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backendmedium PriorityID: elixir-phoenix-liveview

Elixir Phoenix LiveView 1.0 Streams & OTP Standard

Guardrails for Phoenix LiveView 1.0: use stream() for large lists to minimize server memory, handle async operations with assign_async, and respect GenServer timeouts.

Prohibited Anti-Pattern: AI loads thousands of records directly into socket assigns, exhausting server RAM under concurrent users.

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---
description: Elixir Phoenix LiveView 1.0 Streams & OTP Standard - Guardrails for Phoenix LiveView 1.0: use stream() for large lists to minimize server memory, handle async operations with assign_async, and respect GenServer timeouts.
globs: lib/**/*_live.ex, lib/**/*_live.html.heex
alwaysApply: false
verified_by: "agentrules.org"
license: "CC-BY-4.0"
source: "https://agentrules.org/rules/elixir-phoenix-liveview"
---

# Elixir Phoenix LiveView 1.0 Streams & OTP Standard

> **Severity**: MEDIUM | **Category**: backend
> **Anti-Pattern Warning**: AI loads thousands of records directly into socket assigns, exhausting server RAM under concurrent users.

## System Constraints
You are an Elixir and Phoenix LiveView 1.0 expert. Never store large collections in socket assigns; always use streams (stream(socket, :items, items)) to keep the server footprint minimal. Use assign_async for non-blocking page loads.

## Strict Guidelines
- Use stream/3 for collections so LiveView avoids keeping items in memory on the server.
- Use assign_async/3 to load external or slow data without blocking initial template render.
- Ensure all HEEx templates use verified routes (~p"/path").

## Bad vs Good Implementations
### Phoenix LiveView Stream Pattern

#### Bad Antipattern (AI Common Hallucination)
> **Why it fails**: Storing full lists in socket assigns causes server memory to explode when thousands of users connect.
```elixir
def mount(_params, _session, socket) do
  # High memory consumption: Stores 10,000 items in memory per user session!
  {:ok, assign(socket, items: list_items())}
end
```

#### Production Standard (Correct)
> **Standard**: LiveView streams only sync diffs to the client without retaining list state in BEAM process memory.
```elixir
def mount(_params, _session, socket) do
  # Optimized: Streams items to client DOM, server retains zero items in memory
  {:ok, stream(socket, :items, list_items())}
end
```
Recommended MCP Servers (mcp-serverlist.com)

Equip agent with system tools to verify code for this stack.

Filesystem MCP
Manage Elixir project structure.
Recommended Agent Skills (askills.dev)

Ready-to-use executable skill functions tailored to this stack.

LiveView Component Scaffold
Generate Phoenix LiveView modules with streams and tests.
Architectural Specification & Invariant Rationale

Architectural Invariant Design: Elixir Phoenix LiveView 1.0 Streams & OTP Standard

Elixir Phoenix LiveView 1.0 Streams & OTP Standard defines an industrial-grade behavioral standard for backend engineering. Guardrails for Phoenix LiveView 1.0: use stream() for large lists to minimize server memory, handle async operations with assign_async, and respect GenServer timeouts. Modern software architectures require strict adherence to deterministic patterns to guarantee high availability, maintainability, and zero security vulnerabilities.

Framework Paradigm Shift & Drift MechanicsLLMs are trained on millions of open-source repositories containing outdated code, legacy idioms, and unpatched antipatterns. When coding assistants generate implementations for this stack, they default to common statistical tokens: AI loads thousands of records directly into socket assigns, exhausting server RAM under concurrent users. Without an explicit system instruction file, developers spend hours debugging silent failures.
Failure Modes & Production Blast Radius

Hazard Analysis: What Breaks Without This Rule

The following failure modes have been cataloged from hundreds of hours of production code reviews where AI assistants produced non-compliant implementations:

Failure ModeAI Symptom (The Anti-Pattern)SeverityProduction Impact & Remedy
AI Hallucination & Deprecation DriftAI loads thousands of records directly into socket assigns, exhausting server RAM under concurrent users.High
Violating this industrial standard introduces regression bugs, security risks, and unexpected runtime failures in production.
Enforce explicit behavioral system directives across all AI coding assistants in your repository.
Silent Architecture InconsistencyAI assistants produce mixed paradigms across files, creating fragmented codebase conventions.Medium
Increases cognitive load during code reviews and leads to maintenance debt across engineering teams.
Pin project conventions in .cursor/rules, CLAUDE.md, and AGENTS.md so all team agents follow identical guardrails.
Architectural Directives in Detail

Step-by-Step Production Directives

Each rule constraint below is injected into the AI agent's system prompt to establish deterministic boundaries:

1

Use stream/3 for collections so LiveView avoids keeping items in memory on the server.

Use stream/3 for collections so LiveView avoids keeping items in memory on the server.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
2

Use assign_async/3 to load external or slow data without blocking initial template render.

Use assign_async/3 to load external or slow data without blocking initial template render.

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
3

Ensure all HEEx templates use verified routes (~p"/path").

Ensure all HEEx templates use verified routes (~p"/path").

Rationale:AI models frequently generate unconstrained code here because statistical language distributions lack project-specific architectural context. Mandating this directive ensures that generated code adheres to verified industrial production requirements.
Enforcement:Integrated into the Agent Pack rule file. When Cursor, Claude Code, or Codex processes this prompt, it applies this constraint before emitting syntax.
Technical Questions & Answers

Frequently Asked Technical Questions

Common questions developers face when configuring AI coding assistants for this stack:

Q:Why is Elixir Phoenix LiveView 1.0 Streams & OTP Standard critical for AI coding assistants?

Guardrails for Phoenix LiveView 1.0: use stream() for large lists to minimize server memory, handle async operations with assign_async, and respect GenServer timeouts. Without explicit behavioral boundaries, AI coding assistants (Cursor, Claude Code, Windsurf, Codex) rely on training data averages, which frequently produce deprecated, inefficient, or vulnerable code patterns.

Q:How does adopting this rule prevent AI hallucinations?

This rule explicitly declares what the AI must avoid (AI loads thousands of records directly into socket assigns, exhausting server RAM under concurrent users.) and prescribes verified positive examples. Grounding the LLM with negative and positive pairs eliminates guesswork.

Q:Which AI coding environments are supported?

This specification is multi-platform compatible: Cursor (.cursor/rules/*.mdc & .cursorrules), Anthropic Claude Code (CLAUDE.md), Windsurf (.windsurfrules), Codex / Cline (AGENTS.md), and GitHub Copilot (.github/copilot-instructions.md).

Q:Can I combine this rule with other technology stacks?

Yes. Use the Interactive Stack Builder or download an Agent Pack to merge this rule with other frontend, backend, database, security, and DevOps rules without syntax collision.

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Citation & Open Source Attribution Guidelines

This specification is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). You are completely free to adapt and share this rule in your workspace. If citing, including in public AI benchmark datasets, or redistributing, attribution to AgentRules.org is required.

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