AI Knowledge Library

How connecting your tools via MCP transforms an AI agent from a smart guesser into an informed operator — and why it's simpler than you think.

What I learned building my first AI agent from scratch — what surprised me, what I got wrong, and what I'd tell someone starting today.

How to turn Claude Code into a persistent agent using the three-layer pattern — skills for capabilities, a profile for identity, and context files for memory across sessions.

A four-phase daily workflow — morning planning, active work, afternoon review, and nightly cleanup — where each phase feeds into the next so you never start from zero.

A prompt framework that builds your daily plan around energy levels — matching deep work to peak focus, admin to low-energy windows, with an 80% capacity buffer to prevent overcommitting.

A structured prompt that generates a pre-meeting brief — who you're meeting, why it matters, what's open, and the questions you should ask.

A simple framework for sizing tasks, setting daily capacity, and applying the 80% buffer rule so you stop overcommitting and start finishing what you planned.

A data-driven weekly retrospective prompt that calculates completion rate, overcommit score, and 3-week rolling trends to surface productivity patterns you can't see in the moment.

A terminal-based AI executive assistant built on Claude Code that manages your day, tracks tasks, preps meetings, and keeps you accountable.

An automated workflow that scores inbound leads based on firmographic data and engagement signals.

A Claude prompt that generates personalized cold outreach emails based on prospect LinkedIn data.

What this library is, why it exists, and how to use it.