Cognition's CEO highlights five ideal, immediately delegable tasks for AI coding assistants: miscellaneous front-end fixes, version upgrades and migrations, documentation generation, initial incident response, and writing unit tests for existing code.
Before delegating a complex task, use a simple prompt to have a context-aware system generate a more detailed and effective prompt. This "prompt-for-a-prompt" workflow adds necessary detail and structure, significantly improving the agent's success rate and saving rework.
Instead of antisocially typing on a device during meetings, activate ChatGPT's voice mode out loud. This social hack frames the AI as a transparent participant, retrieving information for the entire group and reducing friction for quick lookups without disrupting the conversation.
Integrate AI agents directly into core workflows like Slack and institutionalize them as the "first line of response." By tagging the agent on every new bug, crash, or request, it provides an initial analysis or pull request that humans can then review, edit, or build upon.
Treating AI coding tools like an asynchronous junior engineer, rather than a synchronous pair programmer, sets correct expectations. This allows users to delegate tasks, go to meetings, and check in later, enabling true multi-threading of work without the need to babysit the tool.
Using AI agents in shared Slack channels transforms coding from a solo activity into a collaborative one. Multiple team members can observe the agent's work, provide corrective feedback in the same thread, and collectively guide the task to completion, fostering shared knowledge.
When an agent fails, treat it like an intern. Scrutinize its log of actions to find the specific step where it went wrong (e.g., used the wrong link), then provide a targeted correction. This is far more effective than giving a generic, frustrated re-prompt.