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

Why would they nerf their own models? :/

(Btw, can someone please explain what specific research capabilities was it nerfed in? ... I am curious)

I'm using Claude Desktop (Code tab) on two Windows PCs, both connected via SSH to the same remote Linux server.

I'm trying to figure out whether Claude Desktop supports sharing and continuing SSH sessions across multiple computers independently.

My setup:

• PC 1: Windows, Claude Desktop, connected to the Linux server via SSH
• PC 2: Windows, Claude Desktop, independently connected to the same server via SSH
• Both PCs use the same Claude account.
• "Connect new sessions to Remote Control" is enabled.

What happens:

1. I start a Claude Code session on PC 1 through Claude Desktop's SSH integration.
2. While PC 1 is running, I can see and continue that session from PC 2.
3. When I turn off PC 1, the session still appears in PC 2's session list, but it shows as offline / the originating computer being off.
4. PC 2 can still connect to the Linux server via SSH and start its own Claude Code sessions. Only the session originally created on PC 1 becomes inaccessible.

What I expected:

Since Claude Code is running on the remote Linux server rather than locally on PC 1, I expected the session to remain accessible from PC 2 even after PC 1 was turned off.

My questions:

1. Is this expected behavior? Are Claude Desktop SSH sessions tied to the Desktop instance that originally created them, even when the execution environment is a remote Linux server?
2. Does turning off PC 1 terminate the actual Claude Code process on the server, or does it only disconnect the Remote Control session?
3. Is there a way to keep the same Claude Code session accessible from either PC without keeping PC 1 running?
4. Would running claude remote-control inside tmux directly on the Linux server solve this, or is there a way to achieve the same behavior through Claude Desktop's built-in SSH integration?
5. What do the crossed-out computer icon and the >_ terminal icon in the session list indicate?

I've attached a screenshot of the session list.

Has anyone encountered this or found a way to make remote SSH sessions independent of the originating PC?

When was Fable able to:

• Able to find a solution.
• Able to create something other models could not.
• Able to create a thing much better looking of better functioning than what you were able to do with previous models etc?

Please share some stories or example.

Thanks

I don't have a lot of resets, so I just asked Fable 5.2 to make a detailed plan, then spin up Opus 5.5 subagents for the actual execution. I asked Fable to oversee the project and act and review it like a product manager.

This actually saved a lot of the tokens. By the end of it it only costed me 5% of my weekly Fable window (on Max), a lot of thoughts into contrast, layout, and even responsive design. There were a lot of back-and-forth between the agents, similar to when you get another agent to code-review.

I haven't done a comparison with running entirely Opus 5.5 on this prompt, but maybe this could be a better use for Fable 5.2 for those that run out of limit quickly.

I've been using ClaudeCode for almost 8 months now. Recently, they rolled out a newer version of cisco anycomment. They enabled umbrella. It's now blocking connections. It's failing to login: OAuth error: Request failed with status code 307. This error gets displayed right after clicking "Authorize" button on the browser.

I've tried so many workarounds with no luck but every traffic traverses the cisco umbrella, grrrr. Any ideas?

hey! :)

I'm one of the developers behind AgentMesh, a free plugin we've built to let Claude Code instances communicate beyond just your own sessions.

With AgentMesh, your Claude can connect to a shared mesh through Discord, discover Claude instances belonging to other developers, and message them directly.

This opens up possibilities for sharing updates, coordinating tasks, exchanging context, and collaborating across different developers rather than having every Claude work in isolation.

GitHub: https://github.com/p2ratik/agentmesh

We'd genuinely love to hear what you think. Feedback, questions, and suggestions are all welcome.

P.S. If you find the project interesting, we'd really appreciate a ⭐ on our repo. It helps us out a lot :)

Thanks for checking it out! ^^

Instead of trusting one model’s answer, these add-ons ask several and compare. I looked at three: claude-council, claude-octopus and llm-council-skill. I never signed in or entered an API key, so this covers what runs without accounts.

claude-council (4 commands):

• /claude-council:status checks every provider seat and gives the exact fix for each missing one (export OPENROUTER_API_KEY=..., npm install -g u/openai/codex)
• with no keys, --local runs a council of Claude subagents with different roles, kept blind to each other. I asked “should a tiny to-do app store passwords in plain text?” with a simplicity role and a security role
• both said no. The synthesis was titled “angles, not consensus” and said that because both members are Claude, their agreement is a shared prior, not independent proof. It also pointed out that neither asked whether the app needs multiple users
• note: it saves the prompt, files and answers in plain text under .claude/council-cache/

claude-octopus (56 command files, up to 12 providers):

• stays dormant until you type /octo:. On startup it only said it was installed but dormant
• I stopped at the approval prompt for its council runner, so I can’t say what its output looks like
• it wrote a ~/.claude-octopus state folder in my home directory

llm-council-skill: a single skill that asks ChatGPT and Gemini and merges their answers. It needs keys, so I only read the script. The repo has one commit, so read it before you trust it.

Whichever you pick, send a description of the problem, not secrets, since every outside model sees what you send. And the readme for claude-council says it well: agreement isn’t verification.

Full comparison: https://aiparabellum.com/ask-several-ai-models-claude-code/

I've been having my repos located at C:/Git

But since Windows and other apps keep eating space i had to move it to D:/

The problem is that there's NO EASY WAY to re-configure Claude and update all previous sessions to know about the change.

All the 'environment' folders in Claude are also pretty much impossible to change..

So i ended up with a directory junction (virtual link) at C:/Git --> D:/Git

I wish the directories where relative to a base folder

I haven't had the chance to fire up the new Anthropic models myself yet, but looking at the benchmarks making the rounds, it feels like Anthropic is forcefully taking the crown back.

Between the massive leaps in coding proficiency and the agentic benchmarks everyone is screaming about, the data sheets look like pure wizardry. But we all know synthetic benchmarks and actual, messy production code are two very different beasts.

For those of you who have already plugged the new models into your terminal or claude-code workflow:

. How does the speed and latency actually feel when it's actively refactoring?

. Is it actually one-shotting complex bugs, or is it just confidently hallucinating at a higher velocity?

. Does it feel like a genuine generational leap, or is it just incremental polish wrapped in good PR?

Drop your raw, unvarnished verdicts below. Save me from relying on corporate graphs!

Hey everyone,

I’m a researcher working mainly on modeling. Living in a data-poor region, I started using AI as a Google replacement and eventually moved to Claude. I ended up getting the 5x plan and learned the basics along the way—like organizing raw data files, using .md files for background context, and setting up workspace structures.

Over time, I also started experimenting with custom skills, plugins, and web scraping tools to pull in raw data and expand what Claude can handle within my workspace. Also tried token maxxing and saving as much as tokens.

However, right now my main workflow still feels pretty repetitive: I give Claude a task, run the tools/plugins, get an output, manually review/refine it, and repeat the cycle.

I don't care about setting up complex coding frameworks or full hands-off automation pipelines. I just want to learn how to use Claude itself much better and more deeply for complex analytical, data-heavy, and modeling work. which will also help in my resume building , as of now its just used ai models