How AnySoft scaled AI Development with Devin + Propel’s Quality Loop
The Challenge
As AnySoft’s engineering velocity increased (powered by both their team and AI coding tools like Devin) the volume of changes moving through the development cycle grew rapidly. With more code being produced, the team wanted to ensure that:
- Review quality stayed consistently high
- Internal standards were applied across contributors
- Engineers spent less time on repetitive reviews
- The workflow could scale without adding bottlenecks
AnySoft needed a system that could match Devin’s speed with high-quality review.
The Solution: A Two-Tool Feedback Loop
AnySoft paired Devin for fast code generation with Propel for rigorous code review, forming a tight loop that ensures both velocity and quality.
How the Loop Works
- Devin generates the initial implementation.
- Propel reviews the PR, catching issues, enforcing standards, and providing high-signal suggestions.
This simple pairing created a scalable, dependable review cycle that fit naturally into their existing workflow.
Why AnySoft Chose Propel
AnySoft needed a reviewer that didn’t just point out issues, but guided the rest of their AI workflow.
Propel’s tailored comments surfaced the context that agents needed to improve or regenerate code, making the entire loop more reliable.
As a result, Propel became the quality layer that kept pace with AI-generated output.
Key Results
66% of PRs improved
At least one Propel comment was implemented in two-thirds of PRs.
76% implementation rate
Percentage of review comments addressed through a code change
