The Hidden Layer Every AI Agent Runs On13 insights · See all
- Modeling agents as step functions fits naturally because agents loop through LLM calls and tool invocations and treating each interaction as a step preserves state, enables deterministic retries, and makes orchestration straightforward.
Modeling agents as step functions fits naturally because agents loop through LLM calls and tool invocations and treating each interaction as a step preserves state, enables deterministic retries, and makes orchestration straightforward.
- If many teams share the same workflow problem it is usually better to consume a specialized execution provider because building durable, high-throughput, observable orchestration demands scale expertise and heavy engineering that distract product teams from differentiation.
If many teams share the same workflow problem it is usually better to consume a specialized execution provider because building durable, high-throughput, observable orchestration demands scale expertise and heavy engineering that distract product teams from differentiation.
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