Orientation to the Coding Agent Craft skill path — the cross-vendor patterns that make any coding agent reliable, and where to start based on your current pain

Architect your codebase and workflow for maximum AI collaboration

Advanced git techniques for AI engineers — worktrees, bisect, reflog — each with agent workflows

Make one file work across Claude Code, Codex, Gemini CLI, Cursor, and Copilot — the cross-vendor spec, hierarchy, and migration audit for agent-native repositories

Honest, benchmark-cited decision guide for picking — and switching between — the three terminal coding agents reshaping dev work in 2026

Make the spec your source of truth — run the Spec Kit pipeline across Claude Code, Codex, and Gemini CLI and regenerate code from evolving specs

Frame bugs, read errors, bisect regressions, and find root causes fast — with any coding agent as your debugging partner

Coordinate multiple coding-agent sessions as peers — shared tasks, mailboxes, and the decision tree for picking teams vs subagents vs parallel sessions

Wire any coding agent into CI/CD and ops — automated pipelines, scheduled jobs, and business workflows end-to-end

Roll out coding agents across a team — pilot to org, SSO patterns, cost governance, shared conventions, sandboxing, and enterprise graduation. Cross-vendor.

A 12-minute orientation to five coding agents whose feature lists have converged near 1M context — so the real decision is fit, not capability.

Anthropic's terminal-native coding agent — architecture, 1M-token context, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.

OpenAI's async-first coding agent — CLI and cloud task architecture, sandboxed execution, permissions model, cost structure, and honest trade-offs for engineering managers evaluating their options.

Google's open-source terminal agent — being sunset for consumer, Pro, and Ultra users on 18 June 2026 in favor of the closed-source Antigravity CLI.

Microsoft/GitHub's IDE-native coding assistant ecosystem — surfaces, architecture, context handling, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.

The AI-native IDE that forks VS Code and weaves multiple models into every editing surface — architecture, context handling, permissions, cost model, and honest trade-offs for engineering managers evaluating their options.

A decision framework for engineering managers evaluating coding agents — dimensions that matter, team archetypes, multi-agent strategies, and rollout playbook.

A 12-minute orientation to the Claude Code skill path — why it exists, what you'll be able to do, how the chapters relate, and where to begin

From zero to productive — master Claude Code fundamentals and start shipping with AI from day one

Advanced workflows, custom commands, and power-user patterns that 10x your output

Build your first Claude Code plugin — from zero to shareable

Advanced plugin patterns — hooks, agents, MCP servers, and marketplaces

Master every persistence layer — CLAUDE.md, auto memory, rules, settings, and hooks — so Claude never forgets

Tame your AI agent spend — model tiers, thinking budgets, caching, and Claude Code settings that cut costs without cutting quality

A 12-minute orientation to the orchestration skill path — why it exists, what you'll be able to do, how the five chapters relate, and where to begin.

The cheapest way to multiply yourself in Claude Code — a worker with its own context, tools, and model that hands back only the answer.

The git substrate that lets many Claude sessions edit the same repo at once without ever clobbering each other's files.

Hand whole tasks off to Claude sessions that run without you, and watch them all from one board you only touch when a row needs you.

The first surface where the workers talk to each other — a lead that holds the plan, teammates who share a task list and message directly.

When orchestration outgrows a conversation, hand the plan to a script — and let it cross-check its own work before it answers you.

Orientation to the Codex skill path — what it is, how the four chapters fit together, and where to start

From zero to productive — master OpenAI's coding agent across CLI, app, IDE, and cloud

Skills, subagents, cloud tasks, and power-user patterns that maximize your Codex output

Govern Codex spend across CLI and Cloud — model routing, reasoning effort, ChatGPT tiers, per-task pricing, and caching that actually pays off

Design persistence for Codex across CLI, IDE, desktop, and Cloud — every layer that decides what survives between tasks

A 12-minute orientation to the Cursor skill path — what it is, what you'll be able to do, how the chapters relate, and where to begin.

Project rules, team rules, AGENTS.md, skills, hooks, and the pro workflows that make Cursor a team-wide platform.

Privacy mode, SOC 2, SSO, SCIM provisioning, usage analytics, model governance, and enterprise deployment patterns.

How Cursor understands your entire codebase — indexing, @-mentions, .cursorignore, and the context window budget.

Master the two features you'll use every minute — Tab's predictive edits and Chat's contextual Q&A.

Connect Cursor to external tools via the Model Context Protocol (MCP) — databases, APIs, browsers, and custom integrations.

Multi-file generation, Agent execution, checkpoints, and the edit workflows that turn ideas into shipped code.

Orientation to the Gemini CLI skill path — what it is, how the chapters fit together, and where to start

Master Google's open-source terminal AI coding agent — auth, approval modes, Plan Mode, and GEMINI.md

Subagents, extensions, worktrees, and the Jules handoff — the April 2026 power-user toolkit for Gemini CLI

Govern Gemini spend across CLI, Vertex, AI Studio, Code Assist, and Jules — 1M-context economics, Pro vs Flash routing, billing-surface choices, and budget governance

Design persistence for Gemini across CLI, parallel subagents, and Jules — GEMINI.md hierarchy, 1M-context strategies, Vertex AI Memory Bank, and async-task continuity