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Agentic Patterns

How to actually build an AI agent

An agent is a loop, not an 8-step pipeline. Why the viral infographic shows a parts list — and what the real architecture is.

A parts list is not an architecture

A viral infographic frames agent-building as eight sequential steps. It names real building blocks — prompt, model, tools, memory, evals — but omits the one thing that makes a system agentic at all: the loop. An agent runs a closed cycle until a stop condition is met:

  1. Gather context — prompt, retrieval, state, files, history.
  2. Take action — structured tool call, run code.
  3. Verify — tests, checks, self-critique. On failure, back to step 1.

Two corrections up front

  • Workflow or agent? Decide first. A fixed workflow is often cheaper, safer and faster than full autonomy. Add agency only when the task is open-ended and the cost earns its keep.
  • Evals first, not last. They are the demo-versus-production line. And context engineering — curating what enters the model each turn — is the decisive production discipline for 2025/26.

Read the full guide

Members get the complete reference architecture: the decision gate, the augmented LLM as a building block, five composable workflow patterns (chaining, routing, parallelization, orchestrator–workers, evaluator–optimizer), the four agentic design patterns and the corrected build sequence — plus the extracted tool landscape.

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