Build an AI Dev Team: Code Review & Architecture Analysis
Five frontier AI models working as your senior engineers. Each with a specialized technical role. All trained on your codebase patterns, your style guides, and your architectural decisions.
Code review that catches security issues and design flaws. Architecture analysis that gets smarter with every decision.
Single-AI code review misses the big picture
You paste code into ChatGPT. It catches syntax issues and suggests improvements. But it doesn’t know your codebase’s patterns, your team’s conventions, or why you made certain architectural decisions. Every review starts from zero.
Real code review needs multiple perspectives – security, performance, maintainability, consistency with existing patterns. It needs someone who remembers the post-mortem from last quarter and the tech debt you agreed to address.
Suprmind changes this. Five AI models work as your engineering team – one scans for security issues, another checks performance implications, another ensures consistency with your patterns. The Knowledge Graph remembers every architectural decision, every post-mortem, every code review. Your 100th review has context your 1st couldn’t.
Five specialists. Comprehensive code review.
Each AI brings different technical expertise. Together, they catch what individuals miss.
Grok
Security & Updates
Scans for recent CVEs affecting your dependencies. Checks for security anti-patterns, injection vulnerabilities, and authentication issues. Tracks package updates and breaking changes.
Perplexity
Best Practices Research
Finds and cites current best practices, documentation, and community solutions. Researches how similar problems are solved in well-maintained open source projects. Sources everything.
Claude
Edge Case Analysis
Deep analysis of edge cases, race conditions, and failure modes. Stress-tests error handling. Identifies where code could fail in production. Conservative interpretation of “it works.”
GPT
Pattern Compliance
Checks code against your style guides and architectural patterns. Ensures consistency with existing codebase. Identifies violations of team conventions. Flags when code introduces new patterns without justification.
Gemini
Architecture & Documentation
Synthesizes review into actionable recommendations. Evaluates architectural implications of changes. Generates documentation for significant decisions. Produces the PR summary and tech debt assessment.
15 minutes to build your AI dev team
Configure once for your codebase. Use across all development workflows.
Create a Development Project
“Code review for React/TypeScript SaaS application. Focus: type safety, component patterns, API error handling, performance. Monorepo with Turborepo. Testing with Vitest. Deploy via Vercel.”
Generate Instructions with Prompt Adjutant
Define your code standards, architectural principles, and review checklist. Get structured instructions every AI will follow.
Upload Your Technical Standards
The documents that define “good code” for your team:
Approved architecture patterns
Security requirements
Performance benchmarks
Past post-mortems
Start Your Code Reviews
Paste code or describe an architecture decision. Five engineers respond in sequence – security, best practices, edge cases, pattern compliance, synthesis.
Code review in action
YOUR PROMPT
Review this authentication middleware. We’re adding JWT refresh token rotation. Check for security issues, race conditions, and whether this follows our existing auth patterns.
GROK – Security Scan
“CRITICAL: Refresh token stored in localStorage – vulnerable to XSS. Should use httpOnly cookie. Also: jsonwebtoken package version 8.x has known vulnerabilities – CVE-2022-23529. Current best practice is jose library or jsonwebtoken 9.x+. Token expiry check missing time skew tolerance.”
PERPLEXITY – Best Practices
“OWASP recommends refresh token rotation with single-use tokens (implemented correctly here). Auth0’s pattern includes device fingerprinting for additional security. Next.js middleware auth pattern from Vercel examples uses different approach – edge-compatible. Consider: your current pattern won’t work in edge runtime if you migrate.”
CLAUDE – Edge Cases
“RACE CONDITION: If two requests hit simultaneously with same refresh token, both could succeed before invalidation. Need atomic check-and-invalidate. Also: no handling for clock skew between servers. Token could be valid on one server, expired on another. Error path returns 401 but doesn’t clear client-side token state.”
GPT – Pattern Compliance
“Deviates from existing auth patterns in /lib/auth. Current pattern uses middleware composition; this is inline. Token storage differs from user session handler. Suggest: extend existing AuthProvider rather than new implementation. Also: error codes don’t match your API error standard (AUTH_xxx prefix).”
GEMINI – Summary
“RECOMMENDATION: Significant revision needed before merge. Priority fixes: (1) Move token storage to httpOnly cookie, (2) Add atomic token rotation with Redis/DB transaction, (3) Upgrade jsonwebtoken or switch to jose, (4) Align with existing AuthProvider pattern. Consider: this is a good candidate for ADR given security implications. Shall I draft the architectural decision record?”
Your team learns your codebase
The Knowledge Graph builds understanding of your architecture, patterns, and decisions.
What it learns
Past post-mortem lessons
Tech debt you’ve accepted
Code review patterns
ADR history
Performance benchmarks
How it helps over time
“Similar pattern caused the Q3 outage. See post-mortem: connection pooling issue under load.”
“This contradicts ADR-047 decision to use Redis for session storage. Intentional deviation?”
“Last three PRs touching this module introduced regressions. Suggest additional test coverage.”
Beyond code review
The same team structure works across the development lifecycle.
Architecture Decisions
Evaluate technical options with multiple perspectives. Grok researches current trends, Claude stress-tests edge cases, Gemini drafts the ADR. Comprehensive analysis before committing to a direction.
Incident Analysis
Debug production issues with full context. The Knowledge Graph remembers past incidents, deployment history, and system changes. Faster root cause analysis with institutional memory.
Technical Documentation
Generate accurate documentation from code and discussions. Gemini synthesizes technical content, GPT ensures consistency with existing docs. Documentation that stays current.
Dependency Evaluation
Assess new libraries and frameworks. Grok checks security advisories, Perplexity researches community sentiment, Claude evaluates integration complexity. Informed decisions before adding dependencies.
Build your AI engineering team today.
Code review that catches security issues and design flaws.
Architecture analysis that gets smarter with every decision.