BabyAGI
A minimal 2023 reference implementation of an autonomous task-driven agent — three loops (task creation, prioritization, execution) in ~100 lines of Python.
BabyAGI, released a week after AutoGPT in 2023, demonstrated the agent pattern in ~100 lines. Three loops: a task creation agent that proposes new tasks from results, a prioritization agent that orders the task queue, and an execution agent that completes the top task.
Its value was clarity. Where AutoGPT was opaque, BabyAGI made the agent loop legible enough to teach. Every modern multi-agent system — supervisor-worker, hierarchical, swarm — traces its lineage to the BabyAGI separation of concerns.
Like AutoGPT, BabyAGI is a teaching artifact in 2026. Read the source once, learn the pattern, and build on top of LangGraph or OpenAI Agents SDK in production.
Frequently asked
Why is BabyAGI famous if it is so small?+
Because it showed the agent pattern is small. The breakthrough was conceptual, not engineering — separating task creation, prioritization, and execution into named loops.