n-agentic-harnesses

An AI agent harness standardizes the tool-use architecture by defining solid primitives and boundaries. Explicit boundaries prevent brittle behavior and hidden risks, ensuring multi-step workflows operate safely with clear permission controls.

Design an evaluation plan for multi-step AI workflows by prescribing evaluation-first criteria before building. Establish explicit state tracking, permissions, and testing criteria to ensure the harness meets lean constraints and produces a target architecture with MVP boundaries.

Yes, you can build a lean AI agent architecture as a solo developer. This approach emphasizes solo-dev friendly constraints, guiding phased implementation with MVP boundaries and acceptance criteria to ensure manageable, auditable tool-use architectures.

Structure permissions and observability in AI agents by defining explicit boundaries and solid primitives within the harness layer. This ensures auditable tool-use architectures with clear state management and safe multi-step workflow orchestration.

You should not use a full agentic harness when your AI product lacks clear tool-use requirements or multi-step workflows. Without explicit state and permissions, a complex harness introduces hidden risks rather than providing lean, auditable benefits.