Definition: Everything built around an AI model to make it usable and reliable for software development: the context feeding, tooling, constraints, verification loops, and orchestration that wrap the raw model. Capability in AI-based development comes from the model plus this harness, not from the model alone.
So what? It reframes AI-assisted development as a systems problem rather than a question of which model to pick, putting the emphasis on the scaffolding around the model as the main source of reliable, useful output.
Example: A coding agent set up to fix a failing test, where the model does the reasoning but the harness supplies the relevant files and test output, enforces the project's coding standards, runs the test suite after each change, and gates risky actions like commits behind human approval.
See also: Harness Engineering https://www.ministryoftesting.com/software-testing-glossary/harness-engineering
So what? It reframes AI-assisted development as a systems problem rather than a question of which model to pick, putting the emphasis on the scaffolding around the model as the main source of reliable, useful output.
Example: A coding agent set up to fix a failing test, where the model does the reasoning but the harness supplies the relevant files and test output, enforces the project's coding standards, runs the test suite after each change, and gates risky actions like commits behind human approval.
See also: Harness Engineering https://www.ministryoftesting.com/software-testing-glossary/harness-engineering
