A 7-part AI agents learning path, from basics to building your own harness in 17 steps
blaizedsouza · x · 2026-10-12
sermakarevich published a seven-article learning path on building and running AI agents, written in plain language but grounded in papers and real runs: (1) the layers every agent is made of; (2) six levers that actually move output quality; (3) where the token budget actually goes; (4) how to know if it works via evals; (5) agentic evals that grade what the agent changed, not what it said; (6) scaling from interactive sessions to autonomous fleets; (7) building your own harness in 17 steps — the piece the author argues decides most of the result.
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