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What Good AI Projects Look Like

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Clay Campbell, Founder — Seawolf AI


If it doesn’t change how people work, it’s not a good project.


1. Measurable Outcome

  • Clear before/after metrics
  • Time saved, cost reduced, quality improved
  • Business value, not just technical novelty

2. Embedded in Workflows

  • Built where the work happens
  • Integrated with existing tools and systems
  • Accessible to the actual users, not just engineers

3. Human + AI Co-Ownership

  • AI doesn’t replace the team — it upgrades them
  • Humans stay in the loop for critical decisions
  • Trust is earned through transparency and iteration

4. It Ships — Then It Scales

  • MVP in weeks, not quarters
  • Real usage, real feedback
  • Scale comes after proving value

Why It Matters

You don’t need more AI projects. You need more AI outcomes.