Do people think https://github.com/coracle-social/pomade is a bad idea, or do you just not know about it? It enables login with email and email-based recovery for any nostr app. Keys are stored in a multisig quorum distributed across several parties. It's resilient to custodians going offline via m of n thresholds.

Just discovered this classic: "Help, Sarah, I don't know what to do" 😂

"Excessive automation" due to AI hype is creating a massive pan-market opportunity for startups prepared to come in and pick up the pieces.

The Dead Economy Theory

We can laugh at them but we have to take this seriously

Is Opus 4.8 much dumber than it was yesterday?

Ways I've tried to use LLMs for coding: - Smart autocomplete (dumb, annoying) - Search with poorly articulated queries (really good) - One shot from stupid prompt (random result) - One shot from better prompt (random result) - One shot from plan (random result) - Archon's research/plan/implement with sub-agents (100k LOC broken codebase) - Focused, directed feature implementation (convoluted logic, broken UI) - Focused easy bugfix (mixed results, sometimes works) - Focused difficult bugfix (burns tokens, no ability to debug) - Upgrade dependencies (hallucinations of old versions, usually broken) - Write tests (instead of dependency injection bad mock design, tautological tests) - Write documentation (stylistically poor, did a decent job with something I wouldn't otherwise have done though) - Fix linting errors (useful in a language I don't know, otherwise too slow/expensive to be better than doing it by hand) - Spec-driven development (ended up maintaining the code myself, asked LLM to update the spec) - Generate code in a well-defined context against an API/language I don't know (very helpful if I review/edit it) - Write a plan for me which I implement manually (fails to get design decisions right) - Write boring functions that I stubbed out or just called (works pretty well given enough context) - Help me sanity check plans/implementations by finding edge cases (pretty good, isolated work which I can ignore) So far: LLMs are good for certain categories of search, simple tasks with sufficient context, providing context that I lack (read the docs for me, bringing in skills I lack, helping me think things through). I remember a year ago people saying LLMs were most helpful to sharpen your thinking rather than think for you, but the draw of generating tons of code without thinking was so strong I didn't really see that for a long time. Overall, the net result for me has been that I have moved slower, done worse work, and gotten dumber. But I am slowly coming to a place where I can maybe start using these tools correctly.

My daily experience on nostr: - open coracle - see stupid take on nostr development/grants/specs - write a response explaining how stupid the take is - delete it