Technology Radar
Teams working with coding agents are increasingly adopting spec-driven development workflows. Whether they use a lightweight or opinionated framework, these workflows typically follow a similar flow of spec → plan → implement. The feedback flywheel extends this flow with an additional step focused on continuously improving the coding agent harness.
The approach is similar to retrospectives: teams capture successes and failures during a coding agent session and use them to improve the predictability of future sessions, which compounds over time. It’s a meta-technique where a human on the loop focuses on improving the feedforward controls such as curated shared instructions as well as feedback sensors for coding agents. Our teams have found this effective, as it is analogous to code refactoring. The next level looks more like an agentic feedback flywheel, where, based on accumulated feedback, the agent decides what improvements are necessary. For now, however, teams still need a human-in-the-loop to avoid context rot and noisy feedback that could lead the agent astray.
We suggest using this approach to evaluate the entire coding agent harness as your environment evolves, especially when adopting new models; what worked with one model may not be necessary with the next.
