Lets Build An Agent from Scratch — Kam Lasater
Feb 22, 2025 · 19:29
Kam Lasater demonstrates that an AI agent is simply an LLM paired with memory, planning, tools, and a while loop, and shows how to build one from scratch in incremental steps. He starts with a basic LLM call (step 0), adds a condition using an LLM as judge to check if an answer is complete (step 1), then incorporates a tool for web search via SERP AI (step 2). After refactoring for parallel tool calls (step 3), he introduces a to-do list for planning and tracking progress, along with a browse-web tool (step 4). The agent uses a to-do list to plan, execute tasks like searching and browsing, and then checks completion via LLM as judge. Lasater illustrates with examples: finding the average wind speed of a swallow, buying a hoodie near Times Square, and planning a date in Ardmore. He emphasizes that the simplest agent emerges naturally from combining these components, and encourages running and breaking the provided code.
