AI Slop Cleanup
AI-generated code gets you 70% of the way there fast. The remaining 30% — security, error handling, real architecture, types, tests, the bugs the model invented — is where most teams get stuck. We rewrite the parts that matter, keep the parts that work, and hand back a codebase a real engineer can maintain.
Concrete outputs — not vibes.
Every engagement ends with artifacts you own — running code, infrastructure, and the documentation to keep building on it.
Codebase audit
What's salvageable, what's hallucinated, what's a security risk, what's actually wired up.
Refactor plan
Prioritized by risk and value. Critical security & data-loss first; aesthetics last.
Types & contracts
Strict TypeScript / pydantic / zod boundaries where the AI invented them.
Error handling
Real failure modes — not just try/catch wrapping everything.
Test coverage
Tests on the load-bearing parts. We don't chase 100% — we chase the right paths.
Security pass
Auth, secrets, input validation, SQL injection, exposed endpoints, leaking env vars.
Performance pass
N+1 queries, missing indexes, blocking calls, accidental O(n²) loops.
From brief to production.
A tight, repeatable path. You always know what's happening and what comes next.
Audit
Read the whole codebase. Categorize: keep, refactor, delete, rebuild.
Triage
Security and data-loss risks fixed first, behind a hotfix branch.
Refactor
Module by module, with tests added as we go.
Tighten types
Strict TS / pydantic boundaries. Kill the `any`s.
Deploy with confidence
Observability, CI gates, and a proper rollback plan.
The tools we typically reach for.
Not prescriptions — we adapt to what you already run. Worth knowing what we’re fluent in.
Questions about AI Slop Cleanup
Usually, yes. AI-generated code tends to be verbose and inconsistent but not architecturally broken. We rebuild only when the foundation is hostile (no types, no boundaries, no tests on critical paths).
That's our most common cleanup. We do the audit, prioritize ruthlessly, and leave you with a codebase a hire-able engineer can pick up tomorrow.
Yes — selectively. We use AI for boilerplate refactors and codemods. We don't use it to invent architecture or make judgment calls. That's our job.
Yes. Most of the time you're already serving customers off the AI-shipped version. We work behind feature flags and parallel deploys so live traffic isn't affected.
Pattern matching. AI code has a specific shape of brokenness — invented APIs, copy-pasted abstractions, missing types at boundaries, security holes from autocomplete. We know what to look for.
Better. Strong types and clear module boundaries make Cursor / Copilot dramatically more accurate — they need real ground truth to anchor on.
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Learn moreLet’s scope your ai slop cleanup.
Send a brief and a senior engineer replies within four hours — with an honest read on whether we’re the right fit.