Long-form essays on agentic systems, AI coding workflows, evaluation, and the engineering judgment behind reliable AI work.
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A first-principles architecture study of a production-grade AI pull-request review agent: specialist reasoners, grounded context, orchestration, memory, evaluation, observability, and human review.
Read article ->Reliable AI agents need more than longer context windows. They need explicit state, graphs, task DAGs, validators, proof logs, and feedback loops around the model.
Read article ->An AI coding plan is not a pile of prompts. It is a small machine that writes the to-do list, delegates work, checks results, and records what got done.
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