Design a Loop is where the discipline of loop engineering lives — designing the iterative perceive-reason-decide-act-verify-recover cycle an AI agent runs on every turn, deliberately, instead of letting one emerge by accident from glue code.
Loop engineering is the discipline of designing the iterative cycle an AI agent runs on every turn: what it perceives, what it believes, what it is allowed to do, how it verifies its own output, and how it recovers when a step fails — before looping back and doing it again.
Every agent that does more than answer one question is already running on a loop, whether anyone designed one or not. Left undesigned, that loop degrades in predictable ways: it retries forever when a tool fails, it drifts as early mistakes compound across iterations, and it can't tell the difference between "done" and "stuck." Loop engineering treats the cycle itself — not the prompt, not the model choice — as the primary thing you design.
A fully engineered agent loop runs through seven stages, then repeats. Miss one, and a specific, predictable failure mode shows up in production.
Both matter. But they operate at different points in the cycle, and the returns on each are not equal in production.
Build A Harness is the open-source tool built for this discipline — a visual canvas that implements all seven loop stages as drawable, composable nodes, and compiles to any major agent framework.
# Two commands, everything local
git clone https://github.com/3IVIS/buildaharness.git && cd buildaharness
./scripts/setup-env.sh && docker compose up
Apache 2.0. Source on GitHub → · buildaharness.com →
The discipline of designing the iterative cycle an AI agent runs on every turn — perceive, reason, decide, act, verify, recover, repeat — instead of letting one emerge by accident. Read the full definition →
Yes — two names for the same discipline, from two angles. Harness engineering emphasizes the constraint structure around the model; loop engineering emphasizes the iterative cycle that structure runs on.
Build A Harness — an open-source visual canvas that implements a fully engineered agent loop as drawable nodes, and compiles to LangGraph, CrewAI, Mastra, or Microsoft Agent Framework. Apache 2.0, runs locally via Docker.
The Loop Engineering page covers the full definition, the loop vs. workflows, loop vs. prompt engineering, and a stage-by-stage breakdown of what breaks without each one.
Build A Harness implements the full seven-stage loop — world model, control state, verification, recovery, and cross-run learning — as drawable, composable nodes. Apache 2.0. Runs locally via Docker.