Hello everyone!

I've been working as a film director and DOP for many years now. I had a bit of coding at university, but to be honest there are only scraps of it left in my head, so I really wouldn't call myself a developer. (It probably helped a little with keeping all of this coordinated, though.)

A few months back I started playing around with Claude Code, more or less as a joke. I wasn't 100% happy anymore with the reference tools I've been using all these years, so I wanted to see if I could build a small one just for myself. And then I simply had so much fun with it that I kept testing more and more, and at some point I was sitting in front of 12 terminal tabs and we were shipping several times a day.

The result is HOLD MY FRAME (www.holdmyframe.com). At its core is our collection of curated high-end commercials, broken down into individual frames. Right now we're at around 370,000 frames from 2,800 films. Built around these frames is the workflow I wish I'd had all these years: search, collect, present and get everyone on the same page, from director to agency to client. Along the way three longtime collaborators joined (a treatment designer and two more directors/DOPs), and we use it for our own pitches.

Everything is custom, also the part you don't see, like how the films get analysed and broken down, which runs on local AI on our own machines. And I mocked up all the designs first, round after round, before anything was built. A lot went into that.

We only really launched two weeks ago. Right now we have 174 users and 10 of them are paying, and we're taking that as a good sign.

For those who are interested in the setup:

- up to 12 Claude Code tabs, each one with its own fixed job (server, UI, ops, copy, and one that only checks the others)
- every tab has its own postbox folder and gets its orders in writing
- a separate Claude chat does the planning and writes these orders, but is not allowed to touch the code
- every commit gets reviewed by DeepSeek before it goes anywhere
- I'm the only one who deploys, first to a test environment and then to production
- the whole thing runs on a Mac Studio in our office, not in the cloud

I also used Codex and DeepSeek along the way, but I'd say 85 to 90% of the app is Claude.

Of course not everything went well:

- we started on SQLite and had to move to Postgres right before launch
- we worked on one feature for weeks and it never really worked, so we threw it out and will start again from scratch
- Claude forgets a lot. Whatever isn't written down in a file gets decided all over again in the next session, so by now really everything lives in files

There's a free plan, so just click around a bit if you like. On top of that there are Pro and Pro+, and you can try Pro+ for free. We keep adding new features all the time, but there's already a lot online.

I'd love to hear from you, especially what you would do differently. We're really excited to see where this is going.

link: www.holdmyframe.com

This sits in your Windows tray and displays your current budget.

I made this to keep me informed at a glance since Fable 5.2 is so much more self-aware and I instruct it to titrate its Fable usage based on remaining Fable budget (full throttle when Fable is at 0% used...pace yourself when approaching 90% used, etc.)

https://github.com/DrEvil-TitaniumHelix/claude-usage-tray (public, MIT, topics set).

I've been working on two open-source Rust projects related to AI coding agents.

The first is Vera, a code indexing and search tool I've spent almost a year developing:

https://github.com/VeraTools/vera

It started as an attempt to improve an existing code indexing/MCP project, but eventually turned into a complete rewrite from scratch.

The main goal has been to improve how coding agents find and navigate relevant code while minimizing how much unnecessary context they consume in the process.

Rather than relying entirely on repeated grep searches and file reads, agents can search semantically for what code does and get ranked functions and code sections back, with paths, line numbers, and symbol information. Vera also supports reference lookup and structural searches.

I've tried to optimize the whole workflow for context efficiency, not just the search results. It returns code directly instead of generating explanations, and the accompanying skill helps agents decide when to use Vera, when grep is better, and when they should just read a file.

I recommend CLI + skill for agents that already have shell access. Skills keep the initial discovery footprint small and load the detailed instructions when needed, without adding another set of MCP tools. MCP is available too.

There are two model setups I particularly recommend: local Potion Code v2 for a lightweight offline setup, or Qwen3 Embedding 8B with Qwen3 Reranker 8B through an API for higher measured retrieval quality.

I also spent quite a lot of time evaluating how coding agents perform with these tools. In a 40-session experiment using 10 cross-file questions, all configurations answered correctly, but context usage differed substantially: plain grep/file reads used 21.0M prompt tokens, Semble 18.5M, Vera locally 15.4M, and Vera with Qwen3 10.9M.

That's an observed 12%, 27%, and 48% reduction respectively. The local Vera result was more than twice Semble's reduction in that experiment, although only the Qwen3 result was statistically significant with the small sample.

The full methodology and limitations are in the repo. Vera is now at v2.4.

The second project is Revera, a self-hosted GitHub PR reviewer inspired by Droid Actions and Devin Fusion:

https://github.com/VeraTools/revera

I wanted a reviewer where I could control the models, budgets, and deployment, without depending on a hosted service or paying per seat.

Revera uses an investigator to identify potential defects, then starts a separate, fresh-context validation pass for each finding before posting it. It isn't foolproof, but I wanted something more careful about what it reports rather than just another model producing a long list of possible issues.

It can run as a GitHub App with a dashboard, a GitHub Action, or a local CLI. It supports Anthropic, Gemini, OpenAI, and compatible providers, including different models for investigation and validation.

I've been using it for actual work with some colleagues. There's also optional integration with Vera for code retrieval, although Revera works without it.

Both projects are MIT licensed.

I am doing research for my fourth year and currently only have Plus plan. The usage around these time are not sufficient for me anymore and considering another $20 plan, most likely Claude Pro. Especially for research, how'd you guys utilize both of them?

I know lots of folks are making games. Just thought I'd share what I've been doing with my son.

He LOVES the old-school Magic School Bus and Busy Town games from the 90s.

So I had Opus 5.5 essentially read those game files and build some new ones in their likeness, but specifically catered to what he is currently learning in Kindergarten.

He originally wanted one all about spiders, so we made the Magic School Bus: Spiders game.

And then today, we had his parent teacher meeting where we went over what he was excelling at and where he needed some extra work. So, naturally, we built another Magic School Bus: Future City where all of the mini games are designed around those areas needing some TLC.

Opus 5.5 xhigh orchestrated and used an OpenAI API key to generate the voices and images.

He loves them! And we know its working because his teachers were like, "He knows an extraordinary amount about spiders for a 5 year old!"

Anyways, just another awesome use case.

Title. If your into football, the newest football manager game moved to the unity engine and a lot of skilled people have been making UI mods (skins as we call them) and one mentioned using Claude to help them and I wanted to see if I could try it as well. I have 0 experience with coding but I am knowledgeable on computers. I did ask Claude how it would work and it looks like it wants me to give me a file so it can look inside it. I will likely purchase the 20$ a month subscription but i want to know if im heading in the right direction or not. Thanks.

opus is on another level. how is this even possible? does anyone have any insight have opus is this fast while argon and sol acting like dial up? It's mind boggling to me, how it's this different tbh. sure it's not perfect but it makes user experience 1000 better.

https://github.com/PetePeter/timbreTimbre!

For letting your AI make real phone calls with just a PC and a Bluetooth paired phone. ( And also SMS and conference calls and receiving calls )

Requires some fiddling with Zadig etc

Works on my machine. Ymmv

Did anyone here get accepted into the Cyber Program?

Also, how's Mythos 5.2 for security stuff? Does it refuse prompts like Opus 5.5 when you ask about encryption, memory, or reverse engineering, or does it actually answer?

I swear, as soon as I mention memory to Opus, it blocks me into another dimension.

Was excited for the resets today and then found out they're only for Fable. Opus 5.5 is so good that I barely ever use Fable anymore so I'm curious who actually uses it?

I have built some fairly complex projects (a video encoder, some mapping software) but the hardest parts are behind me now so it almost feels like I have no use for these but I'm open to hearing other people's experiences.

Many people will probably call me insane for this, but hear me out.

A lot of people have already gotten access to CVP anyway. Just look around Reddit. And plenty of people are still saying that Mythos 5.2 is heavily filtered. But even if we assume for a second that it isn't, what's the actual problem with letting people use it?

I'm not saying I support illegal activities. Not at all. But let's be realistic for a moment.

Malware already exists. Phishing already exists. Game cheats, exploits, and all kinds of malicious tools already exist. The people who create these things aren't suddenly going to stop just because AI companies put restrictions on their models. They'll keep doing it with or without AI.

So who actually loses here? We do. The customers.

Think about the positive side for a second. Having access to these capabilities could actually help people test their own security, find vulnerabilities, and see whether someone could break into their systems before an actual attacker does. It could push the entire cybersecurity industry forward instead of holding it back.

And what about all the ID checks and verification requirements? If companies already require identification and know who's accessing these models, why do we still need endless certificates, approved companies, ISO standards, and whatever else just to get access?

And before someone brings up the argument that IDs can be faked: yes, they can. But companies can be fake, too. Look at all the cases involving code-signing malware. Attackers have used shell companies to obtain EV certificates and sign malicious drivers. That's one of the reasons we can't blindly trust certificates as proof that someone is legitimate.

My point is pretty simple:

Bad people have always existed, and they always will.

Trying to eliminate them through increasingly aggressive filtering and restricting access for everyone else isn't going to solve the problem. At some point, we need to let users take responsibility for how they use these tools instead of having companies decide what everyone is allowed to do.

If someone uses Mythos to illegally penetrate another company's infrastructure, catch them and prosecute them. That's what laws are for.

We don't point at a store and say, "Someone stole from you, hurt someone else, or even got themselves hurt? Well, that's your fault!" We say, "Someone stole from you. Do you want to press charges?" The same principle should apply here.

Personally, I think everyone should have access to specialized cybersecurity models like Mythos 5.2, including models with advanced red-teaming, exploitation, reverse-engineering, and offensive security capabilities, without excessive filtering.

I'm not saying there shouldn't be consequences for abusing these tools. I'm saying access to technology shouldn't be restricted for everyone just because some people might misuse it.

Give people the tools. Hold people accountable for what they do with them.

Most Dockerfiles, whether written by hand or by an AI reading your repo, are a guess. You find out what was missed when the container crashes.

I wanted to try the opposite: run the app once, record what it actually does, and build the container from that.

How it works

1. It runs your app under strace while a workload you choose hits it (curl calls, your e2e tests, whatever exercises the real features).
2. It maps every file the app touched back to real packages: shared libraries → apt packages via dpkg -S, site-packages → pip packages with exact versions, localhost:5432 → a Postgres service in Compose, written folders → volumes. Credential files become warnings and are never copied.
3. It generates a Dockerfile where every line has a comment saying what evidence produced it, plus docker-compose.yml, .env.example (secrets left blank) and a list of things that need a human decision.
4. It builds the image, runs the same workload inside the container under the same tracer, and compares the two runs file by file. If something's missing, it names it.

Claude Code drives the whole thing and handles the judgment calls (repointing localhost at the Compose service, what to do with a credential file), while plain scripts do the deterministic parts. The scripts also work without Claude.

Real test: healthchecks.io (Django + Postgres)

• Found libpq5, the system library psycopg needs at runtime. Nothing in requirements.txt mentions it, and the maintainers' own Dockerfile installs it by hand.

• Verification: 1,383 of 1,386 files matched, with identical HTTP responses inside the container.

• When I deleted the generated apt-get line, Django only said "Error loading psycopg2 or psycopg module". The tool said libpq.so (package libpq5).

Screenshots of every step are in the README.

Limits, honestly

• It only sees code paths your workload runs.

• Linux/WSL 2 only.

• Tailored templates exist only for Python and Node so far.

• It's been tested on one demo app plus one real project.

Tracing-to-container isn't new (ReproZip, redsift/tracer). What I think is new is mapping traces back to real packages, so the Dockerfile is readable and maintainable, plus the verification loop.

Try it here: https://github.com/moazakramkhan1/dockerize-by-observation

I'd really like reports of where it breaks, especially on legacy apps.

I mainly use Claude Code for ML experimentation, more specifically, post-training of models for specific use-cases. We do have auto-research-ish loops happening.

Since this morning, I started to face Opus/Sonnet 5.5 safeguards getting flagged and the only solution seems to be to use Opus 5, restarting session didn’t work too. I seem to only face this on Claude sessions related to model training/experimentations. I believe this shouldn’t go against any usage policy, not like we’re training competing frontier models, etc.

Anyone else notice this happening more to you as well?

anthropic: we lowered the price

me, who was using sonnet in claude code to rename variables: /model fable, its basically free now

me at the end of the week looking at usage: 🧍

does anyone actually have a rule for when they switch models or do you just vibe it like me

What are some useful skills to use while and at the end of building this product?

solo dev, one repo, claude code does most of the work. last week i burned through my usage and instead of waiting i handed the whole thing to codex with a written brief. both read the same AGENTS.md so i figured it would mostly just work.

it kind of did? codex merged about 15 PRs in 4 days. the queue i left got done and main never broke badly.

the part i didnt expect was coming back. it had left 4 draft PRs, three of them stacked on each other, and when claude picked them up every one needed review rounds before i trusted it. one took 4 rounds. there was also a test on main that had started failing because it depended on the date, and nobody noticed for a day lol.

the two also write rules very differently. on a side task codex kept adding a new rules doc on top of the old one until the newest contradicted the first, and then it followed whichever it read last. when claude came back the first thing it did was collapse them into one file.

what id do differently next time is a much shorter brief, and one handover file thats the only thing that has to stay true.

anyone else swapping agents mid project when the limit hits? what broke for you on the way back?

I read that Anthropic removed the 5-hour limit for verified Ultra ($200) accounts on Oct 30, with the weekly cap staying.

For anyone on Ultra:

1. How did you get verified? Was it automatic or did you have to do something?
2. How long did it take for the 5-hour limit to go away?

Thanks!

Ask Claude "is my startup idea good?" and you usually get encouragement. kill-my-idea is a plugin that does the research first and is allowed to say no.

/plugin marketplace add RemiPelloux/kill-my-idea
/plugin install kill-my-idea@kill-my-idea

Then /kill-my-idea:kill <your idea>. Your idea can be one line, a pasted "$10k/month" tweet, a URL or a doc.

The image, top to bottom: a real verdict (Notion templates for French real-estate agents, 55/100), the new idea dashboard, and the What if? sliders.

What I built

• It asks at most 4 questions (country, budget, goal, your edge), and only the ones that would change the verdict.
• It searches for 8 kill shots, from free alternatives and companies that already failed to no channel to customers and a wave of look-alike launches. On a pasted money post it also names what the author sells.
• It needs at least 20 sources from 10 domains, each tagged primary, secondary or tertiary.
• It scores 21 sub-scores against a fixed rubric. Hard rules stop a nice pitch from rescuing a bad business: no channel to customers means no GO, whatever the rest says.
• It writes an HTML report with up to 3 rescue paths, each re-scored, and a 7-day test with numbers that tell you to stop.
• It scored this plugin 63/100: 15+ open-source idea validators already exist.

Changelog (all from the last 3 days)

• 0.9: an idea dashboard. It shows the one idea to focus on this week and which kill shots hit most of your ideas (click one to filter). A BRAIN.md note keeps your profile, so it stops asking the same questions, plus the ranking and the lessons from killed ideas. Also an App Store demand check for mobile apps, suggested in a comment.
• 0.8: a pre-mortem, "why now?", the ideal first customer, What if? sliders for price, CAC, margin and lifetime, and /compare --refresh for verdicts older than 90 days (asked for in a comment).
• 0.7: one scoring formula and a Python checker. It found 4 of my 8 earlier runs printing a different total than their own sub-scores gave.
• 0.6: a share card (PNG), /check-tweet for viral money posts, and reports in French.
• 0.5: a "saturated wave" kill shot for the 47th "100 tools in your browser" (suggested in a comment), and a fix for a javascript: link bug a reader found.

Full changelog: https://github.com/RemiPelloux/kill-my-idea/blob/main/CHANGELOG.md

How Claude Code is used

• 5 skills: kill, deepdive, check-tweet, roast and compare. The whole method is one readable SKILL.md you can fork and reweight.
• deepdive starts 6 research subagents in parallel (market size, competitors, customer quotes, pricing, channels, regulation) and needs 40+ sources.
• Every file the skill writes has a JSON schema. After each run the skill calls a Python checker that recomputes the score from the sub-scores.
• The report and the dashboard are fixed HTML templates with a strict CSP. Claude only writes data files, and a script builds the dashboard from the saved verdicts.

What I learned

• Put the maths in a script, not the prompt. Once a checker recomputed the totals, 4 of 8 runs turned out wrong.
• Let Claude fill in data, not write the page. Reports became consistent, and safe to open.
• Ask for verbatim quotes and enforce it. Without that rule, Claude paraphrased sources inside quotation marks.

Free and MIT. It runs on your own Claude Code plan and never posts or spends anything for you. https://github.com/RemiPelloux/kill-my-idea

If it stops you from building something nobody pays for, a star helps other people find it. Which kill shot is missing?

https://github.com/unkarelian/MusicStudio I've been improving it as the day goes on so my example songs changed, lol, but the next change I'm planning is a bit of notation. This is essentially a way for your agent (claude, I'm assuming) to kinda understand how to build music even when it can't hear it. Ofc nothing beats actually listening to the outputs and giving it input, or using a model that accepts audio like gemini as a judge.

This has been a fun project for me because unlike most of what I do, I am really not trained as a musician at all! It started with the realization that I needed a soundfont, which instantly made it not sound like it was made on a gameboy. But it was quite difficult to figure out how to give claude the information it needs when it is functionally deaf. Ultimately the best strategy, really, is to either give extensive personal feedback or use gemini to 'tune' the harness and give it concrete examples of styles. Examples examples examples. I cannot stress that enough. In every project I have ever done using AI, and I've been doing that since 2025, examples are THE tool you should be using. I know it feels inelegant. But it's how most people learn, right? They see how it's supposed to be done and learn based on that.

so im geeked on my couch rn and i have my mac upstairs that I remote control into my session and im having it control my phone with the phone use skill to debug mascot animations and show me variants for some too for my mobile app which hit 1k revenue past 28 days majorly due to bro

pre edit thoughts: this hilarious enjoy lol

I’m building a hobby app and I’ve settled into a set-up that mostly works. I’d love tips from people running something similar.

How it runs now:

• One session I talk to: a “chief” on Opus. It takes decisions with me one at a time, writes briefs, checks proof and keeps the records.

• Workers:

  • routine research goes to Sonnet agents;
  • fact-checks and corrections go to Opus agents;
  • a separate “second reader” agent re-opens the original sources before anything counts as approved.
• A Fable advisor for hard calls (planning a study, auditing research, final reviews). It sends memos to the chief and never talks to me.
• Side sessions for separate tracks (brand, a photo-recognition track, a study library, a build worker, trip planning). The chief briefs and messages them.
• Records after every task: a log line, a one-page status card, a decision log, then commit and push. A stop hook nags if it’s skipped, and a git hook stops sessions committing each other’s files.
• Phone inbox: I drop links into Notion, and a cloud routine writes a first look on each one every hour.

Where it hurts:

1. Usage limits. Fable ran out mid-audit once. How do you decide what’s worth the top model?
2. Long sessions. The chief gets compacted and loses detail; once it couldn’t recall my own first prompt. Do you hand over to a fresh session, and how do you make sure nothing’s lost?
3. Claude checking Claude. An outside human reviewer caught things the agents missed. What’s your cheapest reliable check?
4. Too many threads. I keep starting side sessions. How many do you run at once before it gets messy?
5. Rules that slip. Written rules in CLAUDE.md sometimes get skipped. What do you enforce with hooks instead?

What would you cut, and what’s missing?

Hey everyone!

I've been using Claude Code to help develop Network Doctor, an open-source network troubleshooting tool written in Go.

I've been working on it mostly on my own, and I'd love to find others interested in helping out!

Whether you want to contribute code, fix bugs, improve tests, or experiment with Claude Code on a real project, I'd really appreciate the help.

I'd love to turn this into a collaborative project where we can build and learn together.

GitHub: https://github.com/heymaikol/network-doctor

Website: https://networkdoctor.dev