Coding Agents Are Only as Good as the Signals You Feed Them

Read this article on Signadot . The industry has spent the last few years optimizing AI agents’ code-generation capabilities. The focus has been on expanding context windows, fine-tuning models on repository-specific data, and developing complex prompting strategies. This has undoubtedly produced more capable coding agents. However, for most teams, that code-generation capability has not translated into significant gains in productivity. Most engineering teams are stuck in a manual workflow. The agent generates the code, tests it locally, and submits a PR to the developer for review. Deploying the code, validating that it works, and feeding back any integration issues to the agent all happen at human pace. This workflow puts a hard ceiling on the productivity gains that agents can deliver by making developers into a validation bottleneck. But some companies are enabling real autonomy for their agents and seeing the productivity gains that AI promises. Organizations like Stripe, Ramp, a