Spec-Driven Development With AI Agents: How Checkpoints and Handoffs Tame Long Features

AI coding agents perform well on small, scoped tasks but struggle with large, multi-day features due to context window limits, lost session history, and unmanageable code diffs. A structured workflow built around a constitution, a frozen spec-driven plan, and explicit checkpoints addresses these as process failures rather than model shortcomings. The agent works through small, review-sized groups of tasks at a time, stopping at each checkpoint to pass automated gates and document any deviations from the plan. A two-stage review follows, where a separate reviewer agent first receives a written brief from the coding agent before analyzing the diff, keeping each review to a few hundred lines of coherent changes. This approach keeps complexity bounded, catches drift early, and ensures that a 'done' status is backed by verifiable evidence rather than an agent's unreviewed output.