Your AI coding agents are shipping code fast. The architecture is quietly degrading. You don't have a senior architect to catch it — and most AI architecture software reviews diffs, not systems.
Tekk.coach reads your entire codebase, identifies structural issues before they compound, and tells you exactly what to fix. It's the architecture review you'd get from a senior engineer, without adding one to the team.
How Tekk.coach Does AI Architecture Software Review
Tekk's review mode is not a linter. It's not a CI rule checker. It reads your actual repository — using semantic search via embeddings, file search, regex search, directory browsing, and repository profiling — before forming any architectural opinion. It understands your languages, frameworks, services, and dependencies. Then it reasons about structural design.
When you run an architecture review in Tekk, the agent searches the web for current best practices alongside reading your code. That means recommendations are benchmarked against what's architecturally correct in 2026, not just internally consistent within your codebase. If your dependency injection pattern is outdated, or your service boundaries don't reflect current microservices thinking, Tekk will surface it.
The output is actionable, not generic. "Your auth service has a circular dependency with the user service via a shared repository layer — here's the recommended restructure" is what you get. Not "consider applying clean architecture principles."
What makes this AI architecture software different is the integration with planning. After identifying structural issues, Tekk can immediately generate a structured spec to address them. Review and planning operate from the same codebase context — the finding and the fix plan are one session.
Key Benefits
Catches structural problems before they compound Most architectural issues start small and become expensive. Tekk surfaces dependency problems, design anti-patterns, and layer violations when they're cheap to fix — not after you've built three features on top of them.
Reads the whole system, not just the diff PR-level code review sees what changed. Architecture review needs to see the whole system. Tekk reads the full repository — semantic search across your entire codebase — before any review output.
Web research during review Tekk searches for current best practices while reviewing your code. Recommendations reference what's architecturally sound today, not patterns from three years ago. You get the equivalent of a senior architect who reads the engineering blogs.
Multiple review types from one codebase connection Architecture review, security review, performance review, agent improvement review. One tool, one repo connection, four specialist perspectives. You don't need four different tools with four different integrations.
Connects to the planning workflow Review findings don't sit in a report. They connect directly to Tekk's planning workflow — you can generate a structured spec to address architectural issues immediately after finding them.
How It Works
Step 1: Connect your repository Link your GitHub, GitLab, or Bitbucket repo via OAuth. Tekk gets read access to your codebase. No instrumentation, no deployment changes, no setup overhead.
Step 2: Trigger an architecture review "Do an architecture review." "Check my service boundaries." "Review my dependency structure." Natural language instruction. The agent runs semantic search, file analysis, and repository profiling before responding.
Step 3: Get actionable findings The agent produces specific architectural findings grounded in your actual code: what the structural issue is, where it lives (specific files and patterns), and what to do about it. Not a generic checklist — a codebase-specific analysis.
Step 4: Plan the fix Switch immediately to planning mode. The same codebase context that powered the review powers the spec generation. Describe the architectural change you want to make; Tekk generates a structured plan with subtasks, acceptance criteria, and file references.
Step 5: Execute with your coding agents Hand the structured spec to Cursor, Claude Code, or Codex. Your agents have the precision instructions they need. No flailing, no scope creep, no "that's not what I meant" rework cycles.
Who This Is For
Solo developers building with AI coding agents You're using Cursor or Claude Code, shipping fast, and you know the codebase is accumulating structural debt. You don't have a senior architect to review your design decisions. Tekk is the architecture review you'd otherwise skip.
Small teams (1-10 people) without a dedicated architect Your team has real engineers but no one whose primary job is architectural oversight. Features are getting built on shaky structural foundations. Tekk reviews the system design that none of you have time to review formally.
Developers building in domains outside their expertise Your product now needs a data pipeline, an AI agent integration, or a payments system. You can build it, but you're not sure if your architectural choices are defensible. Tekk reads your code and compares it to current best practice — without you having to become a specialist in every domain you touch.
Technical founders who need to validate their architecture before scaling You've built the MVP. Now you're bringing on developers and need to make sure the foundation is sound before multiplying the structural decisions that are already in place.
What Is AI Architecture Software?
AI architecture software (in the software engineering sense) applies artificial intelligence to the discipline of evaluating and improving software system design. It reads codebases, identifies structural problems, recommends architectural patterns, and reviews adherence to design principles — tasks that traditionally required a senior architect working manually.
The category has expanded rapidly since 2024, driven by a specific problem: AI coding tools are generating code at unprecedented volume, but code that works at the function level often violates architectural principles at the system level. An AI coding agent writing a login handler doesn't know how that handler interacts with the session model or the audit log — it knows only what's in its context window. AI architecture software addresses the structural layer that line-level tools miss.
The landscape includes approaches ranging from runtime behavioral analysis (vFunction, which instruments running applications to map actual dependencies) to static codebase analysis (CodeScene's behavioral git analysis, Sourcegraph's cross-repo intelligence) to on-demand review (Tekk, Microsoft's Architecture Review Agent). Enterprise platforms require significant implementation overhead; lighter approaches work at the session level on demand.
The core problem these tools address: architectural degradation is invisible until it's expensive. PRs are getting larger as AI coding adoption increases, change failure rates are rising, and traditional manual architecture review can't keep pace with output velocity. AI architecture software is the category's attempt to maintain structural quality at AI-assisted development speed.
Ready to Try Tekk.coach?
Connect your repo and run an architecture review in minutes. If your codebase has structural issues — and AI-assisted codebases almost always do — Tekk will find them before they become expensive to fix.