Three Loops of AI-Native Engineering

When code gets cheaper, judgment, context, and verification become more valuable.

Product
Engineering

Choosing the right problem.

  • workflows
  • business rules
  • user pain
  • acceptance criteria

Context
Engineering

Giving agents the right information.

  • project memory
  • docs and tickets
  • business context
  • observability evidence

Harness
Engineering

Proving AI-generated work is safe enough.

  • custom agents
  • skills and MCPs
  • evals and observability
  • verification tools