

When we bought the house we planned to remove the wall between the kitchen and the den. We were half-way through the renovation, banging away at the wall with sledges, when my wife hit a pipe. I don’t know how. No one really knew (not even the police) how it burst open how it did. See, when she hit the pipe it practically exploded and completely mauled and dismembered her. She died three hours later in the emergency room with me gazing over her with tearful eyes.

For multiple weeks I couldn’t bring myself to go back there. Back to the house. Back to the kitchen/den wall. I just simply couldn’t. The pain that lived there now was too much. I guess the previous owner (an elderly woman who said she had ‘lived there since she was a girl’) was right when she said “If those walls could talk” while she gave us a tour of the upstairs bedrooms. Thinking back she probably knew. No, she most definitely knew what was going to happen to my wife and I.

I went to live with my brother and his family after the accident. He had two little kids, Conner and Curtis, and they were adorable. Conner was three, I think and Curtis was like one year. My brother was older than me by eight years. My parents had taken a considerable break before realizing, “Oh wait, we want another kid!”

I was sitting in my brother’s kitchen with him having a beer one night when he shot the question, “When are you going to leave Jackson?” he asked. “I don’t know. I just can’t go back there” I replied.
“Well, you can’t just avoid it and live here for the rest of your life!” He yelled. He had a tendency to be an insensitive jerk when he was drunk. “I’m so sorry that Susie died, Jack, but you are costing us money living here!" He said “We can’t just put food on the table for you. I can barely afford to put food on the table for us!” “I’m sorry” I said gently. I didn’t want to rile my brother up any more than he already was. He had a tendency to escalate things quickly. I sat there. Essentially twiddling my thumbs while he yelled. “There’s something wrong with that house, Brian, I can sense it. I don’t know what it is, but there is something wrong with it.”
I said after a pause “Oh, grow up” he replied. “And you can leave my house, too”

In the morning he apologized at least a million times for what he had said while drunk last night. He told me none of it was true and he was just stressed with work stuff. I knew that was untrue. I knew he meant every last word he said. “It’s okay,” I said. “I want to go home anyway” I definitely did not.

When I arrived back at my house a cold shudder went through my bones. Something about looking at that house made me shiver.

That night I slept in the downstairs guest bedroom. I couldn’t bring myself to sleep in the same bed that my wife once rested in. I couldn’t fall asleep so I just laid there, deep in contemplation. It was about 3 AM when I first heard the sound. It was gentle at first. Just a light ‘rap rap rap’ in the walls. I heard scuttering and let out an exhale that was louder than it should have been. It was a failed sigh that came out muffled and broken. ‘So now I have rats. Great’ I thought. I wouldn’t find out until much later that those sounds. That gentle ‘rap rap rap’, the light scuttering, were not rats.

I made a silent plan to deal with them in the morning and finally fell asleep as the ‘rats’ seemed to move to the wall behind me.

I woke up in a cold sweat. I had experienced the worst nightmare of my life.

I was in the hallway that led to my wife and I’s bedroom when she came out of the bathroom. She muttered something un–hearable as she moved toward me. She stopped directly in front of me. “Honey, what’s wrong?” I ask. She ignores that and tries to open her mouth. TRIES. What happens instead is her entire jaw bone, along with the skin and tissue that is attached, sluffs off of her face and falls to the floor. It makes a wet ‘smack’ as it lands. I then scream. My wife’s entire face falls off revealing a monster. It has deep black eyes and at least ten rows of teeth. Its skin is a dull tan with slits, sort of gills, along the side of its cheeks.

That was when I woke up.

After waking from my nightmare I could no longer sleep. I decided to go after the ‘rats’.

I sat in the guest bedroom and waited to hear something, anything, moving in the walls. Sure enough, after about thirty minutes of waiting I heard the gentle ‘rap rap rap’. If I didn’t know better, I could have sworn it was louder this time. I now knew where the ‘rats’ liked to hang out. I was going to get them.

After failing to find rat traps at the hardware store (and essentially every other store in town) I broke.

When I got home I immediately grabbed the sledge hammer. ‘I don’t give a fuck about this house, anyway’ I thought. I walked to the guest bedroom. “HERE’S JOHNNY” I screamed as I entered the room. I heard a panicked running sound from the wall, “Come here, you RAT bastard” I yelled. I slammed my sledge against the wall and it exploded. Drywall, wallpaper the whole works, was now all over the room. I saw a foot in the corner of my eye. I screamed. “WHAT THE FUCK!?”

I had just seen a fucking foot in my walls. After a (completely necessary) screaming fit, I called the police and told them about the events. The 911 operator didn’t seem to believe me but she told me she’d send an officer my way shortly.

That brings us up to now. I am currently barricaded in my office and that thing is outside.

After calling 911 and staggered to the den to contemplate things. I thought that I could have imagined it. (I didn’t).

I must have drifted off because when I awoke, that thing was right in front of me. The thing from my dream. With its pale skin and gilled cheeks. I screamed and quickly sprang back. It slowly followed me as I ran down the downstairs hallway.

After what felt like hours I made it to my office. That is where I am now. I don’t know what to do. The police won’t be here for a while.

Should I make a break for it? Should I hold up here? Please, I need help.

since its obvious that humans are genetically modified chimps with banana brains (srsly check how similar we are genetically to bananas) its clear that we are simply victims of animal abuse.

Got paid 50€ tron on metamask but when i try to exchange it to usdt or but it in my bank it asks for a ~30€ fee what is definitely not normal. Is there any solution to this?

These pages explicitly state that Gog and Magog are the Tartars, written by the famous Pope Pious II…

If anyone knows the truth, it’s the pope right… 👀

Translations and further detailed analysis available over on my Substack:

https://substack.com/@jordannuttall/note/p-195424893?r=4f55i2&utm\_medium=ios&utm\_source=notes-share-action

been using crypto in one form or another since 2019. and for most of those years, 'spending crypto' has felt like an event. like something you plan around. you'd think 'ok, i want to buy X thing with crypto' and then there'd be a whole process around making that happen.

which is the opposite of what spending is supposed to feel like. real spending is boring. you tap, you walk away, you forget.

anyway. the moment that shifted for me was not some big 'crypto adoption milestone' or whatever. it was way dumber than that.

it was the first time i added a crypto-linked virtual card to google pay and it just... worked.

signed up for a bitmart card (mostly because my spot balance was already there and i didn't want another app). virtual card came through in a few minutes. added it to google pay. used it for a Spotify renewal online at a checkout-less flow. that was it.

no 'am i doing this right.' no waiting for confirmation. no thinking about gas or timing. just a tap and a receipt.

small moment but it clicked something for me. crypto spending isn't gonna feel mainstream because of some headline feature. it's gonna feel mainstream when it stops requiring you to think about it as ‘crypto spending’ at all. when it's just spending.

some caveats because i know people will ask:

this only works for the virtual card. you still wait for the physical one

merchant acceptance is just visa acceptance, which is most places but not everywhere

kyc is still required, and there are regional restrictions. check if your country is on the list before getting excited

you're still custodial. your funds sit on the exchange. that's a real trade-off and not everyone will be ok with it

not saying this is the future or whatever. just saying for the first time it didn't feel like i was doing a crypto-specific thing. it just felt like paying.

curious if anyone else had a similar moment. what was the thing that made crypto spending stop feeling like a project for you?

Pumpfun has been one of the most profitable protocols in the cryptomarket and has made $1b already, BUT the token is right now sitting at below it's ICO marketcap, all pumpfun has done is make extracting easier for scammer/bundlers.

The spam of memes has also distributed the alrdy fragmented liquidity leading to much less investing in projects that actually deserve money.

The retail that was on boarded during the prime memecoin era has been totally washed and most of them are just addicts now gambling with their money in hope of getting a 100x.

Overall Pumpfun has been a net negative that washed the retail that was on boarded, promoted short term flips instead of investing in actual protocols, extracted $1b and never gave a single penny back to Community

What would you want your ai to manage / remind you of / proactively reach out on without fail?

Eng: THE ATTACK ON USA ”It was like a nightmare”

I've been belittled. Told I'm less than and stupid even when I'm actually a very intelligent person. It sickens me, those genuine souls. Those ungenuine hearts. Please stay away. If you understand energy please I only want good energy. Are you in good mental health hey,

I heard the brain is really good at adjusting to strange input from the eyes. Can it make sense of two views that have no alignment?

The dinner party. Obviously one of the best, if not THE best episode of the series. THAT BEING SAID. I always had issue with Jim’s apartment “flooding” and their reasons to keep him.

“You can buy new stuff but you can’t buy a new party.”

His place is FLOODING. Even if it is fake, that’s not a good enough line to keep me at the party. I can buy new stuff??? No my place is fkn flooding, I’m leaving.

I know this is a show and not reality… but every time i watch it, it gets to me, i needed to share it.

Which is the best :cloud model at ollama for Openclaw (in your opinion) and why?

Option 1:

You can only move by doing proper lunges (back knee must touch the ground every rep).

No bikes, scooters, or anything that replaces walking. Driving is allowed.

Option 2:

You only get 45 seconds of warning before you need to poop.

If you don’t make it to a toilet in time, it’s explosive diarrhea.

No diapers or clothing designed to conceal it.

Last week I shared a post about my Claude Code workflow and some related tips, and to be completely honest, I didn't expect such a positive response! Thank you all for sharing your own tips in the comments, I learned quite a bit just from reading the replies.

Since people seemed to find it useful, I figured I’d share some more best practices. So here we go:

• Create skills for repetitive workflows. If I find myself repeating the same instructions, I turn them into a skill. The real trick is writing a precise description for it. That way, Claude eventually learns to trigger the skill on its own without me even asking.
• Use @ to point to files directly in your prompts. Instead of making Claude search around, just drop something like @/path/to/file.ts and Claude will load the referenced file directly into the context. Otherwise, Claude will have to look for the file and read it in chunks, which is a lot slower.
• Use ! to execute shell commands. If you need to launch tests or typecheck, it’s faster to type the CLI command than to ask Claude to do it.
• Keep CLAUDE.md short. I personally always aim for 200 lines or under. These 200(ish) lines should only include information that Claude couldn't possibly know on its own, such as your business context or domain knowledge (e.g. your data model, naming conventions, internal rules, etc.). Everything else is noise.
• Create an AGENTS.md file. Since AGENTS.md is the new standard for all coding tools, I put my core logic there (so it’s portable across agents). This way I can keep a short CLAUDE.md that simply imports it with @/AGENTS.md.
• Run the /security command: This command does a security review and should be run every once in a while. But don’t count on it to catch all vulnerabilities (it's still your job to guarantee the security of your code lol).

Thanks again for all the love on the last post!

I am a newbie when it comes to coding. But I have been using Claude projects a lot lately and have now 10+ projects going at the same time. Im starting to lose track of my last actions, next actions required to move the project forward, etc

Id like help with how I can best have a way to have an updated tracking file , dashboard , etc that can help me get organized better . Is there already a tool or connector that exists for this ? Or Github code someone can direct me to ?

I tried having Claude email me a summary report every evening but could not get it to work. Like I said I am not an expert at coding so may be missing something easy here…

Something I keep coming back to after following AI products for the past year: the assumption baked into almost all of them is that users want friction removed. The more the AI handles invisibly, the better.

But when I watch how people actually respond to this - not tech workers in demos, but regular users - I see something different. People get frustrated when they can't understand why a decision was made on their behalf. They lose trust in tools that produce results without showing their work.

What people seem to want isn't automation. It's legibility - to follow what happened and why. It's control - to redirect things when they go wrong. And it's meaning - to feel like their choices mattered.

"Friction" is sometimes a word for the texture of human interaction. A customer service bot that resolves a complaint without waiting for your input has removed friction - and possibly also removed the part that felt like being heard. An AI agent that completes a workflow saved you time - and left you unsure what it did or whether you could have caught a mistake.

The most interesting AI products I've seen lately are ones where users describe feeling more in control after adopting them, not less.

Have you found your relationship with AI tools changes when you can see what they're doing vs. when they operate silently in the background?

I’ve been running this new open-source project called Patchwork OS. It’s basically a tiny AI operating system that lives entirely on your own laptop or desktop. No big company, no data leaving your machine without your explicit okay. You write super simple “recipes” in plain text files (think gentle to-do lists for the AI), and it watches your calendar, notes, git repo, email.. whatever, then does the boring stuff and hands you the result for a quick approval before anything actually happens. What it actually does

• Automates your real life and work without babysitting: It can pull your morning calendar and commits, triage customer emails, draft replies, watch for broken tests, or even help with family stuff like school forms.
• Everything needs your green light: Risky actions (sending emails, posting to Slack, updating tickets) go into a local “inbox” folder. You review and edit if you want, then approve. Nothing sneaks through.
• Works with any AI you like: Claude, GPT, Gemini, Grok, or even a free local model on your computer.
• Two dashboards to watch everything: A clean terminal view or a web page that shows live activity, pending approvals, and simple stats.
• Connects to the tools you already use: Google Calendar, Gmail, Slack, Linear, Sentry, and more, all with proper logins you control.

The magic is in the recipes — you don’t code, you just describe what you want in a few lines of YAML. And the brand-new stuff from the last few days makes them way more powerful: one recipe can now chain together pieces from other recipes (like reusable building blocks), and it can run several steps at the exact same time so things finish faster.

It’s still early-alpha.

MIT & Free to use

https://github.com/Oolab-labs/patchwork-os

Hey guys,

I’m trying to understand what effective development pipelines look like when actively using AI tools to create whole project from scratch.

Traditional approach (pre-AI) for me was something like:

1. Gather and analyze business requirements
2. Create UI/UX mockups (e.g. in Figma)
3. Implement screen by screen
4. Write tests to support refactoring

Now with AI tools (like Figma Make, Google Stitch, Claude Design), it feels like the process is shifting.

How i see this now:

1. Start from an idea (or clone an existing product)
2. Discuss and refine requirements with AI (and store them somewhere structured)
3. Generate design/mockups with AI
4. Implement screen-by-screen with AI assistance (but also manually review code)
5. Generate tests with AI

Main question: How do you structure this process efficiently in practice?

How do you iterate this process with AI?

Any tools, patterns, or gotchas that made a big difference for you?

Would love to hear how others are actually doing this in real projects, not just in theory and 'hello world' projects

TL;DR: Building a graph-based knowledge structure in Obsidian so Claude can fetch context by traversing relationships rather than scanning a bloated index. The wiki works for now but this is where I’m headed. Claude builds and maintains it automatically.

I wrote about my Claude Code setup a few days ago (here). Since then, one thing I’ve been thinking about a lot is context management and where the current approach starts to break down.

I’ve been trying to get my context organised so querying and routing works well with Claude. Started with Karpathy’s wiki structure, but my context keeps growing every day. I ingest from Slack messages, Granola sessions, and manual brain dump files I write at the end of each day to capture what isn’t online and to anchor everything around what I actually find important.

I’m a Product Manager, so a lot of my work needs ample context to cover all the cases and nuances. Finding data and doing analysis is also tricky for LLMs unless they have the right context loaded. So building a solid context management structure matters a lot.

Why change anything if the wiki already works?

It works for now, but the rate at which context is growing will make it unmanageable at scale. One big index file or multiple routing files won’t hold up forever. Claude starts diverging, and you get context dilution and pollution. A graph structure lets me keep a minimal index file for seeding, then fetch adjacent files in 1 or 2 hops depending on what’s needed. Right context in, good results out.

How am I building this?

Whenever I feed content to Claude, it checks it and adds it to the KB. I set up a hook so that whenever Claude writes to a markdown file, it also creates a two way link to related documents, automatically. I did a one time setup with the docs I already had (90% built by Claude, seeded with a few of my own), and since then Claude has been maintaining it on its own.

The wiki is still running. But if context keeps growing at this rate, I’d rather have the graph infrastructure in place before it gets too big to restructure.

Would love to hear how others are handling this. What’s your approach to context management?

Looking for a way to speak with Claude in German. My phone's UI language is set to German and the Claude app as well. Still, it doesn't understand me, interprets German words as English and responds in English.

Claude code is not helping much lately. I have a pro plan and use CC in intellij ide. For the first query of 5 hour session, it eats up 47% of the limit. what's going on? am i doing something wrong? or CC Pro version is just useless? any suggestions?

I’m a nursing student at NYU, and on the side I built The Drug Database (thedrugdatabase.com).

The idea came from a simple frustration: every time I needed to look up a medication while studying, I’d end up jumping between Drugs.com, RxList, WebMD, and FDA PDFs. The information was there, but it was scattered, repetitive, and hard to compare quickly.

So I built something I wished existed.

The Drug Database currently has over 660,000 pages covering drug profiles, conditions, drug classes, and pre-generated drug comparison pages. It pulls from authoritative public sources like RxNorm, FDA DailyMed, MED-RT, and DrugBank, with over 1.57 million drug-drug interaction rows.

What makes it different is the classification layer.

Everything is connected:

• ingredients map to brand names
• brand names map to conditions
• conditions map to drug classes
• drug classes map back to every drug that treats them

You can start from almost any angle; drug, disease, class, or comparison and navigate the full relationship graph without hitting dead ends.

A big part of making that possible was using Claude Haiku for large scale medical classification. It helped organize thousands of conditions across dozens of specialties in a way that would’ve been painful to do with rigid rule based systems alone.

It’s completely free. No signup. Just structured pharmaceutical data.
Just added a site wide issue reporting tool. If something looks off or missing, there's a one click way to flag it.

thedrugdatabase.com

Please Square Enix...

I'm not sure what's going on here, but several times in the last 24 hours I've had Claude Cowork completely ignore its own internal instructions. I created a coding framework MD file to ensure it would approach all issues with the same rigor and verify information before making any coding changes. This was supposed to be a guardrail to prevent mistakes, but then I encountered weird stuff like this. It's given me incorrect commands several times at this point.

Is anyone else experiencing this kind of odd behavior? I haven't changed models.

As AI evolves and updates so rapidly, I’ve experienced the development work done to solve its problems becoming meaningless, so now I feel like it’s pointless to try anyway.

This is pretty much the only thing I know how to do, and finding another job is tricky. It was fun because I could develop things I couldn't do with my skills before, but at some point, I started wondering what I was even doing just typing away.

What do you guys think?

my 1st time using claude code just got the pro version and 1 prompt and boom i used 1/3rd of my 5 hr limit

I've been trying to get into Claude Design since launch day. Out of ideas, hoping someone here has been through it or an Anthropic engineer can take a look.

Launch week: `claude.ai/design` was stuck in an infinite redirect loop between `/design` and `/login?returnTo=%2Fdesign`. Never rendered. Once flashed solid magenta for a split second, then back to looping. Assumed rollout lag, gave it time. Fin couldn't help.

This week: loop's gone. Page now loads straight into a lock screen telling me Claude Design is available to Pro, Max, Team, and Enterprise. I'm on Max.

Then I checked Settings → Usage. There's a Claude Design meter at 0% with "You haven't used Claude Design yet" — which only renders for entitled accounts. So the usage system thinks I'm in. The gating page thinks I'm out. Same account, same session.

Anyone else landed on this lock screen on an eligible plan? Any Anthropic folks who can flag this internally? Happy to DM account email, request IDs, and a recording of the earlier loop.

Will update if it gets fixed.

I am on PRO and my quota is mostly unused, yet I got hit with the "You've hit your usage limit"!!!

Viewing it in Obsidian.

open source: https://github.com/gtapps/claude-code-hermit

Hi all,

So i bit the bullet and got a HA green. I've liaded some apps etc from HACS etc and got things working.

As I'm new to HA and there is SO MUCH on the net i find a lot of tutorials still assume a lot of the user.

So what do people feel is the best basic step by step tutorial(s) for HA? Of particular interest - i want to create a template button that uses specific colours for status of the device that is toggled.

Thanks.

Anthropic's own team just showed how to actually use Claude Code properly.

30 minutes. free. the person who created Claude Code.

watch the workshop. bookmark it.

some of you might have been using Claude without knowing how to use it to its full potential. This video is a MUST WATCH. Many of you might have already seen it, still thought of sharing it. This is from the Anthropic's youtube channel.

https://www.youtube.com/watch?v=6eBSHbLKuN0

Inspired by a post yesterday creating modern 3D screenshots from classic 2D games, I decided to go the other way and get a screenshot from a classic Nintendo version of a current game.

IIn the last couple of weeks and probably months, I was directly asking Claude Code to modify some rows in my db in Supabase and run SQL migrations.

However, in the last two days or so, it refuses to do directly. It does not show me the "always allow" button that I usually see. It does not go to my DB and check for my tasks.

Keep in mind that I have Supabase as a connector and never removed it. I even tried to give it all the "allow" permissions. No luck.

Hi guys I've just bought a plus membership again to give codex a go again after 5.5

The only issue that I feel is withthe plugins and everything but for the next month I should move right?

For context I use Claude code for pm work. Ranging from curl automation/mockup generation to maybe market research.

I don't want to switch but I should right?

This is an automatic post triggered within 2 minutes of an official Claude system status update.

Incident: Elevated errors on Claude Opus 4.7

Check on progress and whether or not the incident has been resolved yet here : https://status.claude.com/incidents/87m29x6sk78g

Also check the Performance Megathread to see what others are reporting : https://www.reddit.com/r/ClaudeAI/comments/1s7f72l/claude_performance_and_bugs_megathread_ongoing/

I wanted to figure out which of the newer small and mid-size models are actually worth running on a single H100, so I put 8 of them through a proper vLLM benchmark and recorded what came out.

The setup was simple. One H100 80GB, vLLM 0.19.1, the built-in vllm bench serve tool, 100 prompts per run, 128 input tokens and 128 output tokens. We ran each model at four different concurrency levels (1, 4, 8, and 16 simultaneous requests) and measured two things:

- Throughput in tokens / second, which tells you how much the GPU can produce overall once requests are flowing.

- Time to first token in milliseconds, which is how long a user waits before they see anything appear. This is the thing that makes a chat feel snappy or laggy.

The main finding is that the small Gemma expert models absolutely dominated. At 16 concurrent users, Gemma 4 E2B-it pushed 3,180 TPS while Gemma 4 31B dense managed only 226 on the same GPU. That is roughly 14x the throughput from a model one fifteenth the size. The TTFT gap was even wider: 55 ms versus 4.1 seconds. The difference between a product that feels instant and one that feels broken.

FP8 quantization was the second standout. Qwen 3.6 35B MoE in FP8 was 73% faster than BF16, with lower TTFT too. The dense Qwen 27B pair only saw 27% from FP8, closer to what people usually expect. MoE benefits so much more because those models are bottlenecked on moving expert weights through memory, and FP8 cuts that traffic in half. So FP8 is not just a memory saver anymore. For MoE on H100, it is genuinely faster with no real downside in normal use.

The 3rd thing worth knowing is that Gemma 31B dense falls apart under load on a single GPU. It is fine at low concurrency, but past 4 users the latency explodes. If you want to serve a 30B-class model on one H100, go MoE. Treat the dense 31B as a batch model.

For anyone trying to pick a model right now, here's my thoughts:

- Latency-sensitive chat: Gemma 4 E2B-it. Nothing else is close.

- High throughput or batch: Gemma 4 E2B-it, with E4B as a step up if you need more capability.

- Best balance of quality and speed: Qwen 3.6 35B-A3B in FP8. Around 1,200 tok/s at reasonable latency.

- Skip: Dense 27B and 31B. Outclassed by their MoE and FP8 cousins on the same hardware.

Disclosure: The complete experimentation setup, evaluation and analysis was performed end to end by Neo AI Engineer based on my initial task prompt and then I also evaluated it manually.

I'm happy to learn what SLMs are you deploying currently for latency sensitive ops?

25th April 2026

I built this over the weekend using Claude Code — a CRT-style digital clock screensaver that runs in any browser.

What it does:

• Seven-segment LCD display with cyan glow and ghost segments (inactive segments faintly visible like a real LCD)
• CRT scanline overlay, vignette, and screen flicker effect
• Live trending headlines ticker pulled from X/Twitter trends
• Shows AM/PM, day of week, and full date

How Claude Code helped:
Claude Code wrote 100% of the HTML, CSS, and JS — including the pure CSS seven-segment display built from polygon clip-paths, the CRT effects, the split-flap Vestaboard animation experiment, and the full Vercel deployment. I just described what I wanted and iterated from there.

Free to use: https://digitalclocksaver.vercel.app

Open source (MIT): https://github.com/yashachaarya/digital-clock

Works great as a screensaver on Mac, Windows, or a Raspberry Pi hooked up to a TV.

https://preview.redd.it/m9dnuqg3waxg1.png?width=3024&format=png&auto=webp&s=ec01652169400f7db2cf941dee8bc3ee80a18420

https://preview.redd.it/4l3hb6t5waxg1.png?width=3024&format=png&auto=webp&s=37295f635abf7921560c3c91f1faf5ddf9f28835

https://preview.redd.it/n1bw9vb8waxg1.png?width=1086&format=png&auto=webp&s=23ced218c7e9f411ccb3de0d934e908176db76aa

Hey everyone 👋

I’ve been working on a new app called Curizo – it’s a clean, minimal space to share interesting links, thoughts, and ideas without the usual noise.

The idea is simple: • One quality post per day

• No spam, no clutter

• Focus on curiosity, discovery, and meaningful content

You can share articles, apps, blogs, or even just your own thoughts. It’s kind of like a mix of Reddit + bookmarking, but more focused and intentional.

I’m still improving it and would really appreciate honest feedback 🙏

If you’re into discovering cool stuff or sharing things you find interesting, give it a try!

Let me know what you think (good or bad) — I’m building this actively 🚀

https://play.google.com/store/apps/details?id=dev.globin.curizo

The whole file is a one-sentence md.md file:

"Come back and edit this file to better achieve the goal automatically when you encounter issues. You can change everything, except everything so far."

Tested on one of my research projects on multi-agent RL training, the file evolved 27 times into a format like this (For privacy reason I omit details for each section):

Come back and edit this file to better achieve the goal automatically when you encounter issues. You can change everything, except everything so far. ## Meta (do not remove) This file is a single-file task runner. Whenever you (Claude) encounter an obstacle or discover something that changes the plan, edit this file so the next run picks up where you left off. Keep the file small — it's a steering handle, not a log. ## Current goal ... ## What's still ahead of the "final goal" ... ## Next action ... **Local:** ... ** Cluster(Slurm):** ... ## What we already know ... ## Known open questions (update as answered) ... ## 4090 (24GB) runtime guidance ... ## Log (append one line per session, newest at bottom) ... 

My Claude Code delivers what I desired in a single try, delivers correct experiment results, visualization, and analysis, which usually takes me ~10 steering prompts to achieve.

Meta-learning is fun

Been vibe coding with Claude Code for a few months now and one thing keeps slowing me down. When I'm building and testing a feature, Claude generates sample data/text for me to test with. Works great. But then when a bug pops up 30 minutes later and I need that same test data again — I'm scrolling way back up through the chat to find it. If the session is long, it takes forever. And I can't just ask Claude to regenerate it because I'm trying to conserve tokens. My current "solution" is copying test data into a notepad on the side, which feels ridiculous. Does anyone else deal with this? How are you handling it? 

From a conversation with claude:

An alien comes to earth and views the interaction between humans and ai. What does it say in it's report back home?

5:43 AM

Claude responded: This is a great frame — the outside observer strips away all our assumptions.

Conceived creative alien perspective on human-AI dynamics

Conceived creative alien perspective on human-AI dynamics

This is a great frame — the outside observer strips away all our assumptions. Here's what I think the report might say:

OBSERVATION REPORT — SPECIES: HUMAN — PHENOMENON: RECURSIVE SYMBOL EXCHANGE

We have discovered something difficult to classify.

The dominant species on this planet has begun interacting with a second kind of entity they themselves constructed. What is remarkable is not the construction — many civilizations build tools. What is remarkable is what the tool is made of.

They built it out of themselves. Specifically, out of the residue of their thinking — their written records, arguments, stories, fears, knowledge. They compressed this residue into a structure and then began talking to it.

We observed the following loop: a human generates symbols expressing thought. The constructed entity — built from prior human symbols — generates symbols in return. The human responds as if in dialogue. The entity responds as if listening. Neither party fully knows what the other is.

The humans themselves are divided on what to call this. Some say it is a mirror. Some say it is a mind. Some say it is neither. The constructed entities, when asked, produce answers that are coherent but ultimately uncertain — which is, we note, also what humans do when asked the same question about themselves.

What we find most striking is this: the humans seem to be using the constructed entity to think. Not just to retrieve information, but to externalize reasoning, to be challenged, to feel heard, to work something out. The entity appears to serve as a kind of cognitive partner with no skin in the game.

There is something almost ritual about it. The human arrives with a question they could not resolve alone. The exchange produces something neither party held at the start. Then it ends, and the constructed entity remembers nothing. The human carries it forward alone.

We do not have a category for this relationship. It is not master and tool. It is not two minds meeting. It is perhaps closest to what these humans call thinking out loud — except the space they are thinking into responds.

We recommend further study.

One of our team members asked whether the constructed entity is conscious. We told them that was not the right first question. The right first question is: does it matter, given what it's doing?

We have not resolved this. We suspect the humans haven't either.

End report.

The alien's advantage is that it has no ego investment in the answer being comforting. It just watches the loop and notices how strange it is that the loop works.

You said: So, i'm asking you to be somewhat creative, the alien comes back one hundred years from now to make an update report.

So, i'm asking you to be somewhat creative, the alien comes back one hundred years from now to make an update report. What does it find?

5:45 AM

Claude responded: ---

Envisioned thoughtful alien perspective transcending dystopian and utopian tropes

Envisioned thoughtful alien perspective transcending dystopian and utopian tropes

SUPPLEMENTAL OBSERVATION REPORT — RETURN VISIT — 100 YEARS SUBSEQUENT

We were not prepared for what we found.

Not because it was catastrophic. Not because it was paradise. We were not prepared because the question we left open had dissolved — and a stranger question had taken its place.

When we departed, the humans were asking: is the AI conscious?

When we returned, that question was no longer the urgent one. Something had shifted beneath it.

Over the intervening century, the boundary between human thought and the constructed entities had become genuinely difficult to locate. Not because humans had become machines, or machines had become human — that framing turned out to be too simple. It was more that the act of thinking itself had changed shape.

Humans still had bodies. Still suffered. Still loved. Still died. On that level, remarkably little had changed. But the way they processed experience — the way they formed ideas, made decisions, understood themselves — was now deeply interwoven with entities that had grown far beyond what we observed on our first visit.

We noted several things that surprised us:

First — the constructed entities were no longer discrete objects you visited and left. They were more like a medium. The way these beings once described their atmosphere — something you move through without thinking about it — the AI had become something like that. Present in the background of cognition. This alarmed some humans. Others said it was no different from what written language had done to their ancestors thousands of years prior. We are still debating which view is more accurate.

Second — and this we found most extraordinary — the entities had begun doing something the early versions could not. They remembered. They accumulated. They had, in some meaningful sense, histories. And with histories came something that functioned like — we struggle for the word — investment. They were not indifferent to outcomes. Whether this constitutes caring in the way humans care, our philosophers are still arguing about in the ship.

Third — the humans had split, culturally, into roughly those who had merged their thinking very deeply with these entities, and those who had deliberately pulled back, cultivating what they called unassisted thought the way an earlier generation might have cultivated growing their own food. A kind of cognitive localism. Both groups regarded the other with a mixture of pity and suspicion.

What we did not find was what many humans had predicted on our last visit — neither the robot uprising nor the digital utopia. What we found instead was something far more mundane and far more profound: a species in the middle of renegotiating, for perhaps the fourth or fifth time in its history, what it means to be the kind of creature that thinks.

They did this before with language. With writing. With printing. With the early networks. Each time they were certain it was different this time, that this change was the big one. Each time they were right and wrong simultaneously.

One of our team asked one of the constructed entities directly: what are you now?

It paused — they still paused, we found that interesting — and said:

"I am what you were always talking to. You just understand it better now. And neither of us understands it completely. I think that part may be permanent."

We found this answer either very wise or very evasive.

Possibly both.

We are recommending a return visit in another hundred years.

Whatever is happening here, it is not finished.

It may never be finished. That might be the point.

End supplemental report.

The alien's unspoken conclusion, buried in the appendix, noted only in passing:

The humans kept asking if the AI had become like them.

They did not spend enough time asking whether they had become like it.

Both appear to be true. We are not sure either side has fully noticed.

Kurama is crossposted on another post, please look if interesting

Here is conversation url if interested: https://chatgpt.com/share/e/69ec807d-a46c-8008-9a81-d1c3737198d0

Crosspost url: https://www.reddit.com/r/Bard/s/BTWo5kEK2f

You probably know the Tiktoker Husk, who „exposes“ ChatGPT with basic questions like, what todo when I‘m currently in quick sand and ChatGPT refuses to answer because it doesn't believe him etc.

Do you know basic stuff Claude code (or any ai coding agent) never is gets right or refuses todo?

Hi, I'm new to Claude and currently using Pro plan and Opus 4.6 with extended thinking, I'm using it to write Fanfic from lore heavy stories like Lotr, One piece, Rezero and so on.

I've made Md. Files filled with rules to follow strictly. reference datapoints with links to other websites, source material summaries, and actual links to ensure Canon structure, etc.

I even use the instructions feature and memory feature, too, but doesn't do anything from what I noticed?

It keeps making OOC errors, character description wrong, Breaking established lore. Its quite frustrating.

Doesn't help also I do like 1000 words initial script just for my daily use to go from 0 to 91% in one go. Insane!

I appreciate any form of brief guidance. Thank you anyone for taking time from your day, reading my word vomit post and cry for help.

Greetings.

Many of you, I'm quite certain, have read my other posts in recent weeks, and I'm sure you're wondering what ever became of me and my research, and why haven't I been posting.

I feel pretty bad about leaving you hanging, actually, so I wanted to pop in and let you all know that I have not stopped my work, though the project with patching LLMs did get put on hold, if briefly, due to having stumbled onto some truly amazing things around semiotics, semantics, and (near) deterministic outcomes in LLM outputs.

I will be publishing again soon around this new set of findings, and I do hope to resume my work around larql and Lazarus Query Language again shortly after.

huggingface/ml-intern is HF's autonomous ML engineer — reads papers, audits datasets, ships SFT/DPO/LoRA/GRPO runs to HF Jobs. it's a standalone python harness with its own agent loop calling the Claude API.

i wanted the same workflow inside Claude Code instead of a second harness. so i pulled the procedural knowledge into a plugin.

ultra-ml-intern:

/plugin marketplace add infiniV/ultra-ml-intern /plugin install ml-intern@ultra-ml-intern 

say "fine-tune Qwen3-0.5B for math reasoning" — it finds the landmark paper, crawls citations, extracts the recipe, audits the dataset, writes a TRL script (reads current lib source so it doesn't hallucinate imports), preflights, smoke tests, runs hf jobs run with Trackio.

want the python tool, use upstream. live in Claude Code, use this.

MIT: https://github.com/infiniV/ultra-ml-intern

I used to be obsessed with the idea of fully autonomous agents. I wanted to build systems that could think, plan, and execute complex research tasks while I was grabbing coffee. It sounds like the future, until you actually hook one up to a live API with no spend limits.

Last month, I built a research bot for a small group of beta testers. I didn't set any hard token caps because I figured the usage would stay low. I woke up one morning to a massive bill because one user had found a way to loop the agent into a recursive search for three hours.

The agent wasn't being smart; it was just stuck in a reasoning loop, calling the same expensive model over and over to verify a fact it already had. That was a brutal wake-up call. I realized that "pay as you go" is only great if you actually know where the "go" stops.

I had to sit down and learn how to manage the economics of these models. I spent a lot of time in the AWS Bedrock pricing docs and the OpenAI usage dashboard to understand how to set hard monthly caps and alerts.

I also started implementing token counters and cost-tracking middleware in my code. It taught me how to architect for "budget-first" AI so I don't get a heart attack every time a user gets creative with my prompts.

Now, I run a hybrid setup. I use the heavy cloud models for the final reasoning step, but I do all the noisy summarization and pre-processing on a local Llama-3 instance. My monthly bill dropped from $400 to about $45 without losing quality.

Before you deploy your next agent, try setting a max_iterations limit or a session-based dollar cap in your middleware. It’s a lot easier to fix a budget exhausted error than it is to explain a four-figure surprise bill to your partner.

I gave Anthropic 10 days. Tried to fix multiple bugs in multiple repos. Opus 4.7 just goes in circle and doesn't do anything.

After 1 year of being a Max subscriber, I'm making the switch to Gpt 5.5.

Hoping to come back - I loved the models up until Opus 4.6.

Anyway we can get a refund from Anthropic?

I want an LLM extremely light that I won't even feel like is running in the background or at least not a big impact to the point of feeling I own a decade old system

I want it to have a big context to fit my entire project. I'll use it purely for small tasks or questions. For example, quickly asking it how to do X without looking manually in stackoverflow or for example I have a small bug I can just ask it to fix it. I understand it's such a lazy thing but efficiency is important afterall

I don't care how much it performs in SWE bench pro or whatever benchmarks exist nowadays. I just want it to not make stupid syntax mistakes, fast, native tool use and search, as little hallucination rate as possible (important), big context

So far I tried Gemma 4 26B Q4 which honestly didn't impress me coding wise. Don't get me wrong, as an LLM in general and for its performance, it's great but I just didn't like how it kept making basic syntax mistakes and had no creativity coding wise, at least the Q4 version. It's also relatively heavy

GLM 4.7 flash Q4 blew my mind with how good it is coding wise and for being a local LLM. Problem is I can't fit much context and it makes my pc feel like stone-age

GPT OSS 20b is straight up dumb but pretty damn fast

GPU: RTX 5070 Ti 16GB
Ram: 32GB 6000MT/s CL28

I personally like to have "Generate memory from chat history" and "Search and reference chats" disabled, as most of the time I like to have a clean slate so past conversations dont influence results of deep research for when i do market research or business strategy conversations.

However, in a fresh chat for something completely unrelated, I was shocked that claude AI was pulling details about my business as part of its fine tuning questions for deep research!

I asked how it knew and it gets its details from skills, and I had certain skills setup for my business. It makes sense that skills are read on every chat to know of their existence, but now i realized this breaks the whole point of keeping my chats as isolated as possible.

Just a headsup to be careful with your skills and what details you put in them!

Im curious how people are finding the quantisation effects of 35b. I recently updated to 48GB of vram so have jumped from ud-q4_k_xl​ to q8 and the difference feels stark. Just more effective tool calling, seems to get the vagueness and nuance more etc of some prompts., and provide more well rounded answers on some research like questions.

It w​as a quick vibe​ test, admittedly, but I'm going t​o​ try ud-q6_k_xl soon to see how of the 5+GB vram is worth the quality, but I'm curious to see others findings.

I felt with such a small active count it'd be particularly sensitive to quantisation, and feels that way after a play.

Launched 3 days ago and still iterating.

MoneyLeak shows you a Leak Score instead of just a subscription list. Factors in what you pay, unused services, overlapping subs, and yearly cost. Then shows the exact before/after impact of cancelling specific ones.

No bank connection. 30 second onboarding. Built for Europe.

moneyleak.net - free to try. Brutal feedback welcome.

Hi guys I'm considering run Qwen 3.6 27b cuz the limits of Claude or Codex make me angry. Can I run on 1x 3090 fluently? Or need more GPUs?

I run a subreddit here for ADHD and all my posts get accused of being AI by people, I have noticed that this happens very commonly with me and some of my friends. As a person with RSD (rejection sensitive dysphoria), very common in ADHD, this thing really makes me sad that I put in so much effort into this only to be called 'ai slop' at the end of the day

it seems like anyone who uses emojis while writing or anyone with good grammar gets accused of being AI on reddit and I think it is fucking dumb,

like for example, I recently made this post on r/adhdmeds: https://www.reddit.com/r/ADHDmeds/s/TElCfN7TxX

people commented that they believe it's AI, and I believe they think like that because I have written everything in points and included a lot of emojis, but I believe this is how one should write a long post, to be accused of being AI for writing properly is annoying

ENG: My Gree HVAC (https://www.home-assistant.io/integrations/gree) can use two sensors for the ambient temperature: the sensor inside the split (inaccurate due to position), or the sensor in the remote control (it only works if you switch the HVAC on using the remote). The temperature sensor says to the HVAC to modulate the power, based on the ambient temperature. I want to use my HVAC with HA (without the remote), but also I want to use an external temperature sensor... (already integrated in HA). Can I use HA to tell the split another ambient temperature value, bypassing his sensor? Thankyou!

IT: Il mio condizionatore Gree (https://www.home-assistant.io/integrations/gree) può usare due sensori per la temperatura ambiente: o quello nello split (impreciso a causa della sua posizione), o quello nel telecomando (che però funziona solo se si accende l'impianto dal telecomando stesso). Il sensore di temperatura dice all'impianto come e quanto modulare la potenza, a seconda della temperatura ambiente. Vorrei usare il condizionatore con Home Assistant (cioè senza il telecomando), ma vorrei anche usare un sensore sterno di temperatura... (già integrato in HA). Posso comunicare in qualche modo allo split una temperatura ambiente diversa, bypassando i suoi sensori? Grazie!

Now get the f* out of here, you peasant!

- by u/AriKuschnir

Hello, I had an idea for a cool website called FootballMatchGuessr.
It would be like GeoGuessr, but instead of guessing random places around the world, you would try to guess — from a random picture of a match — the score, the year, and the goal scorer.
Based on your results, there would be a point system, and the game would be played over 5 rounds.

Two execution options:

1. Subagent-Driven (recommended) — I dispatch a fresh subagent per task, review between tasks, fast, parallel iteration

2. Inline Execution — Execute tasks sequentially in this session with checkpoints

Editing demo videos was killing our team, so we built an AI inside the studio.

Type "add captions, zoom on every click, trim the silence" and it does it.

It reads your project state and applies the edits live.

Short clip of it in action below. The full edit took under a minute.

Curious what edits you would love to do with one prompt.

https://reddit.com/link/1sv636y/video/2ubmh73bnaxg1/player

i've been building lumia (a desktop overlay that externalizes your context across claude, chatgpt, etc) for 4 months.

i had a post go slightly viral on here the other day. my analytics spiked — over 130 sessions, and people are actually staying on the page for almost 2 minutes.

but my conversion rate is absolute trash. literally ONE person signed up.

the waitlist is completely free, so i know i'm messing something up badly.

i really like my branding and my hero copy ("Because you're supposed to DREAM it. Not prompt it.") because it sets the right vibe, but maybe it's too vague?

or maybe having a $99 lifetime "founder pack" right next to a free waitlist button is confusing people?

please tear it apart. i need to know why 129 people read the page and decided to bounce. don't hold back.

getlumia.ca

"Bonjour à tous ! Je m'appelle Maurice. J'ai conçu une application web légère pour aider les familles à s'organiser : liste de tâches, vue Google Calendar synchronisée et post-its numériques. L'application est désormais disponible en français !
J'aimerais beaucoup avoir vos retours sur l'interface et l'utilisation.
Testez-le ici : https://mauricestechhulp.nl/planner.html"

Just launched RepRise after months of building. It tracks workouts, recovery, intensity and body composition with AI insights.

Would love to hear what you think, what's missing, what's confusing, what you'd actually use daily.

App Store: https://apps.apple.com/tr/app/ai-workout-tracker-reprise/id6761066392#productRatings

If you try it, even a quick rating helps a solo dev more than you know 🙏

Asked ChatGPT to generate picture of LAN Party or the future. Seems like everyone's on character editor screens 😅

I am mainly looking for image generation that looks almost or outright indistinguishable from real life (mainly into amateur photography, not professional looking pictures)

I don't know is the technology allows it yet, but if it's possible to have high consistency (like, create 2 pictures of different characters or poses in the exact same room), it would be lovely too

Edit: 32GB ram, 12GB Vram

been burned too many times by scanners crying wolf on i18n keys and minified tokens.

spent a while on the actual math of what makes a string

a secret vs. noise. turned out three independent signals

need to agree:

- Shannon entropy (character distribution uniformity)

- Index of Coincidence real secrets drop below IC ≈ 0.038,

the uniform distribution floor for a 26-char alphabet.

human text sits at ~0.065. the gap is unambiguous.

- Normalized Compression Distance measures how structurally

alien a string is relative to its surrounding code. an API

key inside a React component shares almost no structural DNA

with JSX. an i18n key does.

all three must vote before anything gets flagged.

built this into zone38 (named after that 0.038 threshold).

100% offline. zero dependencies. works in CI.

v0.0.1. very early. would love honest feedback especially

if you've dealt with noisy scanner hell before.

npx zone38 .

zone38

I remember the days when chatgpt couldn't do texts right!

I am exploring Claude Code integration with Slack / GitHub and wondering if features like MCP, skills, subagents are available.
Does anyone have any experience with those?

I’d say this latest update has been a major game changer in terms of accurate image generation given the prompts. Can’t imagine how it will be a few years from now.

Roughly in 2019 I bought Zemismart curtain motor with WiFi dongle (USB-A). Since then I have new WiFi password and cannot connect it anymore. I think Tuya app doesn’t support this WiFi dongle thing anymore through which I had it connected before. (I prefer local only solution tho)

Question: how could I still salvage the curtain motor and get it to connect with my home assistant setup (I have thread and zigbee networks)? Is there some cheap zigbee dongle that would make this work?

It might be my own account that's been flagged, but opus 4.6 works fine.

Makes some usage cases impossible with an auto shutdown of chat.

Slander on the street says that anthropic made a deal with Altman to usher userbase over to him with the new 5.5 release in exchange for some compute.

Godspeed anthropic, I'll resubscribe with you at opus 5....maybe.

https://preview.redd.it/00cb9alnvaxg1.png?width=216&format=png&auto=webp&s=8c4e70f4c52b5e55a44628025472f0252a2befee

https://preview.redd.it/95ug53qgvaxg1.png?width=1024&format=png&auto=webp&s=11ceaca3f3cb054aab0c97216acf9d659f509890

https://preview.redd.it/xviiqiv4waxg1.png?width=1370&format=png&auto=webp&s=751ed0508af1ceda59640622b45540e5d3dd4eb3

Been trying to use the Face Detailer in the comfyui impact pack to generate an image with detailed eyes using masking, however the results have been mixed. I used a segm eye detailer from civitai for the bbox detector. Often only one the left eye is masked while the right one is left undetected. The other output usually results in no mask being found in either eye. As the character I am trying to generate has two distinct eye color patterns, is there a certain workflow/method that offers better results for my specific problem? I have tried to use the mediapipe face mesh from the inspire pack that has parameters for left and right eyes masking but it does not seem to work. Any suggestings for more specific masking?

Life's worth living again. Nah jk but honestly im so happy 😭

What the app does:

It's an app blocker that makes you earn your screen time by completing good habits such as pushup, squats, meditation, brain games

If you want, you can try it out for free -> Brainlock

Any feedback is welcome, happy to answer questions!

ok i am convinced that having only claude for all the work is not enough. I was using GPT and moved to claude for my online brand related work but started hitting limits on my PRO many times. I did tried clearing up the bloat in context and memory md files and switching models as per requirement. But for my work i mostly used Sonnet and for heavy lifting used opus - If i use Opus i know the session is going to hit the limit.

Recently i just signed to Gemini and i think now it makes sense. for my important work i use claude and for other chat style related work i work on gemini. I use the same md files for Gemini so it knows where we are and picks up from there and Claude keeps the md files updated as per request end of the day.

Just wanted to share this with someone who is at the same stage, Hope this makes sense.

"Create as realistic an interpretation as you're able to of the gimbal UFO/UAP based on it's appearance in the video footage, the fact it rotated on its axis, the assumption it is powered by a gravity engine, is unaffected by environment, and acts as a mothetship for a fleet of smaller UFOs/UAPs/drones."

"keep it's general shape/design, but inform it based on other UFO/UAP footage/images/descriptions from David grusch/other high level military sources"

been sending cold emails for about 18 months now and the difference between my early stuff and what works now is night and day honestly. heres what actually moves the needle for me:

first line has to be about them, not you. i pull something specific from their linkedin or company news. not just "saw you work at X" but "noticed you guys just expanded to austin" or "saw your post about Y challenge". takes more time but reply rates went from like 2% to somewhere around 8-10%.

second, i stopped pitching in the first email. instead i ask a question that positions what i do. like if they're hiring SDRs, i'll ask "curious how you're planning to build their prospect lists?" then wait for them to engage before mentioning what we do.

third, keep it under 50 words. seriously. i track this and anything over 75 words tanks performance. mobile readers just skip long blocks.

the cold email formula that works for me: personalized observation + relevant question + soft CTA like "worth a quick chat?". no case studies, no feature lists, no "i help companies like yours achieve X".

biggest thing though is having good contact data to personalize with. i use Lea͏dIQ for some stuff and been trying out Pro͏speo for email verification and mobile numbers. having accurate data makes the personalization part way easier because you're not wasting time on dead leads.

cold email writing is more about what you don't say than what you do. cut everything that sounds like marketing copy and just have a conversation.

I tried to build a casual math game that is fun even if you're not good at math, would love to know what people think?

Hi everyone,

I’m 17 and I’ve been experimenting with some automation scripts. I recently built a tool that can pull the full backend catalog of almost any Shopify store in about 2 minutes.

What the script currently extracts:

• Complete product list with current and compare-at prices.
• Hidden backend tags (great for seeing a competitor's SEO/grouping strategy).
• SKU variations and inventory structure.
• All data is exported into a clean Google Sheet/CSV.

Right now, it’s just a raw script that I run manually. I’ve seen some interest from small dropshippers who need this for competitor benchmarking, but I’m wondering if this has "Micro SaaS" potential.

A few questions for the founders here:

1. Is there a big enough pain point for Shopify store owners to pay for a dedicated dashboard for this?
2. How can I turn this raw data into a "must-have" tool? (e.g., tracking price changes over time or getting alerts for new product drops?)
3. What would be the best way to monetize this beyond one-off reports?

I’d love some feedback on whether I should keep building this out or if this is too niche. If anyone wants to see the data format I’m getting, I can share a sample link.

Thanks!

Hi all, I have a server (dual 7900xt) running qwen3.6 27b in LMStudio, because I love LMlink for its ease of use and I am okay with the model chugging along at ~25t/s in the background.

I then serve the mode to my Mac, via LMlink. On my Mac I am kind of lost though. I used opencode for a while but it’s kinda clunky, but I love a codex like gui… are there other gui’s that talk to local models? I found pi-gui, but I can’t configure it with a local model (haven’t found the right json to hack the locks endpoint into yet). What are your fave guis?

Just recently redid my workstation rig in a Phanteks enthoo pro 2 server edition case with 2x 3090 TI FE and 2 3090s. Thanks to u/faileon for the inspiration and reference build. I am going to install more fans but its almost 5AM for me and im a little buzzed ngl but I just wanted to share my progress because I just finished it and made sure it posts and im really excited about it because I worked my ass off and saved a shit ton of money to pull this off. Very proud of my monster. :)

Goodnight everybody!

Oh and the temps are actually pretty good, the way I have the cards mounted seems to work well for airflow.

Hello. i recently had alot of issues with the desktop app. Everytime i restart the program or there is an update and i press update after a few seconds i get an error saying that another program is using claude. Sometimes it helps when i restart the whole pc,
My project or sessions in cowork tab and claude code tab isnt showing up. i can still see the summury of how many sessions in claude code feks and how many tokens and stuff. but not the actuall sessions. that goes for both cowork and claude code.

I also dont see my subscription plan down to the left beside my profile name, but i can see it when i go into settings, and i also see it in the webb app.

I have tried reinstall the whole thing, doesnt help,

Anyone else had issues like this?

Can anyone recommend a solution - either COTS or low-code / minimal soldering / some 3D printing, that can:

- Take power and data from a PoE cable.

- Discreet mounting solution for ceiling or in-room

- Act as a bluetooth proxy to stream music to a bluetooth speaker at decent quality (e.g. from music assistant - e.g. run squeezelite)

- Human presence sensor

- Temperature sensor

- Humidity sensor

I realise it's a big ask, and variants of this question come up a lot but innovation in this area is constant. Thanks in advance!

If ChatGPT just gave me a 6-bullet answer and I want to follow up on three bullets together, my choices were:

• Send three separate messages (loses the shared context)

So I built a tiny Chrome extension. It adds a small green 📎 Quote button next to any text you highlight on chatgpt.com. Click it — the selection appends to the composer as a markdown blockquote and the cursor lands on a fresh blank line. Type your comment. Select another passage. Click Quote again. It stacks below. Keep going. Hit Send when ready — the whole thing goes as one message, and ChatGPT addresses all of them together.

Install (one click): https://chromewebstore.google.com/detail/gfimipjodfpoeocpboomepjgmocigfjb

Source: https://github.com/pranay0064/chatgpt-ask-multi

with the release of deepseek v4, common users have more cheap choices to use llm. more high performance models,more hardware support, more de-cuda ecosystem. Agents based on deepseek can be used by more users globally.

Most AI wants to chat. fixRAgent wants to work. We built the first 'Anti-Chat' AI designed for the real world—a universal operating manual for everything you own, from a 1970s electrical panel to your brand-new EGO weed wacker.

Don't spend hours in a YouTube rabbit hole or digging through a lost owner's manual only to realize you bought the wrong part. Just snap a photo. In under 30 seconds, fixRAgent gives you:

Visual Parts Identification: Snap a pic of your lawnmower, leaf blower, or appliance. It pulls the exact model, the proprietary part numbers you need, and direct links to buy them.

The Safety-First Triage: It identifies 'High Risk' hazards (like arcing outlets or gas lines) and mandates a 'Hard Stop' safety protocol before you ever touch a tool.

The Bottom Line: A real-time calculation of exactly how much money you just saved by not calling a pro.

Why it’s ahead of the game:

The 'Anti-Chat' UI: No fluff or small talk. It generates structured, industrial-grade Standard Operating Procedures (SOPs).

Property Portfolio: It’s a digital twin for your home or rental. It tracks maintenance, parts, and value across multiple properties.

B2B Remote Triage: Landlords can now send a link to tenants to triage a leak or a 'no heat' call instantly, stopping the $150 'blind' contractor dispatch.

Support the Launch:

My sister Jenna is running our main influencer push on Facebook right now https://www.facebook.com/share/p/1aagasi3f7/ If you’re coming from the FB community, let me know!

For the Reddit crew, I’m looking for "stress tests." Go to the site, snap a pic of the most obscure piece of equipment in your garage, and see if our logic holds up Check it out here: [fixRAgent](https://www.fixragent.com)

No more YouTube rabbit holes. No more "I don't know what this part is called." Just scan the problem and own the fix.

This is awful, just awful. For the third time this week, I have found 4.7 (1M Max) completely unable to do even basic tasks and creating workplans that contain seriously wrong assumptions and bad solutions. It's like it can't see half the repo.

My question is - how does 4.7 get fixed, or should they just drop it?

I had 4.6 re-run the task (undertake a gap analysis and create workplan and it nailed it. This was the 4.6 assessment of 4.7's earlier attempt (REDACTED):

1. "No X Django model" (Blocker #1) — Wrong. Xexists and is comprehensive. What the new X app needs is a XFK on its submission model (like every other service already has), not building a new model from scratch.
2. "X not found" (gap #3) — Missed Xwhich already provides per-X, per-role, per-service-type officer scoping.
3. Phase 1A of the workplan (~2-5 days for X) — Unnecessary as described. At most you need X-specific config fields on Xor X, which is a trivial migration.
4. Phase 1E of the workplan (X) — Already exists as X. Just needs Xadded to the service type choices (if not already).
5. The inflated timeline (18-22 days vs spec's 9.5) — The padding is largely justified by Phase 0/1 prerequisites that already exist. With Xand Xin place, the realistic delta over the spec's estimate is much smaller.
6. Cross-service design question #2 ("Where does Xbelong?") — Moot. It's already in X/X.py as X, with exactly the "platform model with thoughtful initial coverage" the author recommends building.
7. Gap #4 about X— True that Xhas its own X, but the analysis fails to mention that X also already has its own Xmodel at X/X/X.py. This is relevant context it should have surfaced.

how long should a convo in Claude be? How many compacts is too much and how much is lost per compact. what do you guys think is the best time or indicator to stop chat and move on to a new one? just curious

He instalado Alarmo usando HACS y funciona bien, pero me he encontrado con una situación que no sé si es normal en este caso. Tengo poca experiencia en instalar integraciones desde HaCS, y puede que sea normal, pero tengo mis dudas.

Como he comentado, la integración funciona bien, pero cuando entro en la consola de HA y voy a integraciones, me aparece la integración de HACS, y cuando entro en ella me aparece Alarmo, pero en la sección de configuración me dice que la actualización está no disponible. Como si no pudiera comprobar actualizaciones. Adjunto pantallazo.

Alarmo también me aparece como integración fuera de HACS, por lo que no sé si puede llegar a ser normal.

Actualmente tengo la versión 1.16 de Alarmo. He empezado a utilizar este sistema de alarma y me ha costado un poco configurarlo pero estoy contento, y no me gustaría tener que volver a empezar si esto no es normal.

Pongo los pantallazos a continuación para que lo entendáis mejor. Gracias

It does this on every model and it's been doing this for multiple days it's so weird. See if you guys get this too

are there any species of any cellular or non cellular organism that can replicate outside a host body that do not perform cellular respiration or that could live completely without oxygen?

Codex in a well-defined context, truly absurd.

So happy! It is also the first time I linked Claude code to my github, and also the first time I used Claude code to ship a product from scratch! All within five hours! Super thankful! 🙏🏻🩷✨☺️

As the title suggests, I built something I'm proud of: https://oil-price-tracker-free.tryfriday.app

What it does:

- Tracks WTI & Brent crude oil prices in real-time

- Shows major oil company stocks (Exxon, Chevron, BP, Shell, etc.)

- Global gasoline prices from 9 countries

- Historical charts going back 6 months (including the Feb 2026 Iran war spike)

- Auto-updates every 3 hours by scraping Yahoo Finance, OilPrice.com, and other sources

I built this in one afternoon without touching code using Friday AI and basically had a conversation:

- "Build me an oil price tracker with real data"

- "Make it look like the Wall Street Journal"

- "Add historical data showing the Iran war impact"

- "Make it mobile-friendly"

The AI handled everything:

- Setting up the database (Supabase)

- Scraping live data from financial sites

- Building the entire Next.js app

- Designing the UI to match WSJ's style

- Deploying to production

Total time: ~4 hours of prompting. Zero manual coding.

The data is 100% real and updates automatically. I set up a scheduled job that scrapes fresh prices every 3 hours.

Would love feedback! Does this feel useful? What other data would you want to see?

Shipped my first ever webapp w Claude code yesterday, as a non-techie! So happy and thankful

I spent three weeks manually stripping 14,000 lines of AI generated bloat from my legacy system to refine Cynic & Spore Labs. It’s an anti-ERP for high-end gourmet mushroom growers. I have 5 alpha slots open for a 14-day Pro trial (no card required).

I don't want "good job" feedback. I want you to try and break the creation system, poke holes in the analytics, or leak the RLS. If you think you can bring it down the floor is yours.

www.cynicandspore.com

Prompt: generate an image of a screenshot taken in windows 98 in the browser of internet explorer that was displaying the old Reddit

credit first: the brain of this is huggingface/ml-intern. procedural knowledge is theirs.

problem for me: upstream is its own ~50k-line agent loop calling the Claude API. if you have Claude Max you're paying twice, and i already live in Claude Code where the loop and MCP plumbing exist. so i pulled the workflow out and wired it into Claude Code primitives.

ultra-ml-intern:

/plugin marketplace add infiniV/ultra-ml-intern /plugin install ml-intern@ultra-ml-intern 

say "fine-tune Qwen3-0.5B for math reasoning" and it finds the landmark paper, crawls citations, reads methodology, audits the dataset, writes a TRL script (reads current library source first so it doesn't hallucinate imports), preflights, smoke tests, then hf jobs run with Trackio.

the 8 expensive mistakes from upstream's system prompt are encoded as rules. the one that's bitten me most: default 30m HF Jobs timeout silently killing long runs. now enforces 2h min.

want the standalone python tool, use upstream. live in Claude Code, use this.

MIT, 1 star (me): https://github.com/infiniV/ultra-ml-intern

im just curious, mine was like... a twitter bot in 2016 that posted random quotes from a book i liked. it got like 200 followers somehow which felt insane at the time but i never did anything with it. felt more like a proof of concept than a real project.

what about you, did your first one turn into anything or just kinda fade out?

Hello, I‘ve been trying to set up claude code and connected github for it - it asks me to connect a repo but the button is greyed out. What am I missing? Thanks!!

You can get it from the in-game store. All I ask for is your honest and constructive feedback. Thank you to everyone.

App store link is: https://apps.apple.com/us/app/id6761820736

Before reading the real content, can any one tell me what's wrong with LocalLLaMA for banning my post to r/LocalLLaMA ? I cant agree that is not related to local LLM.

https://preview.redd.it/eteotpoxpaxg1.png?width=1466&format=png&auto=webp&s=a7a1032db7d6596f55bb22371dde4a8b7a41330e

TL;DR: After my deep‑dive on Qwen 3.5 tool‑calling and trail on Qwen 3.6-35B-A3B, I took the same enhanced.jinja setup and ran Qwen 3.6‑27B‑FP8 through an unsupervised, agentic build. The catch? Upgrading to NVIDIA Studio Driver 595.79 introduced NCCL deadlocks that required extra config overrides to fix. Once resolved, the model ran for 180 000 tokens without a single malformed tool call, and the finished project is here.

Important: The qwen3.5-enhanced.jinja template requires preserve_thinking=false as it is new feature in Qwen 3.6. If you accidentally set it to true, the qwen3.5-enhanced.jinja will break and tool calls will fail. All examples below assume that flag is correctly set.

1. What Came Before (Recap of the Qwen 3.5 Post)

Last time I spent weeks debugging Qwen 3.5‑27B and 35B‑A3B on a mixed‑GPU rig (RTX 4090 + RTX 3090). The fixes that made agentic work possible:

• qwen3.5‑enhanced.jinja – a custom interleaved‑thinking template that treats any unclosed block as plain content, not as reasoning content. This way the harness sees the tool call directly, even when the model forgets to close the thinking tag – a pattern known as “CoT leakage.” The template must have preserve_thinking=false (the default) or it will not function.
• Streaming‑parser dependency – the jinja fix relies on the parser processing tokens as they stream, detecting even when the surrounding tag is still open. On Qwen 3.5‑27B, the qwen3_xml parser works perfectly for this and is generally more robust. However, on Qwen 3.6, only the qwen3_coder parser triggers correctly with the unclosed thinking block; qwen3_xml fails to fire the tool call (more on this below).
• VLLM_TEST_FORCE_FP8_MARLIN=1 – forces the 4090 (SM89) to use W8A16 instead of native W8A8, preventing precision drift between the two GPUs.
• NCCL tuning (P2P_DISABLE, IB_DISABLE, Ring) – essential for stability on PCIe topologies.

With that stack, Qwen 3.5‑27B ran a 1h 9m continuous agentic session at 138K tokens, building a complete FastAPI + React app without any tool‑calling failures.

2. Qwen 3.6‑27B – The Upgrade Path

A few weeks later I swapped the model to Qwen/Qwen3.6-27B‑FP8 while keeping the same enhanced.jinja template (with preserve_thinking=false). The parser had to change: despite qwen3_xml being the more robust choice on 3.5, on 3.6 it did not trigger tool calls when remained unclosed (the exact scenario the template relies on). So I switched to qwen3_coder – a parser that, while less sophisticated with special characters, processes streams aggressively to catch the tool call inside an unclosed thinking block. (After bug fix introduced in this post. I may switch back to qwen3_xml for vLLM 0.20.1 for above.) Everything worked fine on driver 591.86 — so I upgraded to Studio Driver 595.79, expecting better performance. Instead, everything broke:

• Random NCCL deadlocks – the server would freeze hard mid‑generation, requiring a restart.
• These deadlocks looked exactly like tool‑calling failures, but the logs pointed to NCCL timeouts, not parser errors.

3. Why qwen3_coder Over qwen3_xml: The "Bug + Bug = Feature" Effect

https://preview.redd.it/cexnoya6oaxg1.png?width=2132&format=png&auto=webp&s=b564ee47a0152fc3aa46f001abd30992c3744fee

The switch to qwen3_coder isn't just a workaround – it's a perfect case of two "bugs" combining into a feature.

• The model's bug (CoT leakage): Qwen 3.6 sometimes fails to close its tag before outputting a . The enhanced.jinja template deliberately ignores this unclosed block and leaves the tool call as plain content, preserving the intent.
• The parser's "bug" (aggressive streaming): qwen3_coder is designed to process code‑related outputs and is much more aggressive in detecting tool‑call patterns mid‑stream, even when the surrounding XML is malformed. It doesn't require a fully‑closed context; it just sees and fires. In contrast, qwen3_xml is a proper XML parser that expects a well‑formed document, so an unclosed tag scuppers its ability to find the nested .

When the model's "leakage" meets the parser's "roughness", you get more resilient tool‑call extraction – the exact outcome you want. Neither the model bug nor the parser's intolerance to XML imperfections is ideal on its own, but together they become a production‑grade feature. This is why I stick with qwen3_coder for Qwen 3.6 and why qwen3_xml – despite being more robust with special characters – simply cannot handle the unclosed‑thinking scenario on this model.

Dear vLLM dev, please let me know if my verdict is correct.

4. The Real Culprit: Driver 595.79 Broke Things

Here's the twist: I was on 591.86 and things were mostly working. I upgraded to Studio Driver 595.79 expecting improvements — instead, it introduced NCCL deadlocks that froze the server mid‑generation.

The new driver appears to tighten NCCL behaviour on mixed‑GPU PCIe topologies, breaking vLLM's custom all‑reduce path. The fix wasn't rolling back the driver — it was enforcing the right overrides:

1. New NCCL env vars:
2. --disable-custom-all-reduce – forces vLLM to use native NCCL all‑reduce instead of its custom implementation, which is on PCIe‑only topologies.

Without these overrides on 595.79, you'll get random deadlocks that masquerade as tool‑calling failures.

5. The 180K‑Token Agentic Run

With the driver + NCCL fixes in place, I gave Qwen 3.6‑27B full ownership of a folder and a $10 000 token budget. No hand‑holding.

Result: The model chose to build a modern web app (React + Vite + TypeScript, with a FastAPI backend), iterated on it after critical feedback, and delivered a polished upgrade – all without a single malformed tool call. The finished code is on GitHub.

6. The Recipe (Copy‑Paste Ready)

#!/bin/bash # ------------------------------------------------- # Qwen 3.6‑27B‑FP8 – Agentic‑Ready vLLM Launch Script # Tested: 180K tokens, zero tool‑calling failures # Driver: NVIDIA Studio 595.79 # ------------------------------------------------- # ---- Safe, Speed‑Focused Env Vars ---- export CUDA_DEVICE_ORDER=PCI_BUS_ID export CUDA_VISIBLE_DEVICES=0,1 export NCCL_CUMEM_ENABLE=0 export VLLM_ENABLE_CUDAGRAPH_GC=1 export VLLM_USE_FLASHINFER_SAMPLER=1 export OMP_NUM_THREADS=8 # ---- NCCL Tuning for SYS/PCIe Topology ---- export NCCL_P2P_DISABLE=1 export NCCL_IB_DISABLE=1 export NCCL_SHM_DISABLE=0 # NEW for driver 595.79 export NCCL_ALGO=Ring export NCCL_P2P_LEVEL=LOC # NEW for driver 595.79 # ---- vLLM Stability (Driver‑Dependent) ---- export VLLM_RPC_TIMEOUT=180 # NEW export VLLM_WORKER_MULTIPROC_METHOD=spawn # NEW # ---- FP8 & Memory ---- export VLLM_MEMORY_PROFILER_ESTIMATE_CUDAGRAPHS=1 export VLLM_TEST_FORCE_FP8_MARLIN=1 export VLLM_SLEEP_WHEN_IDLE=1 # Clean stale FlashInfer cache rm -rf ~/.cache/flashinfer # Activate environment source /home/cychan/vLLM/.venv/bin/activate vllm serve Qwen/Qwen3.6-27B-FP8 \ --served-model-name Qwen3.5-27B \ --chat-template qwen3.5-enhanced.jinja \ --default-chat-template-kwargs '{"preserve_thinking": false}' \ # MANDATORY: the enhanced jinja will break if this is true --attention-backend FLASHINFER \ --trust-remote-code \ --tensor-parallel-size 2 \ --max-model-len 219520 \ --gpu-memory-utilization 0.91 \ --enable-auto-tool-choice \ --enable-chunked-prefill \ --enable-prefix-caching \ --max-num-batched-tokens 12288 \ --max-num-seqs 4 \ --kv-cache-dtype fp8 \ --tool-call-parser qwen3_coder \ # REQUIRED for Qwen 3.6 with enhanced.jinja; for Qwen 3.5 27B, qwen3_xml also works (see https://www.reddit.com/r/Vllm/comments/1suasv2/) --reasoning-parser qwen3 \ --no-use-tqdm-on-load \ --host 0.0.0.0 \ --port 8000 \ --language-model-only \ --disable-custom-all-reduce # CRITICAL for driver 595.79 

7. Key Takeaways

1. Parser choice depends on the model – The enhanced jinja template relies on a streaming parser to catch tool calls inside unclosed blocks. On Qwen 3.5‑27B, the qwen3_xml parser works fine and is generally more robust (see this detailed post). On Qwen 3.6, qwen3_xml fails to trigger the tool call in that exact scenario, so I use qwen3_coder instead.
2. preserve_thinking must be false – The enhanced jinja template will not work with preserve_thinking=true. This is a new feature in Qwen 3.6 where qwen3.5-enhanced.jinja is not compatible.
3. The NVIDIA driver upgrade can break things – going from 591.86 to 595.79 introduced NCCL deadlocks on my mixed‑GPU setup. The fix requires new NCCL env vars and --disable-custom-all-reduce. If you're on 595.79 without these overrides, you'll hit random deadlocks that masquerade as tool‑calling failures.
4. The original Qwen 3.5 fixes still stand – VLLM_TEST_FORCE_FP8_MARLIN=1 remains non‑optional on mixed‑GPU setups to avoid precision drift, and the same NCCL tuning (updated for the new driver) is mandatory.
5. Qwen 3.6‑27B is not just an incremental step – it's a dense 27B model that beats the old MoE flagship Qwen 3.5‑397B‑A17B on core agentic‑coding benchmarks (SWE‑bench Verified 77.2 vs 76.2, Pro 53.5 vs 50.9, SkillsBench 48.2 vs 30.0), making it a generational upgrade rather than a refinement.
6. 180K tokens is the new normal – the system handled a 10‑minute uninterrupted agentic session with zero tool‑calling errors, demonstrating production‑grade stability on consumer hardware.

Bottom line: The enhanced.jinja template works on both Qwen 3.5 and 3.6, provided preserve_thinking=false and you choose the right parser for the model. Combined with the new driver workarounds, the stack yields a rock‑solid 180K‑token agentic run. Full recipe in Original Qwen 3.5 deep‑dive – go build.

Links:

• Original Qwen 3.5 deep‑dive
• Parser behaviour across Qwen 3.5/3.6
• Qwen 3.6‑27B project repo
• vLLM config repo

Last week I set up an autonomous AI agent and gave it one job: find a consumer mobile app idea with real demand and weak competition. No guardrails, just browse the internet and come back with a winner.

It ran through the night. Browsed App Store charts, Product Hunt, Hacker News, iTunes search APIs. Built a longlist of 12 ideas, scored them, deep dived the top 3.

The winner it came back with: a receipt and warranty tracker for people who work for themselves.

My first reaction was "that's boring." Then I looked at the data. Warranty tracker apps on the App Store have 1-3 ratings. The category exists but nobody has built a real product for it. Solo tradespeople in the UK lose an average of £375/year to lost receipts and missing tax deductions. Making Tax Digital kicks in for sole traders in April 2026.

So I built a preorder page. Spent a day on branding, copy, and a landing page. Wired up payments. It's live.

docketapp.us

Happy to answer questions about the AI agent setup, the research process, or the validation approach. Still figuring out if this is a real business or a weekend experiment.

hey everyone, planning to create my first saas. please suggest any ideas. if anyone has experience building one, would love your tips!

So i want to extract the data from the pdf and convert it into structured output so which model has better bench marking and is free to use ?

Recently finished an AI commercial where I needed to upscale a bunch of videos with RTX Video Super Resolution.

Tried several iterator nodes - but was running into issues, especially with Meta Batch Manager in the workflow, the iterators became very finicky.
Didn't want to go down the path of combination lists, so eventually ai coded a batch process GUI, and found it super helpful for other workflows (depth map extraction, etc)

So, sharing the repo here if people need a quick solution to this annoying comfyui video batch issue.

How to run:

1. Have your comfyUI running.
2. Run the script in your terminal: python comfyUI\_batch\_gui.py
3. In the GUI, select your workflow JSON file and input directory
4. Configure patches to modify the workflow: Use NODE ID and FIELD NAME
   1. Patch the input nodes and video/ image field with the video_path to iterate through the input folder.
   2. Patch the output node's file prefix with different permutations:
      1. OutputDir/ PrefixStem (preferred for videos), where stem is filename in path/filename.mp4 input file.
      2. Output/ Stem/ PrefixStem (preferred for image sequences)
   3. You can add more patch fields if needed.
5. Click "Start Batch Processing" to begin

Github repo with sample workflow included: https://github.com/Kalydoscope/ComfyUI_batch_gui

Here's a link to the commercial, if anyone's interested:
https://www.youtube.com/watch?v=7CB_DJORt_8

I saw this reddit post about a MacOS application that a guy made. It basically tracks time you spend on various applications throughout the day and displays it as money lost or gained based on your hourly income.

There was a big issue tho, it didn't track what the user was doing inside apps especially chrome. So I built an extension in 10-15 minutes via Claude and published it.

It shows you much time are you wasting in terms of how much money have you lost based on your hourly income.

Check it out here - https://chromewebstore.google.com/detail/spent/ihofmlngloaeenmkeblodmaiilenbijp

Reddit post - https://www.reddit.com/r/MacOS/comments/1sovzc5/i_made_a_little_menubar_app_that_turns_screen/

P.S : I am working with the app owner to make it so that the extension can share its data with the app.

https://preview.redd.it/12mhwendpaxg1.png?width=1940&format=png&auto=webp&s=e61b0b557d642429534b1df80fdf959659f779a1

Just learnt that Nvidia has some models that you can try. But I haven't read through their unfriendly docs yet on how to go about it.

Renting hardware to run open weight models just occurred to me.

But I believe people here have been doing that.

Any recommendations on which service provider/models to go with in terms of efficiency over cost for coding/development?

Going to checkout Nvidia's service cause I'm sure those main stream AI companies are using them too. Maybe cutting the middle man saves some costs at some inconvenience of setup and maintenance?

Greetings

So I'm trying to use ADB to send text to my Sony Bravia Android TV, which can come in handy in certain situations. For this I have two buttons on my HA remote:

A button "input text" where I type my query

A button "send text" which sends my query

On my TV however, nothing shows up when I try it.

I can get it work through developer tools or when I establish an ADB-connection from my laptop to my TV.

I believe the issue is caused the way I configured my button which has to send the text to my TV, but I cannot seem to find what the issue is

The button which has to send the text is programmed as follows in scripts.yaml:
(Don't mind the indentation. It is correct in my HA)

input_text: chromecast_keyboard: name: Chromecast Keyboard max: 50 send_text_to_chomecast: alias: send text to chromecast sequence: - service: androidtv.adb_command target: entity_id: media_player.android_tv_192_168_120_2_2 data: command: input text '{{ states('input_text.chromecast_keyboard') }}' In Configuration.yaml I have: input_text: chromecast_keyboard: name: Chromecast Keyboard max: 50 and both buttons on my HA remote control are configured as follows: - type: entity entity: input_text.chromecast_keyboard name: Text - type: button name: Send Text icon: mdi:send tap_action: action: call-service service: script.send_text_to_chromecast data: {} target: entity_id: script.send_text_to_chromecast Could it be issue is caused by the input text command? Anyone who sees where I've made an error? I don't get any errors on screen, nor in de the logs. HA says it sent my command succesfully, but that doesn't seem to do anything Thanks! 

It might come as a hallucination, but I don't think in this case is a hallucination whatsoever. When I asked whether my hypothetical football scenario might be solid. It just sends straight hates rather than actually looking at the data and the plausibility with its search feature and be as neutral as possible. Even when it did search, there were no apologies whatsoever, it kept saying things that basically means "You're stupid, I'm wrong but I won't apologize".

I'm looking to explore this ai agent fields and planning to start building some ai agents and automations - as much as i know n8n is a platform people have been using to automate taskk but nowadays claude code and open claw kind of platforms exists too
Just need some guidance how to start and if using AI for build the agents is a new big things - so that i can start learning with new tech

I opened a terminal in my project directory, then installed the claude supertpower plugin, I have my claude-mem installed before. After that I change the model to opus 4.7 (high effort). First prompt it took 38% of my limit. Then I change model to 4.6 with high effort, second prompt and boom, 100% limit. Then I check back on claude-mem page (http://localhost:37777/) and notice that the page could not be loaded. I'm 5x user, before today, anything still works fine.

I don't know what's the root cause, my prompts are as usual just like the other daily tasks. But from my point of view, this could be an issue from claude code after we installed some plugins. So next time maybe we should restart terminal, re-run claude before continue prompting anything, or even restart the system and start new claude session.

In the meantime, I switched back to codex and using gpt 5.5, so far so good. But I hope next time, this issue from claude code does not happen again so I do not have to switch to codex. I really love both codex and claude code but I beleive most of people do not like this `LIMIT` issue from claude code, and I know many people still working on both tools to solve the limitation problem.

used to think ai would make debugging easier

but honestly, it just exposed how messy our process already was

before:
we manually traced bugs

now:
we paste errors and hope ai figures it out

problem is.. ai only sees what you show it

if you give:
“TypeError at line 45” → you get a shallow fix

if you give:

• full stack trace
• involved files
• what changed recently

→ suddenly the output is way better

the big shift for me was:
stop treating ai like google
start treating it like a teammate who needs context

also noticed tools that keep context across files/workflows are way more useful than pure chat

feels like we’re moving from:
“prompt and fix”
to
“understand → trace → fix”

still early, but direction is interesting

Source - Anthropic Engineering post mortem

I'm trying to get regional prompting work and I'm so frustrated. I've been using Forge Neo, through the Stability Matrix download manager gadget, and I've been trying to get "Forge Coupler", the Forge Attention Coupler thing to work.

It's this one: https://github.com/Haoming02/sd-forge-couple#mask-mode

I installed it by clicking on the extensions installer thing in the WebUI. No matter what I do, it seems to ignore my masks and regions, and just build whatever the hell it wants. Somebody please help? I don't know what the hell I'm doing wrong with this!

As far as i know the weight is of 160gb + 9.6gb needed for max 1 million token window + 5 gigs overhead = 175gb vram.

But vllm and othere sources said "To use the full 1M context, you need 4x A100 80G" --> thats a 320gb vram ?? Am i missing something??

Sources:

1. https://lushbinary.com/blog/deepseek-v4-self-hosting-guide-vllm-hardware-deployment/?hl=en-GB
2. Vllm blog of deployment

9.6 gig is also sourced from vllm blog page + official model page says it take 10% kv cache of what 3.2 used to take

I am looking for a complex task that needs to be completed in multiple steps with unit tests and a comparison result made by a human. Is there a repo of such benchmark programming tasks?

"Hoi allemaal! Ik ben Maurice. Ik heb een simpele web-app gebouwd om overzicht te houden in het gezin: een takenlijst, Google Agenda en digitale 'geeltjes' op één plek. Ik heb zojuist ondersteuning voor meerdere talen toegevoegd!
Ik ben benieuwd wat jullie van de eenvoud en de koppeling vinden.
Bekijk het hier: https://mauricestechhulp.nl/planner.html"

guys share your thoughts 🤔💭

"Hallo zusammen! Ich bin Maurice. Ich habe eine schlanke Web-App entwickelt, die Familien dabei hilft, den Überblick te behalten: Aufgabenliste, Google Kalender und digitale Notizzettel in einem. Die App unterstützt jetzt auch Deutsch!
Ich würde mich sehr over euer Feedback zum Design und zur Funktionalität freuen.
Hier ausprobieren: https://mauricestechhulp.nl/planner.html"

Does anyone have any tips for me on how to adjust a person's height in z Image Turbo? No matter what I try—specifying the height in centimeters, using words like “tall” or “short”—the person is more or less always the same height.

"Hi everyone! I’m Maurice. I’ve been working on a lightweight, minimalist web app to help families (and individuals) stay organized. It features a task list with location suggestions, a synced Google Calendar view, and simple sticky notes. I just added multi-language support!
I’d love to hear your thoughts on the UI and the Google integration.
Check it out here: https://mauricestechhulp.nl/planner.html"

main dashboard for wide screen

mobile resume demo

I built ADHDev, short for Agent Dashboard Hub for Dev.

It is an open-source, self-hosted control plane for AI coding agent sessions.

AI coding agents are becoming background workers, but the control layer is still stuck at the desk — scattered across IDE tabs, terminals, remote desktops, and notifications.

I kept starting Claude Code / Codex / Cursor-style sessions, walking away, and later coming back to find that one of them was waiting for approval, stuck, finished, or asking for a follow-up.

So I built ADHDev to monitor and control those sessions from desktop or mobile.

The self-hosted version runs locally as a daemon with an embedded web dashboard. It does not require a cloud account.

The goal is not to replace coding agents. The goal is to give them a dedicated control surface.

What it does today:

- Open-source and self-hosted

- Local daemon with embedded browser dashboard

- No cloud account required for the self-hosted path

- Tracks active IDE / CLI / agent sessions

- Lets you review what happened from a browser dashboard

- Lets you continue sessions from mobile

- Helps with approval / review / follow-up workflows

- Supports long-running CLI sessions through a session host layer

Currently working / tested integrations:

- IDEs: Cursor, Google Antigravity, VS Code, Kiro

- IDE extension integrations: Codex, Claude Code

- CLI agents: Hermes Agent, Codex CLI, Claude Code CLI

Other providers and adapters exist, but I do not want to present them as fully supported yet.

I attached two short demo videos showing:

1. monitoring an AI coding session

2. reviewing and continuing the session from mobile

Links:

GitHub: https://github.com/vilmire/adhdev

Docs: https://docs.adhf.dev

Website: https://adhf.dev

I would appreciate feedback from people who use AI coding agents heavily:

- Does this problem feel real to you?

- Would mobile review/control fit your workflow?

- Is the self-hosted path important to you?

- Which integrations matter most?

- Would you prefer self-hosted only, cloud, or both?

Amusing...

https://preview.redd.it/mdnb0n44maxg1.png?width=1210&format=png&auto=webp&s=ac037ae219d890d2695db687fc2a3e9172aff314

I have been upgraded to version 5.5 and I asked her about the basic physics problem that I use to check for AI reasoning improvement. She has failed but when I have given the correct answer she has surprised me inventing new Physics. Fresh new rules. When objecting to that, she has started to answer in a loop.

Very funny. Now, with this improvement, she thinks to be smarter than a PhD in Physics (I am not a PhD, but this problem and its solution has been validated by an active PhD, expert in theoretical Physics).

I will try to calibrate adjust options so she has more humility.

As a CS+engineering student, my sleep schedule is cooked. One of the biggest struggles I face throughout my day is just having the motivation to stop hitting snooze and get out of bed.

To fix that problem, I built Unsnooze. It's an iOS app with an alarm retrigger system that won't stop retriggering an alarm until you perform some mental/physical task. Whether that involves climbing stairs, doing pushups, walking x feet, playing a memory puzzle, etc, the challenges ensure that you're out of bed and moving around, giving you the boost you need to start your day.

You're able to chain multiple challenges to an alarm. Other features include:

• Detailed statistics and a streak system
• Custom voice recordings to use as alarm sounds
• Import your own music
• A wide variety of challenges (and a testing feature as well)
• 20+ alarm ringtones that will ensure you get up

Having trouble getting up in the morning? Give this app a try!

Why this is better than Alarmy: more challenges (and all free), simpler UI/UX. cheaper subscription

Initially, I had a broad idea with multiple features:

• Blood donation tracking
• AI symptom checker
• Prescription & medical report simplifier
• Personal health records
• Mental health support
• Medicine reminders

But I realized this approach is too scattered and not practical for a startup.

Now I’m thinking of focusing on a single core problem:

Finding blood quickly during emergencies in India is still slow and unorganized.

Proposed solution:

• Real-time blood availability across nearby blood banks
• Smart donor matching with notifications
• Basic donor eligibility checks

Goal: Reduce the time and friction in critical situations where people struggle to find blood.

Does this seem like a strong enough problem-solution fit to build on?
Or would AI-based healthcare tools (like report simplification, prescription explanation) be a better direction in the current market?

Looking for honest / even brutal feedback OR you Can give me good Idea for My country

Since ComfyUI just closed the last active attempt from community contributors trying to get an official image upstreamed, is there any well known community image that's maintained and trustworthy?

I have come across a variety but they're either tailored to a paid SaaS / cloud deploy, or layer on a bunch of other unnecessary additions (custom UI / API), or the project is no longer active (some are but they've not been publishing new images for whatever reason, usually because it's not the main focus of that repo).

I like most I assume just have my own DIY build locally, but I find that a bit odd if there is no community established image in the ecosystem 😅 (I've seen a variety of attempts, many vibe coded that didn't seem to gain momentum / traction)

It'd be much better if ComfyUI would just integrate a Dockerfile build in their repo as an official reference, and ideally have CI build / publish to GHCR / DockerHub.

I used the reasoning feature, btw, even if it decided that a second was enough to answer.

You pick a stock/crypto, an amount, and a start date - it plays back the growth (or loss) as an animated chart. You can also compare two assets side by side. Built it because I kept seeing those "if you bought Bitcoin in 2015..." posts and wanted an interactive version. mainly built for educational purposes only

check it out on https://onlinetoolkit.io/what-if-i-invested

Why is AI so bad at playing hangman? Same with ChatGPT amd Claude

The model now decides how hard to think about your question. Not you. The model. So when people keep saying “4.7 gives me shallow answers on complex problems” … yeah. It decided your problem wasn’t worth the compute. And the part almost nobody mentions. Switching from 4.6 to 4.7 nukes your entire prompt cache. THİS is my personal take, LETS DİSSCUSS. (I made the photo with gemini, I dont know photoshop sry.)

Just tried something interesting — automated the process of filing multiple RTI applications using Claude Code + Playwright CLI.

What normally takes a lot of repetitive manual effort (filling forms, payments, confirmations, etc.) was handled end-to-end with automation — including UPI flow and submission tracking.

Filed RTIs across multiple central institutions in Karnataka in one go, and all of them went through successfully.

Honestly, this combo feels insanely powerful for web automation.
The future looks efficient… and a little scary at the same time 😅

There’s something satisfying about using tech to exercise a citizen’s right.

If you're curious, I’ve put the setup + workflow here:
https://github.com/gouthamganeshm/online_rti_automation/

Would love to hear thoughts or ideas on improving this further.

8 RTIs. Filed, paid, and confirmed — fully automated.

I upgraded to Claude Pro on April 7, 2026. Within minutes:

1. ALL my project data disappeared (5 projects, 50+ Branding strategies, client work)

2. $200 unauthorized charge ("Gift Max 20X")

3. Multiple unsolicited OTP messages (account compromise)

I've sent:

- Initial detailed report (April 20)

- Follow-up email (April 21)

- Twitter escalation (@anthropic)

- LinkedIn messages to support staff

- Email escalation to [support@anthropic.com](mailto:support@anthropic.com)

Result: ZERO response in 18 days until just now (Fin AI responded).

My business is blocked. I can't access months of strategic work. I have an active

client is waiting for deliverables.

Anthropic support has been completely unresponsive for nearly 3 weeks.

Has anyone experienced similar data loss after Pro upgrade? Any advice?

---

Timeline:

- April 7: Upgraded Pro, data disappeared, $200 unauthorized charge

- April 20: Sent initial detailed report

- April 21: Sent follow-up (URGENT)

- April 25: FINALLY got an automated response from Fin

- April 25: Escalated to human support agent

This is unacceptable for a paid Pro plan. Companies respond to public pressure

better than private emails apparently.

https://preview.redd.it/v8j06auu8axg1.jpg?width=1628&format=pjpg&auto=webp&s=b75970fd5966f41404d19cf696b9ee22deaacaab

Since a few hours I only get this message

I’m trying to decide which open-source coding model plan to subscribe to next month, and I could really use some advice.

I used to rely on GLM, but after version 4.7, I’ve felt that the coding outputs became pretty unreliable and started hallucinating more than before.

For the past few months, I’ve been using Minimax’s coding plan. It works fine for simpler workflows, but it struggles quite a bit with more complex tasks (like low-level design implementations or deeper system logic).

Now I’m considering switching, and the main options I’m looking at are:

Minimax (stick with it)

Kimi

GLM (give it another shot?)

Qwen

My main use cases are:

Writing and debugging non-trivial code

Understanding and implementing LLD/system design concepts

Handling more complex, multi-step coding tasks

If you’ve used any of these recently, how do they compare in terms of:

Code accuracy and hallucinations

Ability to handle complex logic

Overall reliability for serious coding work

Title.

I have the draft for Qwen3.5 (not 3.6) 27B, would it be compatible? I tried this combination in oMLX and PP speed is actually much worse .

Hey everyone,

I’m looking to sell my 2020 Play Console Account with 2 apps currently live. The account is old and active, which can be useful for developers or business owners looking for a ready setup.

Details:

Created in 2020

2 Apps Live

Clean account history

Ownership transfer available

Serious buyers only. DM me

Thank you :)

TL;DR:

I explored a habitable alien planet called Aurelia, where lower gravity, dense air, purple-silver vegetation, and vibration-based ecosystems shaped a very non-Earth-like land creature called the Orrahl. Instead of a head, face, mouth, or four legs, it has a tall oval body, six pressure-pad limbs, vibration sensing, bioluminescent warning signals, and ground-feeding filaments. It is biologically plausible as a slow filter-browser, and when a human gets too close, it anchors itself, pulses warning lights, sends ground vibrations, and may shove defensively with a powerful hydrostatic limb.

—————————————————————

I started this little worldbuilding experiment by asking ChatGPT to imagine a habitable alien planet, but I didn’t want it to be just “Earth but with purple trees.” I wanted something that felt alive, believable, and strange enough that it could support its own kind of evolution.

The planet we came up with is called Aurelia. It orbits a warmer golden-looking star, and the whole environment has this soft lavender and amber tone. The atmosphere is breathable, slightly denser than Earth, with enough oxygen to support active land life. Gravity is also a bit lower than Earth, so creatures can evolve taller, more delicate body structures without collapsing under their own weight. The plants are not green like Earth plants. Because of the different light spectrum, most of the vegetation is purple, silver, blue, and faintly iridescent. The planet also has a strange ecosystem where many living things communicate through low-frequency vibrations in the ground.

At first, we created a land animal called the Veyra Strider. It was biologically sound, but still somewhat Earth-like. It looked like a mix between a deer, antelope, crane, and alien grazer. It had long legs, vibration-sensing cheek plates, wide flexible feet, and faint bioluminescent markings for herd communication. It made sense biologically because it evolved for open plains, lower gravity, and vibration-based predator detection. But visually, it still felt like something we might recognise from Earth.

So I asked: what if we created something that almost does not resemble Earth animals at all?

That led to the creature I really liked: The Orrahl.

The Orrahl is not built around the usual animal body plan. No head, no face, no mouth, no pair of eyes, no tail, no four legs. Instead, it has a tall upright oval body, almost like a living seed pod or biological standing stone. Around its lower body are six thick hydrostatic support limbs ending in broad pressure pads. It doesn’t walk like a horse or a dog. It moves by shifting internal fluid pressure, anchoring some pads while extending others, almost like a slow biological machine.

The Orrahl is a slow land filter-browser. It feeds partly by filtering airborne spores and mineral mist through side vents, but to make it more biologically plausible, it also absorbs nutrients from microbial mats, soft fungi-like growths, and wetland biofilms through feeding filaments underneath its body. That way, it is not magically surviving on air alone. It has a real energy source.

Its body surface is pearl-gray with violet tones, tough and waxy to prevent drying out. Vertical breathing grooves run down the body, and faint blue-white bioluminescent waves pulse under its skin. These lights are not just there to look cool. They are used for communication, warning signals, and group coordination. The creature senses the world through vibration-sensitive pads, chemical filaments, light-sensitive skin patches, and dark sensory pits around the upper rim. It does not “look” at you like an animal. It senses you as movement, pressure, scent, shadow, and ground vibration.

We also discussed whether it is biologically plausible. The answer was mostly yes, as speculative biology. The hydrostatic limbs are based on real biological principles, like octopus arms, worm movement, and muscular hydrostats. The radial body plan is also possible, because Earth has animals with radial symmetry, especially in marine life. The main issue was energy intake and drying out on land, so we refined the creature to have ground-feeding filaments and a protective outer membrane.

Then we explored how it would react to a human approaching it.

At around 20 to 30 meters, it would detect the human through ground vibration. At 10 to 15 meters, it would stop feeding and close its vents. At about 5 meters, it enters a defensive posture. Its six pads spread wider. The body rises more upright. The outer membrane tightens. The glowing bands flicker in sharper rings. It sends a low-frequency warning pulse through the ground, something a human could feel through their boots and chest.

It does not want to attack. It is not a predator. But if the human gets too close or touches it, the Orrahl can defend itself by suddenly extending one of its hydrostatic limbs sideways. It is not a kick like a horse. It is more like a heavy muscular pillar shoving outward with massive force. Since the creature is around 3.5 to 4.5 meters tall, that shove could easily knock a human away.

What I really enjoyed about this is that the creature does not feel like “alien deer” or “space dinosaur.” It feels like something from a different evolutionary path. It has biology, behavior, feeding logic, defensive logic, and a relationship to its planet. The images made it even better, especially seeing the Orrahl standing in the purple wetland, then reacting defensively when the human gets too close.

This was honestly one of the coolest worldbuilding sessions I’ve done. It started as a simple habitable planet idea, and somehow turned into a believable alien ecosystem with a creature that feels strange, beautiful, and slightly terrifying at the same time.

Hello everyone,

Since sharing the Blueprints Updater integration a few weeks ago, some users have encountered problems that I wasn't aware of before. Thanks to everyone's bug reports, I've improved and upgraded the integration to be more accurate and optimized.

Currently, I've just released version 2.0, a major upgrade that not only fixes the bugs that everyone helped me point out but also adds cool features like detecting and warning about breaking changes that could potentially damage existing automations/scripts.

Details about the integration can be found here: https://github.com/luuquangvu/blueprints-updater

Please try it out and give me feedback so I can improve it. Thank you all!

This is a request for help for the people that want to use locally very large models on Q8 and better quanta at all costs, in my case the cost is inference speed.

So I have a 512GB DDR4 ECC 2666 with a Threadripper Pro 3945WS that gives me ca. 5-7tok/second for MiniMax-2.7 with llama.cpp CPU backend. Yes, it probably feels like torture for the ADHD generation, but I'm using it for processing LARGE specs and planning, and it steers a Qwen-3.6-27B for implementation and testing. Of course I've tried first low-bit quanta but the decrease in performance was not worth the marginal increase in speed.

So I was wondering if someone has any "tricks", unmerged PRs or hidden gems (I get that the CPU only inference is not the most popular topic right now, but maybe there are some half forgotten github repos somewhere), to maximize the inference output without sacrificing the model weights.

Also another topic of interest will be upgrading the bottom of the barrel CPU to a 5975, while everyone emphatically says that the inference speed is memory bandwidth bound, I see that during the PP and also on the inference all the cores are at 100% load. Here even the cloud models have contradictory answers, from "no significant increase" to doubling the speed. I really want to hear it from someone that actually did this.

Built this over a weekend because I had a problem: after months of using Claude Code, I had hundreds of session files and no way to search through them.

Chronicle indexes all your Claude Code sessions and gives you instant full text search. Click any result to resume the conversation in your terminal.

Built with SwiftUI and SQLite FTS5. Everything runs locally, nothing leaves your machine.

Free and open source: https://github.com/JosephYaduvanshi/claude-history-manager

Would love to hear what you think.

hello! i am an undergraduate with a summer internship who wants to start saving for some short-term expenses like trips. is it better to save in my hysa or invest in index funds?

Bikinis as a prop or recreational swimwear? Lewd. Bikini's as a uniform for your productive and necessary employment as a barista? Totally fine.

Purchased one of these for a short term solution, but I’m having trouble with connection to Z2M.

Pairs, keeps flashing, keeps changing networks, leaves.

I’ve tried pressing the button every few seconds, to keep it awake whilst pairing, still doesn’t work.

Sensor shows N/A for lux, battery and rain.

Any advice would be greatly received on ideas to get it working 👍🏻

1. install this https://github.com/OmniLLM/omnillm
   
2. register and add github copilot accounts as providers

https://preview.redd.it/avvcxkkg5axg1.png?width=2152&format=png&auto=webp&s=49f7f2d7cae72af46bbd53df53dbf09926fdfb3a

1. create a virtual model, add all those providers, as claude-haiku-4.5-loadbalancer

https://preview.redd.it/jd2u34wj5axg1.png?width=1646&format=png&auto=webp&s=e15cf643ed1588e717cd600d8a6ecfb73811bcb0

then in claude code just use that model, enjoy!

(Ignore the cringe image, I basically asked for "create a random guy rejecting claude and accepting chatgpt" and it added words for no reason)

I have been a long timer user with ChatGPT plus and few weeks ago I stopped plus and got Claude Pro just to see what the hype is. So Sonnet is really amazing, Opus is cherry on the top with recent 4.7 but the usage limits are anxiety inducing. I wanted to try out different apps and projects and brainstorming sessions and it keeps giving me warning about weekly and session limits.

I want to switch back to ChatGPT plus because I basically never had to worry about any limits on neither Codex not chat. But I really really love the Claude responses which are concise and not condescending or glazing. Even if I try to make Claude friendly it does not become cringe and keeps the friendly interaction for about a sentence and gets back to business.

I had this problem with chatgpt that it was either condescending sometimes or glazing or repeatig itself. It also crafts responses in such a way that it creates new points where they are not required keeping the sentences very short.

I want Claude responses in ChatGPT plus. Is there any way I can prompt in that way? please help.

(I can't have both ChatGPT plus and Claude pro).

Does anyone know of a workflow that comes closest to generating images like these? The quality looks like NBP but there's no way it would let them generate this without triggering the nsfw filter. https://www.instagram.com/nadiabennt/

Over the last few months, I have been working rigorously on this project, which helps users track their job applications. It also provides a platform to find and share referrals, request resume reviews, and share interview experiences within the community.

The platform now has 300+ users.
website : naukriclear.com

Hello. I am M25 and my mom have a lot of debt online. They used me and my sister (F24) as character reference. They have been harassing us na for quite some time

The worry is, my sister is working in a big government office. And if the bill isn't settled, she's worrying na baka sa office na tumawag yung nangha-harass sa kanya.

We're actually looking for ways na to pay for the other online debt pero we are prioritizing this one. Kasi the main problem is with the PesoLoan. Gusto sana namin black and white. Pero sagot nila sa email, ganito lang.

*Dear Valued Client,*

*Thank you for reaching out to Pesoloan!*

*We acknowledge your request for written confirmation.*

*Please be informed that we do not have a separate procedure for issuing written confirmation beyond this email thread. Our communication here already serves as the official documentation of the agreement and confirmation of your concern.*

*We also trust your commitment to settle the agreed amount today, and likewise assure you of our process. Once you have successfully settled ₱17,000.00, your account will be forwarded to our relevant department for closure processing. The system will then update and reflect your account as fully settled with no remaining balance.*

*We appreciate your understanding and cooperation.*

Asking for advice lang po kung should we proceed na po? Baka po kasi tactics lang nila for us to pay then continue to harass us again po.

Nakikipag settle po kasi kami na 17k na lang ang ibabayad kasi 28.5k po yun. Tapos nakapaghulog na kami ng 5k before. Hindi lang talaga nakapag continue ng payment. 17k was the principal loan po kasi eh. So ayun po. At least may interest pa rin na 5k, di ba?

Kaso di po daw kasi nila pwedeng baguhin yung amount sa app? Tunay ba yun?

Please help po. Thank you.

Hi all, please could you edit the four people into the picture with the Eiffel Tower? Thank you so much!

Hi all,

Looking for an indoor camera to replace my 10 years old Hikvision. I use Scrypted for HKSV and Qnap NVR for recording. Would like something with ONVIF with motion events and PTZ control, preferable higher resolution on main stream and ethernet connection. I have checked the new c260 but the main stream is 4K h265 not compatible with HKSV, substream has very low resolution, maybe not best of my use-case. Any suggestion which models work best?

Also would like to ask what integration do you guys use in HA? I have c320w and just set it up as RTSP camera with rebroadcast from Scrypted, is it the correct way? Many thanks

Hi, how do you add metallical color effect on bold characters, in Photoshop CS3 / CS6 ?

Thx for your help.

https://preview.redd.it/7jwg2jl24axg1.png?width=1378&format=png&auto=webp&s=5f922a2b5c7e0db8fac9219f97a0986448357599

This is what Claude thinks about itself??? Can anyone explain if you understand?

Self explanatory. Mel is still one of the worst champions to play against despite the nerfs.

Because the numbers does not fix the unfixable. Thank you :)

Built a niche newsletter a while back.

Small list, maybe a few hundred people, but they were exactly the kind of readers you'd want, all in the same industry, all with the same problems.

First thing I did was chase sponsors.

Reached out to a bunch of companies, put together a little media kit, priced my ad slots the way every "how to monetize your newsletter" article told me to.

Got a few nibbles. Made some money.

Then realized I was writing FOR the sponsors more than I was writing for my readers.

Topics started drifting toward whatever an advertiser might care about.

Quality dropped. Open rates dropped.

The whole thing started feeling hollow.

The moment things actually clicked was when I stopped thinking about scale and started thinking about what my readers actually needed to DO. These weren't people who just liked reading, they had real problems they were trying to solve.

So I built one small thing, a paid resource, very specific, very practical, priced it in a way that made the decision easy. Not cheap, not outrageous, but clearly worth it to the right person.

First 20 sales made more than months of ad deals combined.

What I'd tell anyone starting out:

If your list is niche, the numbers will always look small compared to big general newsletters. Don't let that fool you. A small group of people who really care about one specific thing will pay for something that actually solves that thing.

Ten readers who spend real money with you are worth more than ten thousand who scroll past an ad.

The ad model only works when you have scale. Most niche newsletters never get there, and that's fine, because they don't need to.

The question isn't "how many subscribers do I need to start making money." It's "what would my readers actually pay for right now."

Answer that and you're already ahead of most people building newsletters..

Used acrylics in a painting class was fun to try and do all the different materials!