ai-agent-builder

# AI Agent Builder Structured framework for building AI agents that work in production. Based on the Storm & Storm methodology. ## When to Use - Designing a new AI agent from scratch - Planning architecture for an automated workflow - Reviewing or improving an existing agent's design - Teaching someone how to build agents ## The 8-Step Process Follow these steps in order. Each step has a clear goal and concrete deliverables. ### Step 1: Choose a Task Pick ONE painful, repeating workflow. Not "AI in general." - Must be repeatable (weekly+), follow steps, have clear I/O - Define success: "Given X, the agent should output Y so that Z happens." ### Step 2: Map the Steps Break the task into 4–7 steps: INPUT → ACTIONS → DECISION → OUTPUT - Classify each step: ⚖️ pure rules | 📖 heavy reading/writing | 🎯 judgement calls - Choose infrastructure (no-code vs dev-friendly) - You need: strong model + tool calling + basic logs ### Step 3: Specify Inputs, Outputs & Tools Treat the agent like an API, not a chatbot. - Define required input fields (text, file, URL, ID) - Define structured outputs (JSON/template the system can trust) - Attach tools: data (search/DB/CRM), action (email/Slack/tasks), orchestration (schedulers/webhooks/queues) ### Step 4: Write the System Prompt Create a clear role with: role definition, boundaries, style, 1–2 example conversations. - Use ReAct pattern: observe → think → act → reflect ### Step 5: Add Memory Three layers: conversation state, task memory, knowledge memory (vector store/file search). - Key question: "What does this agent need to remember for the next step to be smarter?" ### Step 6: Add Safeguards Gate high-risk actions (email, data changes, money) behind human approval. - Rules: never invent IDs, ask when ambiguous - Log every tool call and decision for audit ### Step 7: Build the Interface Match to where users work: chat, Slack command, button in app, or web form. ### Step 8: Test For each real example: watch the trace, score correctness + efficiency + time saved. - Tighten prompts/tools/rules where it fails. Iterate. ## Detailed Reference For expanded details on each step, including selection criteria, classification examples, tool categories, memory layer patterns, and a pre-launch checklist: → Read [references/guide.md](references/guide.md) ## Output Format When using this framework to design an agent, produce a design document covering: ``` # Agent Design: [Name] ## Task & Success Criteria [Step 1 output] ## Step Map [Step 2 output — numbered steps with classifications] ## I/O Specification [Step 3 output — inputs, outputs, tools] ## System Prompt [Step 4 output — the actual prompt] ## Memory Architecture [Step 5 output — which layers, what's stored] ## Safeguards [Step 6 output — gated actions, rules, logging] ## Interface [Step 7 output — chosen interface and why] ## Test Plan [Step 8 output — example inputs, expected outputs, scoring criteria] ```