Thoughts on software engineering, architecture, and building things that matter.
a 1.4b parameter model matching 4b models on reasoning benchmarks. looped language models reuse the same layers multiple times instead of stacking more parameters.
your agent failed at step 9 of a 10-step chain. traditional monitoring shows you a 500 error. what it doesn't show you is why the reasoning drifted at step 4.
llm tooling has moved past simple api wrappers. function calling, mcp servers, structured outputs, agent frameworks. here's what the landscape actually looks like.