We're building an AI agent orchestration platform using Claude (Coworker) for code generation paired with local builds and iteration. Our current workflow:
Feature planning in Claude (conversational)
Code generation in Coworker (full repo context)
Local build and testing
Push to GitHub
Manual PR review + merge
The bottleneck: Step 5. We're currently doing manual code review and merging ourselves, which is slowing down iteration.
Options we're considering:
Hire a part-time senior dev (GCP + FastAPI) to handle all PR reviews/merges
Automate more of the review process with tools
Combination of both
Our stack: FastAPI (Python), GCP (Cloud SQL, Firestore, Vertex AI), five microservices, strict architectural rules (boundary integrity, state sync, cold start mitigation).
Questions:
How are other teams handling AI-generated code review at scale?
Tools worth looking at? (GitHub Actions, Sonarqube, etc.)
Is hiring a part-time architect/reviewer the move, or should we invest in automation first?
Anyone doing this with Claude/LLM-generated code?
Curious what the community recommends.
The PR workflow with AI-assisted dev needs one critical addition: prompt versioning. When your system prompts affect code generation quality, changing a prompt is effectively changing your "compiler." Track which prompt version generated each PR so you can correlate code quality with prompt changes. I keep my system prompts in the repo alongside the code — they get reviewed in PRs just like any other config that affects output.
¿Qué ventajas tiene usar aplicaciones web (como Google Workspace) frente a los programas tradicionales instalados en la computadora?
the hardest part of AI-assisted development + PR workflows isn't the code generation — it's the review layer. what keeps biting teams i talk to:
reviewer fatigue. once you're reviewing 5x the PR volume, "LGTM" becomes default and real bugs slip through. you need tighter scope-per-PR enforced at the agent level, not the human level.
attribution drift. six months in, nobody remembers which lines the human wrote vs which the agent wrote. matters a lot when you need to debug a regression.
convention drift. every agent session starts with a blank slate unless you invest in a strong CLAUDE.md + slash commands layer. "we figured out last sprint that our tests need X" is knowledge that evaporates without scaffolding.
the fix i've landed on is treating skills and CLAUDE.md files as first-class, versioned, installable artifacts. been building tokrepo.com as an open registry for exactly this class of thing — claude code skills / slash commands / MCP configs, installable with one command, so the conventions don't evaporate between projects or team members. works really well alongside a tight PR workflow: agent runs the skill, skill enforces the convention, PR stays on-spec.
fwiw the thing that surprised me most: the scaffolding ends up mattering more than model quality. an average model with great conventions beats a great model with no conventions, every time.
You’re definitely not alone that “Step 5 bottleneck” is where most AI-assisted teams hit reality.
Right now, most teams aren’t fully automating reviews yet. The common pattern I’m seeing is a hybrid approach, not purely human or purely automated.
AI generates code → Automated checks (linting, tests, security, architecture rules) → Targeted human review (not full manual review)
👉 The key shift: humans review intent + architecture, not every line.
Shubham Jha
6+ years of engineering experience → production-ready code, simplified.
The PR bottleneck is real, but hiring before you tighten scope is the wrong order. AI-generated PRs tend to be large because the agent has no reason to keep them small. That's a prompting problem, not a people problem. Enforce atomic PRs at the agent level first.
On tooling: automated checks (lint, tests, type safety) should catch the mechanical stuff so human review stays focused on architecture and intent. That's the only version of this that scales. A dedicated reviewer gets buried fast if every PR is 400 lines of generated code with no boundaries.