DESIGN RELIABLE ACTION

AI Agents Roadmap

A grounded path through tool use, workflows, memory, planning, evaluation, safety boundaries, and production agent systems.

THIS PATH IS FORDevelopers and product teams building assistants, research workflows, coding tools, operations automation, or multi-step AI systems.
THE ROADMAP

Start with deterministic software and add model autonomy only where it improves the result. Many reliable agent systems are carefully designed workflows with explicit tools, bounded choices, and strong feedback loops.

  1. 01

    Start with workflows

    Chain model calls and software tools in a visible, testable sequence before introducing open-ended planning.

  2. 02

    Design safe tools

    Give every tool a narrow contract, validate its arguments, limit authority, and require confirmation for consequential actions.

  3. 03

    Manage context

    Separate working memory, durable knowledge, user preferences, and retrieved evidence. Treat all external content as untrusted input.

  4. 04

    Evaluate trajectories

    Test not only the final answer but the sequence of decisions, tool calls, recovery behavior, latency, cost, and safety.

KEEP LEARNING
AI for Beginners→Machine Learning Roadmap→Generative AI Roadmap→