About CodeMySpec
Built by John Davenport. 15 years in enterprise systems, 2 years building LLM-assisted dev tooling for Phoenix.
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Reviews, comparisons, and resources for AI-assisted development tools and workflows.
Privacy Policy
How CodeMySpec collects, uses, and protects your data. We use Google Analytics for usage data and cookies for session management.
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Terms of Service
Terms of service for using CodeMySpec, the AI-assisted Phoenix development platform.
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Progressive Tool Disclosure: How Claude Handles Hundreds of MCP Tools
Five MCP servers burn 55K tokens before Claude reads your first message. Progressive tool disclosure fixes this. Here's how it works.
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The Five Layers of an Agentic Coding System
Most developers treat their AI coding tool as one thing. It's five layers. Here's the framework that changes how you evaluate and build with them.
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The Agent Layer: How AI Coding Tools Actually Work
The agent loop is a while loop that changed software. Here's how tool use, context management, and ReAct turn a token predictor into a coding tool.
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The Environment Layer: Where AI Code Actually Runs
CLI, IDE, or cloud? Sandboxed or wide open? The environment determines what your AI coding agent can do. Here's why it matters more than you think.
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The Harness Layer: Why the Wrapper Matters More Than the Model
OpenAI shipped 1M lines with zero manually written source. The secret wasn't the model. It was the harness - constraints, verification, lifecycle.
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The Model Layer: What Your AI Coding Tool Actually Is (and Isn't)
The model didn't write your code. It predicted tokens. Everything else is the harness. Here's why that matters more than benchmarks.
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The Orchestration Layer: Coordinating Multiple Agents
One agent hitting its ceiling? Multi-agent coordination is the next frontier. Here's what works, what doesn't, and why the demo-to-production gap is wide.
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GitHub Copilot in 2026: Features, Pricing, Benchmarks, and Community Sentiment
GitHub Copilot deep dive: $10/mo Pro tier, Coding Agent, 60M+ code reviews, Copilot Memory, and what Reddit developers actually think.
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Aider in 2026: Features, Pricing, Benchmarks, and Community Sentiment
Aider deep dive: 50+ model support, 4.2x token efficiency vs Claude Code, best-in-class git integration, and what Reddit developers actually think.
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Gemini CLI in 2026: Features, Pricing, Benchmarks, and Community Sentiment
Gemini CLI deep dive: 1,000 free requests/day, improving quality with 3.1 Pro, Jules async agents, and what Reddit developers actually think.
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Codex CLI in 2026: Features, Pricing, Benchmarks, and Community Sentiment
Codex CLI deep dive: open source Rust CLI, 2-3x token efficiency, 9,000+ plugins, and what Reddit devs actually think. Pricing, strengths, weaknesses.
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Cursor in 2026: Features, Pricing, Benchmarks, and Community Sentiment
Cursor deep dive: $2B ARR, Background Agents, MCP Apps, credit-based billing, and what Reddit devs actually think. Features, pricing, and assessment.
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Writing Applications for LLMs
Your CLAUDE.md is settings. Your skills are libraries. Your hooks are middleware. Two activities, one progression.
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Claude Code in 2026: Features, Pricing, Benchmarks, and Community Sentiment
Claude Code deep dive: highest-rated for code quality, Agent Teams, MCP ecosystem, and what Reddit developers actually think. Pricing and weaknesses.
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Open Source vs Vendor-Locked AI Coding Tools: The Tradeoffs That Matter
The most-loved tool (Claude Code) is fully closed. The most-starred (OpenCode, 117K) is fully open. Analysis of 21 tools shows when to choose which.
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What Happened to Supermaven, Aide, and Void: AI Coding Tools That Didn't Make It
Supermaven was acquired. Aide is sunsetting. Void went silent. Why AI coding tools die, what patterns predict failure, and which tools are at risk today.
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CodeMySpec Specs vs Kiro EARS: Two Approaches to Spec-Driven AI Development
Amazon's Kiro generates specs before code using EARS notation. CodeMySpec takes a platform approach. How two tools are betting on spec-driven AI development.
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MCP: The Protocol Connecting AI Coding Tools
Model Context Protocol is USB for AI agents. 1,000+ servers, adopted by Anthropic, OpenAI, Google. What MCP is, who supports it, and what it enables.
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Best Free and Open-Source AI Coding Tools in 2026
9 free and open-source AI coding tools compared. Gemini CLI is truly free. Aider and Cline match paid tools. When is BYOK cheaper than subscriptions?
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AI IDEs Compared in 2026: Cursor vs Windsurf vs Zed vs Kiro
Cursor, Windsurf, Zed, and Kiro compared: pricing, philosophy, benchmarks, and Reddit sentiment. Which AI IDE actually fits your workflow?
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Claude Code Skills: Writing Apps for Agents
What Claude Code skills are, how they work, and why they matter. Markdown applications that AI agents execute on demand.
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The Rise of CLI Coding Agents: Why Terminal-Native AI is Having a Moment
Claude Code accounts for 4% of GitHub commits. Gemini CLI hit 90K stars. The terminal won the AI coding war nobody expected. Here's why.
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The Best CLI Coding Agents in 2026: Claude Code vs Codex vs Gemini CLI vs Aider vs OpenCode vs Goose
6 CLI coding agents compared: benchmarks, pricing, and Reddit sentiment. Claude Code, Codex CLI, Gemini CLI, Aider, OpenCode, and Goose.
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The Five Levels of AI-Assisted Development
From autocomplete to fully autonomous development. A framework for understanding where you are with AI coding tools and where the real leverage is.
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Agentic QA
Unit tests and BDD specs verify pieces. QA verifies the running application — story QA, journey QA, and automated issue filing by AI agents.
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Architect - Your AI Phoenix Architecture Consultant
Conversational AI architect that maps user stories to Phoenix contexts, validates dependencies, and reviews architectural health.
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BDD Specs for AI-Generated Code
Unit tests verify your code works. BDD specs verify your app does what users actually want. One scenario per acceptance criterion, traced to user stories.
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Design Docs - Validated Specs Before Code
Write specs first, validate automatically, then let AI implement what you specified. 17 document types with type-specific validation.
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Why I Built CodeMySpec
After 10 years of failed startups and learning the hard way, I built CodeMySpec to help others avoid the same decade of pain.
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How to design architecture that keeps AI on track
Learn to design Phoenix contexts and vertical slice architecture to keep AI-generated code consistent.
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How to manage user stories to get the most out of LLM's
Practical approach to using user stories for AI code generation. Keep LLMs focused on requirements, maintain living documentation, and avoid technical debt.
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Stories - Your AI Product Manager
Get better user stories with an AI-guided conversation than you'd write alone. Complete traceability from requirements to code.
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Stories - AI-Managed Requirements
AI-guided story management through Claude Code. Interview-driven requirements gathering, structured data, quality reviews, and component traceability.
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Stories MCP Server - Project Manager AI Assistant
CodeMySpec's Stories MCP Server - AI project manager that helps you refine ideas into well-structured user stories through interactive interviews.
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How to write design documents that keep AI from going off the rails
Write one design doc per code file to prevent architectural drift and keep LLMs on track.
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