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Dogfooding with Rapid Iteration for Agent Improvement NEW

Problem

Developing effective AI agents requires understanding real-world usage and quickly identifying areas for improvement. External feedback loops can be slow, and simulated environments may not capture all nuances.

Solution

The development team extensively uses their own AI agent product ("dogfooding") for their daily software development tasks. This provides:

  1. Direct, Immediate Feedback: Developers encounter the agent's strengths and weaknesses firsthand.
  2. Real-World Problem Solving: The agent is tested on actual, complex development problems faced by the team.
  3. Internal Experimentation: The team can quickly try out new agent features or modifications on themselves.
  4. Rapid Iteration: Shortcomings identified through dogfooding can be rapidly addressed and new features prototyped and validated internally before wider release.
  5. Honest Assessment: The team can be brutally honest about a feature's utility if they themselves don't find it useful, leading to quick pivots or discarding ineffective ideas.

This creates a tight, high-velocity feedback loop where the agent is continuously improved based on the practical needs and experiences of its own creators.

How to use it

  • Encourage all members of the agent development team to use the agent as their primary tool for relevant tasks.
  • Establish channels for easily reporting issues or suggesting improvements based on internal use.
  • Prioritize fixing pain points experienced by the internal team.

References

  • Lukas Möller (Cursor) at 0:04:25: "I think Cursor is very much driven by kind of solving our own problems and kind of figuring out where we struggle solving problems and making Cursor better...experimenting a lot."
  • Aman Sanger (Cursor) at 0:04:55: "...that's how we're able to move really quickly and building new features and then throwing away things that clearly don't work because we we can be really honest to ourselves of whether we find it useful. And then not have to ship it out to users... it just speeds up the iteration loop for for building features."