Applying 12-Factor Principles to Coding Agent SDKs:🦄 #40
Автор: Boundary
Загружено: 2026-01-19
Просмотров: 1591
In this episode, we dive into why AI agents often feel fragile and what it takes to make them reliable in real-world systems. The discussion covers state and memory, planning vs execution, long-horizon tasks, failure recovery, and the tooling needed to ship agents into production.A practical conversation for anyone building or deploying AI agents beyond simple demos.
Chapters:
00:00:00 Intro
00:04:29 Agent Fragility
00:08:51 State & Memory
00:13:59 Planning vs Doing
00:20:20 Long Tasks
00:26:13 Failure Recovery
00:33:53 Tooling
00:42:08 Production Lessons
00:51:36 Wrap-Up
Check out our github: https://www.github.com/boundaryml/baml
AI That Works repo: https://github.com/ai-that-works/ai-t...
Socials:
X: https://x.com/boundaryml
Discord: / discord
LinkedIn: / boundaryml
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