Elixir Expert

Purpose

Provides expertise in Elixir development, Phoenix Framework, and OTP patterns. Covers concurrent programming, real-time features with LiveView, and building fault-tolerant distributed systems on the BEAM VM.

When to Use

• Building Elixir applications

• Developing Phoenix web applications

• Implementing real-time features with LiveView

• Using OTP patterns (GenServer, Supervisor)

• Building distributed systems on BEAM

• Designing fault-tolerant architectures

• Working with Ecto for database access

Quick Start

Invoke this skill when:

• Building Elixir applications

• Developing Phoenix web applications

• Implementing real-time features with LiveView

• Using OTP patterns

• Designing fault-tolerant systems

Do NOT invoke when:

• Building Ruby on Rails apps (use rails-expert)

• Building Node.js backends (use javascript-pro)

• Building Python backends (use python-pro)

• Infrastructure automation (use terraform-engineer)

Decision Framework

Concurrency Pattern: ├── Stateful process → GenServer ├── Async work → Task ├── Background job → Oban or Task.Supervisor ├── Event streaming → GenStage / Broadway ├── Real-time UI → Phoenix LiveView └── External service → Retry with exponential backoff

Supervision Strategy: ├── Process can crash independently → one_for_one ├── Processes depend on each other → one_for_all ├── Ordered restart needed → rest_for_one └── Dynamic children → DynamicSupervisor

Core Workflows

1. Phoenix Application Setup

• Generate Phoenix project

• Configure database with Ecto

• Define schemas and migrations

• Create contexts for business logic

• Build controllers or LiveViews

• Add authentication

• Deploy with releases

2. OTP Application Design

• Identify stateful components

• Design supervision tree

• Implement GenServers for state

• Add proper error handling

• Implement graceful shutdown

• Test supervision strategies

3. Real-Time with LiveView

• Generate LiveView module

• Define assigns and state

• Implement handle_event callbacks

• Use pubsub for broadcasts

• Optimize with temporary_assigns

• Add JS hooks if needed

Best Practices

• Let it crash - design for failure recovery

• Use supervision trees for fault tolerance

• Keep GenServer state minimal

• Use contexts to organize business logic

• Prefer immutable data transformations

• Test concurrent code with async: true

Anti-Patterns

Anti-Pattern Problem Correct Approach

Large GenServer state Memory and serialization External storage, ETS

Defensive coding Hides bugs Let it crash, supervise

Blocking GenServer Process bottleneck Async tasks for I/O

No supervision Unrecoverable crashes Proper supervision tree

Mutable mindset Bugs and race conditions Embrace immutability