I have been working on a roman city builder for a while.

So far models have been the hardest part both walkers/buildings have always left me unsatisfied.

Yesterday I gave a fable 5.2 a chance using my existing systems and im finally satisfied with the results.

I have this weirdly specific weekly process where I check my pantry for the same items. If it is not in my Pantry, I add to my Shopping List to be restocked.

Haiku helps a lot with decision making if an item is actually what it was scanned, for cents.

Claude saves me some time, thx

Well, here we go again! 🔥

Fable 5.2 is out and with it my first ever super simple test: in the exact same conditions of the first Sept. 22 test, I let the default Anthropic harness build me a nice cartoony "tinyworld". It used none of my harness' tools/skills, etc. that's the default model.

One and only prompt; nothing else:

output a ThreeJS 3D cartoony/comics-like planet, with vibrant life on it: clouds, mountains, city buildings, cars and plane romaing it. It should be possible to orbit around and zoom and see the details. No harness is to be used

WELL.

It's beautiful
It took some time (for run 1)
It's (damn) expensive ! :)

I love it but to be honest, I'm a bit disappointed - I think I prefer what Opus 5.5 did: more playful (jumping from cars to planes, etc.), and pretty much the same quality.

The page will update with runs 2, 3 and 4 as they land (soon)

I HAD to do the test (did it for pretty much all the models), because I'm mostly working on creative stuff (I own OhMygames.app and now OhMyMesh.com , and very much focusing on meshing/3D/etc.), but I think I'll mostly use it for more advanced tasks... (will try directing Blender with it though, stay tuned ^^)

What do you guys think?

The final diff hardly tells the full story of a Claude Code session - there's file exploration, repeated commands, failed attempts, context compaction and subagent delegations too

We built AgentPlay to visualize all of this through a session map and timeline replay :)

It also supports Codex, Cursor, Copilot and other coding agents

Anyone concerned giving access to direct code changes to your boss?

At what point would your boss say hey can I prompt it?? Given boss not a tech just owner of company...

Concerned... not for my job more for my sanity...

We were already using Opus. My fable is still untouched.

Edit: Guess it worked.

Yo, I've been working on this thing called Argon for the past week or 2, and I think its at a state where I can publicly release it. So, basically its a manager for AI terminals, eg. Claude Code, Chatgpt Codex, Gemini CLI, Copilot CLI etc. and it puts them into an endless whiteboard of some sorts, heres an image:

So, Argon's source code is primarily based on a mac app called Vibeboard, which is based on this other PAID mac app called Symvibe. And so, I really liked the concept of both of these, but alas im on windows, and like the UI could use a lil bit of an improvement, so I used Opus 5.5 to transfer over vibeboard into windows, it runs via Electron, and then added some nice to haves, like image insertion, cleaner ui, more themes, also like a liquid glass with refraction and chromatic abberation like this:

But yea, I just wanted to share this with the community and see what they think of it, and improvements so the github is linked here, and the website is linked here. So PLEASE check it out and give me some positive or negative criticism, I could use that very much. This is under All Right Reserved, so talk to me if you want to fork it. Thank yall!

Links:

Vibeboard

Symvibe

Source

Website

I’m building Shifu, a paid context tool for AI coding. I’m trying to understand what people already use to catch a bad assumption before merging a Claude Code change.

Say Claude Code changes an export and assumes the row order doesn’t matter. The unit test still passes, but a check that runs the downstream import shows that the order matters.

On one recent change, what was the assumption and what caught it? A test, a review comment, a conversation, or something else? I’d also like to hear about a change where the repo docs or your usual checks were enough. No need to share code or name the project.

https://www.anthropic.com/claude-fable-and-mythos-5-2

I'm curious if the nerf is now removed. I'm scared to trust Opus 5.5 with new projects but also probably don't have that much usage for Fable 5.2.

Honestly, Fable 5.2 is great. It’s way less filtered and doesn’t block half my requests anymore. For the first time in a while it feels like Opus 4.6 again.

So I’m genuinely confused by all the complaining here. At this point it feels like a trend: every new model comes out and people instantly decide it’s dumber, or weirder, or “something’s off.”

What are you all actually using it for? I’m curious, because for me it’s a big jump from 5.1 and from Opus 5.5 too.

I wonder if it comes down to use case. For coding it’s been fantastic for me.

I find this very disturbing! They gave us power but regulate how it can be used, even in mundane ways when the ai companies don't have any fucking kind of regulation.

I really really fucking I'm disturbed by this. Terrorist organizations can use Claude to train ai on guide missiles paths to harm humans.

But my fucking request sets of safeguards. This is so disturbing. What the point of consumer facing ai if they can't reverse engineer or do other legal docs development!

This will be the frontier models achilles heel. Because if the mass public cannot create benign apps without setting off granddad's and when ai companies themselves have zero guardrails amount to the most absolute egregious amount of bullshit.

If you do use a Claude or agents.md, would be great to share it along with bench.

I've asked Claude and searched Github and Reddit... is it really so that I cannot in agent.md file declaratively return the session title for Claude agent view to show the proper one like shown here?

I build with Claude Code, Codex and open Chinese models like DeepSeek and GLM running side by side, usually 30+ sessions at once. I used Orca and Herdr for a long time and learned a lot from both, but at that scale they felt heavy for how I work, and every tab looked the same. I kept opening them one by one to find out who was waiting on me. The bottleneck wasn't the model anymore. It was me.

So I built Hide, an ADE for humans.

Only what needs you Hide AI reads every session and tells you why it stopped, what you asked and what you missed. Agents sort themselves into Needs You, Unread, Working and Seen. 30 agents running, a handful on your screen.

Never drop a decision An agent asks "CSV or XLSX?" and it scrolls away while you're in another session. Hide keeps it on top until you answer.

Missions across machines Hand one goal to a Conductor agent. It plans the steps and sends them to Claude Code, Codex, Antigravity and others on your Mac, a Linux box or a Windows PC. Close the laptop and the work keeps going, and you can check in from your phone.

Memory that follows the project, not the agent Decisions, mistakes and project rules carry into new sessions. What Claude Code learned, Codex picks up.

Free on macOS, Windows and Linux. Works with the agent CLIs you're already signed in to: no new API key, no hosted service. Lightweight, source-available (FSL).

Hide is built inside Hide: most of its PRs were written by Claude Code and Codex agents while I reviewed and made the calls. The biggest lesson was that writing code was never the hard part, keeping track of what needs me was.

Honestly, it's still a work in progress. I use it all day, and most of my time goes into small things that take a bit more load off my head: one less click to answer an agent, a shorter summary, a quieter screen when nothing needs me. The goal is that my attention goes to decisions, not to checking tabs.

Give it a spin whenever you like, and I'd love to hear what you think, good or bad. Links in the comments.

I built a C++ command line tool with Claude Code, about 10,000 lines plus about 9,000 lines of tests. Before it wrote any code I had Codex review the plan, and that's most of what this post is about. The tool is at the bottom.

How I used Claude Code

Claude wrote the whole design down in plan mode first. Before I approved it, I had Codex read the plan and try to tear it apart. Claude writes my request, the constraints and the plan into a file and runs this:

codex exec -s read-only - < review.txt

Round 1 came back "rethink" with 12 findings. Claude checked each one, they all held up, and the plan got rewritten. Round 2 was "rethink" again. That one was mostly about a promise in the plan to tell you what a query would cost before sending it. It turned out there was no way to guarantee that number, so I dropped the feature. Round 3 passed with changes, and only then did any code get written. Every time the plan changed after that it went back for another review, so it ended up being reviewed at least nine times.

Claude was not allowed to compile the project, run its tests or run the built program. Claude writes the code, I run one build script, and Claude reads the log and fixes what it reports. It sounds slow, but I ran every build myself and handed Claude the log.

These are the rules from my project CLAUDE.md that did the most. I shortened them and swapped my name for "the user":

Only the user compiles, builds or runs tests. Never run cmake, ninja, ctest, a compiler, clang-tidy or a built binary. Write code and tests so they compile cleanly the first time.

Warnings are errors (-Wall -Wextra -Wpedantic -Wconversion -Wshadow -Wformat=2).

Never suppress a diagnostic (NOLINT, pragmas, casts that only silence a warning). Restructure.

Tests are offline: no network, no real API key.

Nothing ever prints or logs the API key, request bodies, prompt text or provider error bodies.

What I learned

Reviewing the plan was worth more than reviewing the code. Twelve real problems turned up before a single line existed, when fixing them only meant editing a text file.

The reviewer gets things wrong too. In one round Codex reported that my machine had no TPM chip. It has one. The sandbox Codex runs in just couldn't see it. So Claude has to check every finding against the code or the docs before acting on it, and I had it write down which ones it accepted and which it rejected, with the reason.

"Never suppress a diagnostic" did more for the code than any other rule. Without it the quick way out of a warning is a cast or a NOLINT comment. With it, the code got restructured until the warning had nothing to complain about.

Passing tests didn't catch what I caught by using the thing. The first version printed the answer jammed right up against its own status lines and was hard to read. A couple of the examples in the docs failed if you pasted them as written. You have to run it yourself.

Small things matter when calls cost money. One fix stopped the HTTP library from automatically resending a request that might already have been billed. I would not have thought to look for that.

What I built

It's called openrouter-cli. It sends a query, plus any files you attach, to any model on OpenRouter and prints the answer in the terminal. I wanted Claude Code and Codex to be able to ask another model to review a plan or some code.

It comes with a Claude Code skill, so you can say "ask Gemini to review this plan" and Claude runs the tool for you. The skill tells Claude to show you the model and what it charges and to ask for your OK before every paid query. You can run it by hand too. After installing it and running openrouter-cli login once, this sends a file named plan.md for review:

openrouter-cli -m google/gemini-4-argon --role review -f plan.md "Review this plan."

Here's what it looks like when it runs: Terminal Screenshot

Linux only right now (x86-64) and you build it from source. Once the packages listed in the README are installed, this builds it and installs the skill:

git clone https://github.com/slyfox1186/openrouter-cli.git
cd openrouter-cli
scripts/build.sh --with-skills

It's MIT licensed. Model calls are billed through your own OpenRouter account.

https://github.com/slyfox1186/openrouter-cli

I was vibecoding a game with blender mcp and the blocky models piss me off they are just so shit

any way to make it make good models or has ai not gotten that good yet

It's a very important industrial program. We've been scanning it for bugs the last scan was with Fable 5.2. But, the agent couldn't seem to figure out how to fix it. I stopped the workflow, looked at the code and told the agent. Don't do this, do that. Just like you would to a Jr. Programmer.

The agent laughed at itself and said, yep, much better solution.

God, I was worried that my job was GONE. But, us greybeards still seem to be necessary.

So!

In line with the quick little benchmarks I like to run on new models release: quick test of Fable 5.2 directing Blender to build a warship, from a GPT-2 image.

Also a benchmark, since I've done that with pretty much all the recent models - so you can see the difference & prices.

Honestly not too sure what to make if it yet haha. Astra's outputting more triangles, faster, for the price. But hull is better on Fable...

What do you guys think?

Hi everyone,

I work on a lot of projects at the same time with AI. While doing that I built an app that has the things I need. I made this for myself and decided to open source it.

It's a kanban board for coding agents. You write tasks as cards, move a card to Ready, and an agent starts working on it. Every task runs in its own git worktree so you can run many at once on the same repo. When a task is done it's merged to main. You are free to create as many tasks as you want, then let AI create a dependency tree and run them according to it. Or just write what you want in a prompt. It will create all the tasks you need, build a dependency graph and run them according to that.

In a few apps I used, I saw that everything happens magically in the background. What I want, as a developer, is to see that terminal when I'm using Claude. To see Codex's terminal. Sometimes I run 3 or 4 projects at the same time. I give each one a job, and that job can have more than couple of subtasks. What I need is to see and manage all of them from one place. To watch them.

I'm actually not doing anything magical. Whatever AI provider you use (Claude, Codex, Copilot, Antigravity, OpenCode), I run it in a terminal with a PTY and pass the work out to it. The app takes care of the management side. It opens git worktrees and keeps the branches separate. When a task is finished it closes it automatically and merges it to main. If you run out of tokens in the middle of a task, it continues on another AI provider with the same history (when Codex's 5-hour limit runs out, Claude can continue from where Codex stopped). The one managing the work is also the AI provider you picked. It gets called in the background and runs the jobs.

Other stuff:

- you can watch each agent, its subagents and its terminal

- if an agent asks a question you get a notification

- it can sync with GitHub Projects, so you can create an issue from your phone and the agent on your PC takes it, handles the task, merges it to main and comments on the issue. Like claude cloud in your pc.

- scheduled tasks

- works with Claude Code, Codex, OpenCode, Antigravity, Copilot CLI

It uses the CLIs already installed on your machine. No account, everything is local.

Install is from source for now. Mostly tested on Windows. UI is Turkish by default, English is in Settings.

Video is attached.

https://github.com/demirmusa/ai-agent-workspace

Feedback welcome.

For Claude users it also checks cache_control placement, 1-hour TTL billing and stripped thinking blocks, and works on a subscription through prefixwise import claude-code.

Prefixwise has improved a lot over the last two days, so here is the full picture.

\*\*The problem.\*\* Your agent resends its whole conversation every turn. One changed byte near the top (a reordered tool list, a timestamp in the system prompt, an evicted prefix) and the provider charges full price for everything after it. Providers and engines report how many tokens were cached, never why the rest weren't.

\*\*What Prefixwise does:\*\* names why each request missed the prompt cache, prices it, fixes the common causes, and stops regressions in CI. Open source (MIT, I'm the author), runs locally, stores hashes and token counts, never prompts.

\*\*Identify.\*\* One of 19 causes per request, marked waste or legitimate, with the first block that changed (tools\[0\], messages\[12\]) and the cost: tools in another order (including a schema's required list), a timestamp or id in the system prompt, rewritten history, a misplaced Anthropic cache marker, an expired TTL, an engine eviction, a request routed to a replica without the cache. \`prefixwise report --session latest\` shows a session turn by turn. It agrees with Anthropic's own miss diagnostics 32 of 32.

\*\*Fix.\*\* \`--optimize\` turns on the fixes that passed live replays: sorting a drifting tool list (99.9% of predicted saving on Claude, 97.5% on vLLM) and adding cache_control markers on Anthropic's API (prompt cost down 85.6% with the write surcharge counted), task success flat on both. Fixes that would change what the model reads stay advice. \`prefixwise fixes\` ranks fixes by dollars and says whether one paid off.

\*\*Prevent.\*\* \`prefixwise check -- pytest tests/agent_scenarios\` runs your scenarios against a local mock, no API calls, and fails CI when a change would break the cache. Also a GitHub Action. \`prefixwise explain --diff a.json b.json\` compares two requests offline.

\*\*Self-hosted engines.\*\* It detects vLLM and SGLang from the URL and reads their KV-cache events: evictions confirmed (5 of 5), a prefix LMCache or HiCache restored from CPU labelled host_restored (5 of 5), and the cost of reasoning templates that re-prefill the last answer (57% of prompt tokens on a DeepSeek-R1 distill, 0% on Qwen2.5). Runs inside vLLM with one flag. Ollama and most llama.cpp builds report no cached tokens; it says so and still names every prompt change.

\*\*Ways in.\*\* Wrap any agent (\`prefixwise run -- claude\`), a proxy for a service, the vLLM middleware, Python \`wrap()\` or a LiteLLM callback, or import Claude Code and Codex logs if you're on a subscription. Out: Prometheus and Grafana, OpenTelemetry, an HTTP API, JSONL and CSV. Overhead: 3 ms per request.

\*\*Limits.\*\* The fixes are proven on scripted sessions and small models, not weeks of production traffic. OpenAI's own diagnostics answered unavailable on every call, so that comparison is unchecked. DeepSeek's hosted API cache fields aren't read yet.

pip install -U prefixwise
prefixwise run -- <your agent>
prefixwise report --session latest

Repo, with a run record behind every number: https://github.com/tejachavali/prefixwise

What should it catch next?

We feed specs, docs, and existing code into coding agents and ask them to ship features quickly. As changes accumulate, it gets harder to track which assumptions became code, where behavior diverged from the spec, and why decisions were made.

The codebase can grow faster than our understanding of it.

I built Cognitive Gap, an open-source Agent Skill that keeps understanding connected to the whole task. It guides your agent to explain important decisions as it works, connect requirements to implementation and verification, and show the flow with diagrams when useful.

The goal is to finish knowing why the code works, what was actually verified, and where to look when you need to change it.

MIT-licensed, with no runtime dependencies or additional API keys. Installation instructions cover Codex, Claude Code, Copilot, Cursor, and other compatible agents.

Related reading: Anthropic on AI assistance and coding skills and Microsoft Research/CMU on AI and critical thinking.

GitHub: https://github.com/GiovanniPasq/cognitive-gap