A specialized three-person team called Slopfix is charging companies $10,000 per week to identify and remove inefficient AI-generated code from their software, using AI tools themselves to analyze and improve the code without sacrificing functionality.
- Slopfix uses AI to detect and fix AI-generated code issues.
- $10,000 weekly fee based on achieving code reduction targets.
- Offers a two-week warranty on any repairs made.
What happened
Slopfix, a three-member software team, has launched a consultancy service that helps companies clean up excessively large AI-generated codebases in their internal applications. They use AI tools to identify inefficient, duplicated, or broken code created through vibecoding practices, a method where AI agents generate code based on user prompts.
The team combines AI-powered code analysis with their own development expertise to evaluate each screen and endpoint in the application, isolating problematic AI-generated segments. Their pricing model charges $10,000 a week contingent on meeting defined code reduction goals, ensuring clients pay for measurable results.
Why it matters
AI-generated code is increasingly used for software development, but it often results in bulky, error-prone projects as AI agents lose logical context over time. This creates challenges such as duplicated functions, broken features, and hallucinated code, leading to maintenance difficulties and degraded software performance.
Slopfix’s approach represents a novel hybrid of human expertise and AI tooling to address these growing pain points. Their service helps companies optimize the outcomes of vibecoding without discarding AI assistance entirely, highlighting the evolving role of AI in both creating and refining software.
What to watch next
As awareness of AI-generated code issues grows, more consultancies may emerge offering similar AI-assisted cleanup services. The market could see increasing demand for specialized teams that combine software craftsmanship with AI capabilities to tame the complexities introduced by vibecoding.
Clients should track success stories and evolving best practices from early adopters like Slopfix, as well as monitor how pricing models and warranty commitments shape the service landscape. Future innovation may also focus on better tooling to prevent AI code flab from accumulating in the first place.