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AGENTIC ENGINEERING

Give coding agents a bounded engineering context.

BOUND is not an AI-only methodology. AI agents are contributors operating inside human-defined responsibility boundaries, contracts, acceptance criteria, and verification controls.

The problem

Parallel agents can produce locally reasonable implementations while diverging on shared assumptions about schemas, errors, ownership, timing, retries, compatibility, or state. Local build success does not establish system-level conformance.

Bounded execution

A bounded agent context should specify the objective, owning boundary, allowed change surface, governing contracts, and acceptance evidence.

Boundarywhat the agent owns
Contractwhat neighbours rely on
Briefexecution context
Toolsauthorized actions
Verifyevidence

Human accountability

Agents can accelerate bounded execution and verification. Human responsibility remains explicit for intent, trade-offs, acceptance, and controlled architectural change.

Future integration

The durable integration layer should be machine-readable boundaries, contracts, permissions, and verification. Transport mechanisms such as MCP, tools, skills, or future plugin protocols can evolve independently.

Safety boundary: do not infer authorization merely from technical capability. Agent access to repositories, credentials, network resources, or execution environments should be explicitly scoped and verified.

Agent integration

For a concrete integration model, see bounded agent context and machine-readable agent artifacts and agent security and sandboxing. These are design guidance, not claims of an existing BOUND runtime.