AI, LLMs & agents
Agentic Dev API
Coordinate multi-step work with durable state, bounded authority, and recoverable decisions.

Understand the boundary
Agentic systems add orchestration questions to the basic tool-calling boundary. A workflow may pause for approval, wait for an external job, or resume after a service restart. Represent those transitions explicitly. Keep the proposed plan, accepted actions, observed results, and pending work distinguishable so the system can recover without replaying every side effect.
A practical starting project
Sketch a release-preparation workflow with separate stages for collecting changes, drafting notes, requesting approval, and publishing. Record the revision being released and the approval payload. On resume, check durable state before invoking a publishing tool. A changed release target should invalidate an earlier approval rather than inherit it silently.
Where integrations go wrong
More agents do not automatically create more reliability. Additional handoffs can obscure which actor made a decision and which evidence was available. Start with one orchestrator and narrowly scoped tools, then add parallelism only where tasks are independent. Make failed and cancelled states visible to the user and the operating team.
Review before you ship
- Can the workflow resume safely?
- What invalidates an approval?
- Is each side effect traceable to a request?
Reference for implementation: OpenAI function calling documentation. Check the official reference for the specific version and environment you plan to use. The exercise above is an engineering starting point, not a live DevAPI.com service.
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