My main takeaway is that skills are software, and the same rules apply. The things that make a bad skill also make a bad software component, eg. being badly scoped. "Should we factor this out" has become "Should we make a skill for this". Same stuff, different form factor
Announcing Codex.
A new product from OpenAI that moves beyond coding, into cooking. We were already cooking before, but now *you* can cook too ... with Codex. It is powered by the same technology as our other Codex products. You can just cook things.
@rseroter@_philschmid This is excellent. It's a bit buried but I especially love the point about skill retirement. Skill bloat is coming :) A couple others have mentioned it but we genuinely do quite good plug-and-play skill evals at Tessl. Check out this one for example https://t.co/thBXTNd1rr
Did you know that you can call agent skills *from* other agent skills? 😵💫 I wrote about this & other fun things you can do with skills here: https://t.co/unADexq3wv
@nonils@tessl_io Great write up. I completely agree with your assessment. Admittedly I took the scenic route to get there over the past year, but yeah, the up-front design-heavy process didn't make sense pre-LLMs, and doesn't make sense post-LLMs either. We're embracing this at @tessl_io too!
@aruiz_tagle@chaisoyum@kindabored@MickyAbir@_opencv_ Tbf though, models are great at optimizing for those success markers, eg “cheating” on tests. “Code that works” is a really hard thing to evaluate at scale
There’s a pattern with LLM dev tools:
First few tries? Magic.
Then you hit the edges: the LLM guesses, hallucinates, ignores your tools, blows through tokens… and the magic fades fast.
@macebake shares what she learned building an MCP server for a CLI tool.
MCPs shine when the user already knows what’s possible. But for new users? The limits show up quick.
Check out the article for pitfalls + practical tips 👇
https://t.co/uZIGGVqjYE
#AINativeDev #ClaudeCode #MCP
I wrote about some lessons learned building an MCP server... I imagine this will feel silly, for one reason or another, in a year's time.
https://t.co/7guWjd5SIy