AI Code Review for Elixir Projects

The hidden complexity of Elixir codebases

Elixir projects benefit from the BEAM virtual machine's battle-tested concurrency model. Processes are lightweight, supervision trees restart failed components, and the “let it crash” philosophy encourages developers to write code that handles failure gracefully. In theory, this makes Elixir applications robust by default. In practice, the abstractions hide a category of issues that static analysis tools and linters struggle to detect.

The problem is that Elixir's power comes from runtime behaviour, not compile-time guarantees. A GenServer that accumulates state without bounds will eventually exhaust memory, but the compiler will not warn you. A supervision tree with an incorrect restart strategy will cascade failures instead of containing them, but Dialyzer cannot reason about that. Pattern matching that covers every clause the developer considered may still miss edge cases introduced by upstream data changes.

Standard Elixir tooling – Credo for style, Dialyzer for type checking, and mix format for formatting – catches surface-level issues effectively. But the category of bugs that cause production incidents in Elixir systems tends to involve process lifecycle management, message passing semantics, and OTP behaviour misuse. These are cross-module concerns that require understanding how different parts of the system interact at runtime, not just how individual modules look in isolation.

VibeRails applies AI reasoning across every file in your Elixir project simultaneously. It understands OTP behaviours, Phoenix conventions, and Ecto patterns well enough to identify issues that span module boundaries – the kind of problems that cause 3 AM production pages and are invisible to line-by-line linting.

What VibeRails finds in Elixir codebases

Elixir projects have a specific profile of technical debt shaped by the language's concurrency model and the OTP framework. VibeRails scans every module and surfaces these patterns:

• GenServer state management problems – processes that accumulate unbounded state over time, handle_info callbacks that silently drop messages, and GenServer calls that block the caller without timeout guards. A GenServer that grows a list without pruning will eventually consume all available memory.
• Supervision tree design flaws – incorrect restart strategies that cascade failures instead of isolating them, supervisors with too many children under one_for_all strategy, missing supervision for critical processes, and dynamic supervisors that spawn processes without backpressure limits.
• Pattern matching exhaustiveness gaps – function heads that handle known cases but rely on a catch-all clause that silently discards unexpected inputs. When upstream data formats change, the catch-all masks the problem until downstream effects surface.
• Process mailbox overflow risks – GenServers that receive messages faster than they process them, missing flow control between producer and consumer processes, and receive blocks with selective receive patterns that let the mailbox grow unboundedly.
• Ecto query composition issues – N+1 query patterns hidden behind Ecto associations loaded without preloading, dynamic query construction that bypasses parameterisation, schema-less queries that drift from the actual database structure, and missing indexes for common query patterns.
• Phoenix LiveView memory leaks – LiveView processes that subscribe to PubSub topics without unsubscribing on unmount, assigns that accumulate data without bounds across user interactions, and handle_event callbacks that trigger expensive operations without debouncing.
• Hot code reload safety – modules that rely on process state formats that change between releases without migration logic, GenServers missing code_change/3 callbacks, and release configurations that do not account for state transformation during upgrades.
• OTP behaviour misuse – using GenServer where a simpler Agent or Task would suffice, implementing retry logic manually instead of leveraging supervision tree restarts, and mixing synchronous calls with asynchronous casts in ways that create race conditions.

These are not theoretical risks. They represent the categories of issues that cause production incidents in real Elixir systems – gradual memory growth, cascading process failures, and silent data loss from unmatched messages.

Beyond Credo and Dialyzer

Credo is excellent at enforcing code style conventions and catching common anti-patterns at the individual function level. Dialyzer provides gradual type checking through success typing. Together they form a solid baseline for Elixir code quality. But neither tool can reason about the runtime behaviour of a system of interacting processes.

Consider a GenServer that handles both synchronous calls and asynchronous casts. Credo will check the formatting and naming conventions. Dialyzer will verify the type signatures match. But neither will detect that the handle_cast callback modifies state in a way that makes a subsequent handle_call return stale data under concurrent access. That requires understanding how the GenServer's message processing order interacts with the state transitions – a cross-function, cross-clause analysis that AI reasoning is well suited for.

Similarly, supervision tree analysis requires understanding the relationship between multiple modules. A supervisor's restart strategy only makes sense in the context of the children it manages and the dependencies between them. A one_for_one strategy is correct when children are independent, but becomes dangerous when one child writes state that another reads. VibeRails analyses the full tree structure and flags strategies that do not match the actual dependency patterns in the code.

For Phoenix applications, VibeRails understands the framework's conventions around contexts, schemas, controllers, and LiveView modules. It identifies cases where business logic leaks out of contexts into controllers, where changesets validate data inconsistently across different entry points, and where LiveView socket assigns grow without limits during long-lived user sessions.

Elixir-friendly pricing and workflow

The Elixir community values simplicity, reliability, and tools that respect developer autonomy. VibeRails aligns with these values:

• Per-developer licensing – $19/mo or $299 once per developer. Each licence covers one machine. Volume discounts available for teams.
• Free tier to evaluate – 5 issues per review at no cost. Run a scan on your Elixir project today and see what VibeRails finds before committing any budget.
• Desktop app, no CI integration needed – point VibeRails at your local repository and run the scan. No GitHub App, no webhook configuration, no mix dependency to add.
• BYOK model – VibeRails orchestrates your existing Claude Code or Codex CLI subscription. If you already use these tools for development, VibeRails adds code review capabilities with no additional AI cost.
• Local analysis – your source code is read from disk locally and sent directly to the AI provider you configured. It never passes through VibeRails servers. For projects with proprietary business logic or sensitive data handling, your code is not uploaded to a VibeRails cloud service.

Start reviewing your Elixir codebase today

Whether you are building a Phoenix web application, a distributed system with custom OTP behaviours, or a data processing pipeline with Broadway, VibeRails provides a structured review of your entire codebase. The AI understands Elixir idioms, OTP patterns, and the BEAM runtime model well enough to find the issues that matter – not just style violations, but the architectural and concurrency problems that cause real production incidents.

Export findings as HTML for team discussions or CSV for import into your project management tool. Each finding includes the module path, specific function, severity rating, and a description of the issue and its potential impact. Turn findings into actionable tickets and start paying down technical debt systematically.

Download the free tier and run your first scan. If the findings are valuable, upgrade to the lifetime licence for $299 – less than a single day of contractor time.