Personal notes from experimenting with AI coding tools, workflows, and frameworks.
Keybinder
A modern, intuitive macOS app for managing skhd keyboard shortcuts.
Features
- Auto-Detection - Finds skhd config from standard locations
- Visual Editor - Clean interface for editing keyboard shortcuts
- Safety Controls - Confirmation for destructive commands
- Real-time Log Viewer - Live streaming of service logs
- System Theme Integration - Automatic light/dark mode
Development Approach
Used spec-kit for specification-driven development:
- Initial feature planning with structured specs
- Implementation tasks generated from specifications
- Pragmatic deviation during actual development (specs as reference, not strict rules)
SealCode (VS Code Extension)
Smart Code Review with AI-Powered Insights
Features
- AI-Powered Review - Send comments to Claude, Copilot, OpenCode, or Amp
- Prompt Templates - Built-in templates for review, security, refactor workflows
- Categorized Comments - Bug, Question, Suggestion, Nitpick, Note
- Rich Visual Feedback - Inline decorations, gutter icons, line backgrounds
- Export Options - Export reviews to Markdown or HTML
Development Approach
Built autonomously using Ralph (AI agent system) with Amp as the coding assistant:
- PRD-driven development with task decomposition
- Autonomous implementation of extension features
- Integrated testing and quality validation
Ralph
Autonomous AI agent loop for PRD-driven development.
Minimal Ralph implementation: PRD → task decomposition → autonomous execution → loop until complete. Used in SealCode development. Will deprecate once upstream PRs land.
AI CLI Switcher
Fast launcher for switching between AI coding assistants.
Fuzzy search interface for Claude Code, OpenCode, Amp, etc. Quick switching without managing multiple terminals.
Tiny Coding Agent
Minimal coding agent focused on simplicity.
Lightweight agent with minimal dependencies. Response to heavy frameworks that waste tokens on orchestration overhead.
Key Takeaways
| Tool Combination |
Best For |
| Claude + spec-kit |
Greenfield projects requiring structured planning |
| Amp + Ralph |
Autonomous development with PRD-to-implementation pipelines |
| AI CLI Switcher |
Developers working with multiple AI tools |
| Tiny Agent |
Cost-conscious development with minimal overhead |
Focused, single-purpose solutions > heavy, all-in-one frameworks.
Not every tool fits every workflow. Here are tools I evaluated but chose not to adopt:
Task Master (claude-task-master)
Repository: eyaltoledano/claude-task-master
An AI-powered task management system designed for Cursor, Windsurf, and other editors.
Why I didn’t keep it:
- Complexity - Requires multiple API keys (Anthropic, OpenAI, Perplexity, etc.)
- Heavy setup - MCP configuration, environment variables, PRD structure
- Overkill - 36 tools available, ~21,000 tokens context usage in full mode
- Too structured - Strict PRD-to-task workflow doesn’t fit iterative development
SuperClaude
Website: superclaude.netlify.app
A meta-programming configuration framework for Claude Code.
Why I didn’t keep it:
- Context hungry - Uses too much context for the framework overhead
- Mental overhead - Learning the framework’s abstractions vs just coding
- Over-engineered - Adds complexity without proportional benefit
Oh My OpenCode
Repository: code-yeongyu/oh-my-opencode
A feature-rich plugin for OpenCode with multi-model orchestration, background agents, and “Sisyphus” workflow.
Why I didn’t keep it:
- Too opinionated - Enforces specific workflows (ultrawork, ralph-loop, Sisyphus mode)
- Multi-model complexity - Requires multiple API keys (Claude, GPT, Gemini, Grok)
- Magic keywords -
ultrawork, ulw, ultrathink - adds cognitive overhead
- Feature bloat - LSP tools, AST-grep, background agents, keyword detectors
- Not my style - Aggressive automation doesn’t fit my iterative workflow
Worth Learning From
These tools aren’t for me daily, but are valuable references for understanding AI-assisted workflows:
Superpowers
Repository: obra/superpowers
A complete software development workflow for coding agents with composable “skills”.
Key concepts worth studying:
- Brainstorming phase - Agent asks questions before coding, refines specs iteratively
- Writing plans - Bite-sized tasks (2-5 min each) with exact file paths and verification steps
- Subagent-driven development - Fresh subagent per task with two-stage review
- TDD enforcement - RED-GREEN-REFACTOR cycle, deletes code written before tests
- Git worktrees - Isolated workspaces on new branches
Why it’s a good reference:
- Well-structured skill composition patterns
- Philosophy: systematic over ad-hoc, evidence over claims
- Shows how to build layered agent workflows
My Philosophy: Keep It Simple
“Add only if needed”
Instead of adopting heavy frameworks, I prefer:
| Approach |
Why |
| Minimal tooling |
Less context usage, more tokens for actual work |
| AGENTS.md |
Simple, portable project guidance |
| Native AI features |
Use built-in Claude/Amp capabilities first |
| Add incrementally |
Only add tools when there’s clear friction |
The best tool is the one you don’t have to think about.