Eclipse π retweeted
I am begging @AnthropicAI please add an automated test suite somewhere that ensures Claude Code on the web never blocks me from cloning or interacting with other public repos from within my existing sessions
![Screenshot of a mobile chat interface with a modal sheet sliding up over it. The chat text reads: Release page loaded β 9 binary assets. Now let me download them and explore the repo. Ran a command, read a file > The downloads came back as 195-byte files β likely proxy blocks. Let me check. Ran Inspect failed download content and headers > The modal sheet is titled "Add Repo" with a back arrow, and shows: Error / add_repo: cross-tier adds are not supported in v1: requested "tractordev/wanix" but session already has repos from owner(s) [simonw]. Start a new session with the requested repo as the initial source, or add a repo from the same owner as the existing sources](https://pbs.twimg.com/media/HNfC2anbUAAV0z2.jpg?name=small&format=webp)
ALT Screenshot of a mobile chat interface with a modal sheet sliding up over it. The chat text reads: Release page loaded β 9 binary assets. Now let me download them and explore the repo. Ran a command, read a file > The downloads came back as 195-byte files β likely proxy blocks. Let me check. Ran Inspect failed download content and headers > The modal sheet is titled "Add Repo" with a back arrow, and shows: Error / add_repo: cross-tier adds are not supported in v1: requested "tractordev/wanix" but session already has repos from owner(s) [simonw]. Start a new session with the requested repo as the initial source, or add a repo from the same owner as the existing sources
Eclipse π retweeted
How can an LLM switch between low-, medium-, and high-effort reasoning? And how does an LLM learn to reason more or less?
I put together a βlittleβ article explaining how these effort levels are implemented at inference time and during training.
Eclipse π retweeted
this is cool:
welcome-to-codex.openai.chatβ¦
Eclipse π retweeted
i talk to chatgpt more than i type to it at this point
new voice model really crossed a threshold
Eclipse π retweeted
Claude Fable 5 Max simulates 15s of VHS footage of a TV displaying video of itself in a feedback loop
Introducing GPT-Red
An internal automated red teamer on a mission to find our modelsβ prompt injection vulnerabilities at scale, helping us build stronger defenses before wider deployment.
openai.com/index/unlocking-sβ¦
Eclipse π retweeted
I am hiring a TPM lead for @GoogleAIStudio, the job is to accelerate our progress in every way possible across product, GTM, engineering, and more. If you are AI pilled, high agency, and want to push the frontier in Google DeepMind, consider working with us : )
Eclipse π retweeted
i do love rottweilers
My view of: Fable 5 vs GPT-5.6-Sol. They are not easy models to compare, these are my vibes - take them as you will.
My overall feel is that Fable is a 'wise owl' who is very thoughtful and very well spoken, GPT-5.6-Sol is like a rottweiler who will grab the problem by the throat and not let go until it is done.
In other words, Fable, is a fundamentally smarter model - even at low reasoning it can be very insightful and writes in a clear compelling way. GPT-5.6-Sol on the other hand is extremely diligent, I can give it a list of 8 things to do and you will be sure that they will be done.
Fable feels more arrogant to me, I was both to get it to build a new benchmark for me - 5.6 worked between 6 hours and 2 days (I tried several times) and it came up with very thoroughly tested, working benchmark. Fable came back within 40 minutes (twice) and the benchmark sounded smart, but was ultimately was 'vibe' based slop and since it was Fable's vibes that was doing the judging, it decided that it was good to go (it kept giving Fable 100% score btw).
Some thoughts by category:
UI & App building: Fable will still craft a better UI from scratch, the flow of the app would probably be a bit nicer. But I find that Fable often misses quite key things, which GPT-5.6-Sol doesn't. GPT's Frontend skills are big jump vs previous GPT models, but still not as great overall.
Writing: Fable is better hands down, Sol feels quite difficult to align to what I want to say or explain things to me simply. Though I think the 'Pro' model writes clearer.
Robustness & Reliability: This is where I think GPT-5.6-Sol wins for me hands down. Fable seems to do things of high quality, but I can never relax with it, it always misses something. With 5.6 this just almost never happens.
Other things where I liked GPT-5.6-Sol, but can't compare to Fable directly.
- Video editing is actually working now, it is not completely perfect, but with the right skill/guidance you can just give it 1h footage and it can give you a 5 min highlight clip no problem
- Computer use - getting really rather good, very usable
- Sub agents - it is very fluent at managing sub-agents and speaking to different threads, can help with some new workflows
- Adhering to existing code patterns - I love this, even without asking it would implement something in a way that aligns with you app - major problem for slop generation
- Research - I think it is getting quite a bit better, it still has some bad patterns (e.g being too tactical), but it feels like it is more steerable to be a good researcher
- Multi-day runs - the /goal feature is pretty insane with 5.6-Sol, you can run it for days if you wanted to and it does work. Useful to have another thread or /side to check up on it, but I have some great results with it
- Token efficiency - it is so much more token efficient and faster than 5.5, in reality it is now much faster than Fable too
On the downside, you can feel that Fable is naturally smarter, and I did have some baffling moments with 5.6 when I was getting it to make a fairly simple change in 8 turns - it seemed to get stuck in a dumb stream that was hard to get out of. So it is not AGI, don't get too carried away by the hype.
I have some phenomenal examples that I'm honestly blown away by that I'll share, but as a side anecdote, I have a kind of 'swear meter' which counts how often I'm rude to Codex. In GPT-5.5 era, the % was at around 4-5%, it dropped to 1-2% when I was testing GPT-5.6-Sol and it shot up to 7% when I went back to 5.5 - it was so shocking to go back to 5.5 and experience how much worse it was.
So is GPT-5.6-Sol better than Fable? On pure intelligence - no. But man, I missed it when I just wanted to get sh*t done. It is insanely capable workhorse that you can give any task to and just expect it to be done. No lectures or 'you are absolutely rightisms', nothing is beneath it, if it takes 2 days to do some dirty work, it will do it.
It feels like the first time in a while when we have quite different types of frontier intelligences that benchmark sort of similarly, but feel very different. If you can, you would be probably better off using both and iteratively finding what you'd use Fable or GPT-5.6-Sol for. Perhaps, something like - an architectural discussion with Fable, implementation with 5.6 and docs & comms with Fable.
We audited SWE-Bench Pro, one of the most widely used AI coding benchmarks, and found it no longer reliably measures frontier coding capability.
We find 30% of SWE-Bench Pro tasks to be broken, and are retracting our previous recommendation that the research community use it as a leading coding eval.
openai.com/index/separating-β¦
Eclipse π retweeted
Today we are rolling out some big updates to Managed Agents in the Gemini API:
- support for background tasks
- remote MCP & function calling
- network credential refresh
and you can now get started with Managed agents in the API via the free tier!
teapawt.net/GoogleAIStudio/status/β¦
Eclipse π retweeted
need a model for ocr or vqa? try gemini 3.5 flash. gemini 3.5 flash is faster, cheaper, and more accurate.
Details β
Eclipse π retweeted
grateful to the people that created the idea of america, everyone who built it over the past 250 years, and the people who will carry it forward for the next 250.
most impressive social experiment in history.
Eclipse π retweeted
The most interesting Fable tip I've heard so far is to let the model use its own judgement as much as possible
I told it "For all coding tasks use your judgement to decide an appropriate lower power model and run that in a subagent" and it seems to be saving a lot of tokens
Eclipse π retweeted
going to world cup games is always awesome, but watching the USA win in the USA during USA birthday week was just incredible
Eclipse π retweeted
The @googlehealth API got a CLI! ghealth is an open-source CLI for your Fitbit Air. You can now pull 40 health metrics from the terminal or pipe them straight into your AI agent.
Pull sleep breakdowns and heart rate data into context. Use `--detail` flag on sleep gives you per-stage data (awake, deep, REM), which is useful for spotting patterns week over week.
```
npx skills add Google-Health-API/google-health-cli
ghealth setup
```
Setup takes a few minutes. Wizard handles GCP project, OAuth, scopes.


















