Intent-driven development: How to guide agents from idea to implementation

Intent-driven development (IDD) is an AI-assisted software development approach that keeps a team’s desired outcomes, constraints, preserved behaviors, and success criteria explicit throughout planning, implementation, and validation, allowing agents flexibility in how they achieve a result without losing alignment with product goals. It complements test-driven development, behavior-driven development, and specification-driven development by treating tests, scenarios, specifications, and plans as evolving ways to carry a more persistent underlying intent. A typical workflow moves from defining intent and supplying relevant system context to creating a plan, implementing iteratively, validating with appropriate evidence, and refining either code, technical specifications, or ambiguous requirements when failures occur. IDD can fail when requirements are unclear, agents lack visibility into dependencies and system context, or validation does not measure the qualities that matter, making human judgment necessary for unresolved product decisions and qualitative assessments. The discussion presents CircleCI tools as support for this feedback loop, with Chunk sidecars enabling pre-push agent validation, CI providing broader shared-system checks, and the CircleCI CLI or MCP integrations returning pipeline failures to agents so they can revise and revalidate their work.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.