60 Days of Production AI Systems · chapter 6 of 10
Agentic AI Foundations
Outcomes, loops, planning, tools, memory and reflection: what makes an agent more than a prompt.
6 of 6 published
Chapter guide · 6 min readThe hard part of building an agent is not making it act. It is making it stop.The whole chapter in one read. Then go part by part below.- 01
Day 31 · Explainer · 1 min read
Why agents need outcomes, boundaries, and stop conditions
Why agents need clear outcomes, boundaries, budgets, and stop conditions before autonomy.
On the map: Agent - 02
Day 32 · Explainer · 2 min read
Why agent behavior is a loop, not a single prompt
Why reliable agent behavior comes from loop design, not a single clever prompt.
On the map: Agent - 03
Day 33 · Explainer · 1 min read
Why planning reduces wasted AI actions
Why planning matters when actions have cost, risk, or dependencies.
On the map: Agent - 04
Day 34 · Explainer · 2 min read
Why tool access is where AI becomes operational risk
Why giving AI tools means designing permissions, observability, rollback, and approval paths.
On the map: Tools - 05
Day 35 · Explainer · 2 min read
Why agent memory is not one database
Why useful agent memory has to be separated, scoped, and governed.
On the map: Memory - 06
Day 36 · Explainer · 1 min read
Why reflection should change the next action
Why reflection is valuable only when it decides whether to revise, retry, escalate, or stop.
On the map: Agent