Been using Windsurf for a few months. The initial speed boost is real. But the overall project velocity hasn't moved much. Here's why:
The raw generation is fast, but the output often requires significant review and correction. It's not just about fixing logic. It's about:
* Context it doesn't have (project-specific patterns, internal libs).
* Drifting from established code style.
* Introducing subtle anti-patterns or security oversights.
You end up spending the time you "saved" on:
* Thoroughly reading through the generated diff.
* Running additional tests to be sure.
* Correcting the approach in follow-up prompts.
Example: Asked for a GitHub Actions workflow to cache dependencies. It generated this:
```yaml
- name: Cache dependencies
uses: actions/cache@v3
with:
path: node_modules
key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }}
```
Looks okay, but our project uses `pnpm` and a specific `pnpm-store` path. Had to stop, correct it, and verify the cache key was correct for our setup. The "time saved" on writing the initial YAML was spent on the review and fix.
The bottleneck shifts from *writing* code to *reviewing and debugging* AI-generated code. If your review process is already rigorous, the net gain can be near zero.