• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
• determinism — Whether the same input reliably produces the same output — something LLM systems mostly lack, which changes how you test and debug them.
• context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.

Retry-happy agents double-charge customers without idempotency keys and status lookups. Also: context that can influence an action is state, so it needs invalidation and provenance, and approvals must bind to an action, actor and expiry.

• videoBuilding uReview, Uber’s Multi-Agent Code Review Engine — Will Bond & Ameya Ketkar, Uber
• videoAI Evals for Cross-Functional Teams — Nachiket Paranjape & Swaroop Chitlur Haridas, DoorDash
• videoProductionizing LLM Gateways: Architecture, Tradeoffs and Hard Lessons — Kanish Manuja, Twilio
• videoHow to avoid disaster when vibe-coding a billing engine — Andrew Garvin, Stripe

• videoBuilding Agents Is Trivial Now, Context Is the Next Frontier — Jeff Ng, UnblockedAI Engineer
• videoCoding Agents Don't Scale Themselves. Neither Do Your Teams. — Patrick Debois, TesslAI Engineer
• videoUnlock Agent Autonomy: The Runtime for AI-Native Systems — Tushar Jain, DockerAI Engineer

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