Claude’s API exposes tool use/function calling — the model decides when to call a tool you’ve defined, your code executes it, and the result feeds back into the conversation. That’s the real machinery behind “agentic” workflows, best framed as a plan → act → observe/reflect loop with human-in-the-loop guardrails rather than fully autonomous execution.
The Claude API is Anthropic’s REST API (POST /v1/messages): a messages array plus an optional system prompt go in, a response comes out. On top of that, tool use / function calling lets you define tools via JSON schema; the model decides when to call one, your code executes it, and the result is fed back into the conversation for the model to continue reasoning with. This single mechanism is the underlying machinery for essentially all “agentic” behavior — everything else is built on top of that same call-tool, get-result, keep-reasoning loop.
GitHub Copilot sits at a different layer: inline, context-aware code completion plus chat-based assistance directly in the IDE, rather than an autonomous tool-calling loop.
The useful mental model for an “agentic workflow” is a plan → act → observe/reflect loop: the model plans a step, takes an action (a tool call), observes the result, and decides the next step. The important qualifier is that this should ideally run with human-in-the-loop guardrails — review gates, static analysis, test suites — rather than letting it run fully autonomously end to end.
