I'm working on test scenarios (in natural language) after defining my initial task to keep my mind on the same topic. Edge cases to test, implementation details to check, log traces where it makes sense,... Basically crystalizing my vision of what the code should do and look like, so I can check against the implemented version.
Readit Newscranium commented on Ask HN: Do you struggle with flow state when using AI assisted coding tools? · Posted by u/rasca
cranium commented on Genie 3: A new frontier for world models deepmind.google/discover/... · Posted by u/bradleyg223
I find the model very impressive, but how could it be used in the wild? They mention robots (maybe to test them cheaply in completely different environments?), but I don't see the use in games except during development to generate ideas/assets.
What is an “antigenic AI” or “antigenic workflow” in this context?
It’s used so consistently that I’m not sure if it’s just careless editing or if it’s something new I don’t know about.
I guess it should be "agentic" but it's used so many times it can't really be a typo...
cranium commented on I'm switching to Python and actually liking it cesarsotovalero.net/blog/... · Posted by u/cesarsotovalero
I always forget this syntax exists. When was this introduced?
The Walrus operator! Introduced in Python 3.8 according to the PEP 572.
Really nice to combine 1) checking if something exists and 2) act on it
I'd be happy to spend my Claude Max tokens during the night so it can "ultrathink" some Pareto improvements to my projects. So far, I've mostly seen lateral moves that rewrites code rather than rearchitecture/design the project.
cranium commented on Opencode: AI coding agent, built for the terminal github.com/sst/opencode... · Posted by u/indigodaddy
Has anyone done a (somewhat) apple-to-apple comparison between opencode and claude code, as they both can use claude pro/max subscription?
I'm curious about how they feel to use and their "performance".
cranium commented on Building a Personal AI Factory john-rush.com/posts/ai-20... · Posted by u/derek
I think the hardest problem in computer science right now may be coming up with an LLM demo that doesn't get called "pretty trivial".
Instead of "pretty trivial", I'd say it's "well-defined and generally understood".
The implicit decisions it had to make were also inconsequential, eg. selection of ASCII chars, color or not, bounds of the domain,...
However, it shows that agents are powerful translators / extractors of general knowledge!
anthro needs to let the creator charge % on top of their usage quota or give points/money to the creator to fix up the incentives here
That's a really good idea! That would handle micropayments that nobody would even bother with (to pay, to process, to receive, ...).
Could even have users select the payment %age or have it set by the contract tier between the app creator and the user (10% for simple user, 20% for pro access with other features, 40% enterprise,...).
As someone who does both, I have to say that the only reason I am writing MCP stuff is that all the user-side tools seem to support it.
And the moment we, as an industry, settle on something sane, I will rip out the whole thing and adopt that, because MCP brings _nothing_ to the table that I could not do with a "proper" API using completely standard tooling.
Then again, I have run the whole gamut since the EDI and Enterprise JavaBeans era, XML-RPC, etc. - the works. Our industry loves creating new API surfaces and semantics without a) properly designing them from the start and b) aiming for a level of re-use that is neither pathological nor wasteful of developer time, so I'm used to people from "new fields of computing" ignoring established wisdom and rolling their own API "conventions".
But, again, the instant something less contrived and more integratable comes along, I will gleefully rm -rf the entire thing and move over, and many people in the enterprise field feel exactly the same - we've spent decades builting API management solutions with proper controls, and MCP bodges all of that up.
Looks like the GraphQL beginnings, it feels fresh now and the AI products kind of nudge everything that way but fundamentally the main point is being able to package an API into a standard format, with documented endpoints, support for authentication, and different transports.
Nothing that couldn't be solved by a well designed REST API with Swagger documentation (and authentication, and websockets), but by being the same interface for all APIs it reduces the burden on the LLM.