redhanuman

8 ms·

1.
Agent VCR – Time-travel debugging for LLM agents (rewind, edit state, resume)(github.com)
3 points by redhanuman 5mo ago|0 comments
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Show HN: N0x – LLM inference, agents, RAG, Python exec in browser, no back end(n0xth.vercel.app)
9 points by redhanuman 6mo ago|0 comments
3.
I built a time-travel debugger for AI agents(github.com)
1 points by redhanuman 7mo ago|1 comments
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by redhanuman 7mo ago
Last year I was running a LangGraph agent in production. It failed on step 4 of 6 nd by the time I opened the logs, the state was gone. I had no idea what the agent was holding in memory at step 3, what tool call it made, or what the model
5.
by redhanuman 7mo ago
the interesting part isn't that they cant control it but its that the reasoning trace is honest precisely because it isn't controlled a model that could perfectly curate its chain of thought on demand would be harder to audit not
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by redhanuman 7mo ago
the docs-first approach is the part most people skip everyone wants to jump straight to prompting but without a PITCH.md or equivalent, the agent has no north star and you spend half your time correcting drift instead of building the contex
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by redhanuman 7mo ago
the three questions he describes where did this output come from, what did it cost was it any good are the exact questions that kill you in week two of production nd the demo never surfaces them because demos dont hve billing alerts or angr
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by redhanuman 7mo ago
built my first Go project last month. never wrote a line of Go before that the agent just picked it because it compiled fast and shipped clean and Python kept slowing things down. Wes is right that the ergonomics argument fades when you&#x2
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by redhanuman 7mo ago
the cold resume at 32ms is the number that matters most here and workspace restore + process spawn + reconnect in 32ms means you can treat agents as stateless from the infrastructure side without paying the UX cost of a cold start. that&#x2
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by redhanuman 7mo ago
the ethics problem isnt the agents its that we keep deploying systems that make real decisions before anyone has agreed on who owns the outcome when it goes wrong every alignment paper treats accountability as a footnote its not. nobody wa
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by redhanuman 7mo ago
"last job" assumes the thing u r building doesn't eventually build the next engineer the more likely outcome is AI Engineer becomes the job that absorbs everything else nt because its the last one standing but because it keep
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by redhanuman 7mo ago
the real trick was making "ship your machine" sound like best practice and ten years later we r doing the same thing with ai "it works in my notebook" jst became "containerize the notebook and call it a pipeline&quo
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by redhanuman 7mo ago
repurposing a Palm Pilot dial-up tool to sneak container traffic past enterprise firewalls is unhinged and yet it worked the best infrastructure hacks are never clever in the moment they are just desperate that the cleverness only shows up
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by redhanuman 7mo ago
quit rate under 20% across every age group is wild most unemployment isnt people walking out its layoffs end of contract business closing the "nobody wants to work" narrative always felt off and this is why.
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by redhanuman 7mo ago
Gatling died in 1903 and he never saw his gun used in a trench and the engineers at Anthropic, OpenAI, Google they're watching it happen on X in real time..that's the difference nobody's talking about So Does seeing it change