Methodologies to Machines
Every great project balances two forces: meticulous planning and adaptive agility. This same fundamental tension defines the minds of our most advanced AIs. Explore the parallel worlds of project management and AI architecture to understand how we build intelligent systems.
The World of Planning
🏛️ The Waterfall Model
A traditional, linear approach where a project is broken into distinct, sequential phases. Each phase must be fully completed before the next begins, emphasizing upfront planning and comprehensive documentation.
🧠 The Planner-Executor AI
An AI architecture that mirrors Waterfall. A powerful "Planner" LLM first creates a complete, multi-step plan. Then, a simpler "Executor" carries out each step in sequence, decoupling high-level strategy from low-level action.
The World of Adapting
🌪️ The Agile Methodology
An iterative approach centered on flexibility and customer collaboration. Work is done in short cycles ("sprints"), allowing teams to adapt to change and deliver value continuously based on feedback.
⚡ The ReAct AI
The spirit of Agile in an AI. The agent operates in a tight "Thought-Action-Observation" loop, constantly reasoning, acting, and learning from its environment in real-time. It doesn't follow a grand plan; it discovers the solution.
An Interactive Comparison
How do these AI agent philosophies truly stack up? See their characteristics visualized below. A higher score means the feature is more prominent in that approach.
The Grand Synthesis: Bridging the Worlds
The parallels aren't a coincidence; they reveal a shared logic for solving complex problems. Hover over a core concept below to see how it maps across both domains.
The Developer's Toolkit
These conceptual architectures are brought to life by powerful frameworks. Each offers a different level of abstraction and control for building AI agents.
Which Architecture Is Right For You?
The best architecture depends on the task. Answer the questions below to see a recommendation.