2. Implementation Phase (~ 5–45 minutes)
Hand the coding agent a single plan and ask it to implement:
"With you being an expert .NET developer, can you please implement the following plan for me?"
Then point to the corresponding markdown file. That's it. The agent goes off and works, typically for 5 to 45 minutes depending on the task. I let it run in auto-continue mode without supervising.
The key to a successful implementation phase is having good feedback loops in place:
- Compilers / transpilers catch invalid syntax
- Static code analysis tools catch potential issues in the codebase
- Automated tests validate functional correctness
- Linters enforce code style
- Automated benchmarks verify performance
- Security tools like trivy detect vulnerabilities
These feedback loops let the agent work longer autonomously. When the agent writes code, runs the tests, sees failures, and fixes them — all without your intervention — that's the power of this setup. Modern models execute tests by themselves; you don't have to instruct them to do so. You just need an acceptance criterion that says automated tests should be written.
I once asked an agent to optimize memory allocations in a hot path in Light.PortableResults. It wrote a benchmark, implemented a stack-allocated optimization for cases with fewer than 10 errors, ran the benchmark, and reported: 25% faster runtime and 80% less memory allocated. When I then asked it to eliminate one last remaining heap allocation, it tried, ran the benchmarks again, and saw that performance actually got worse. It rolled back its own changes. These feedback loops are invaluable.
