The AI source-of-truth map
A practical map for connected AI workflows: decide which app owns the truth, what AI may read, what it may draft, and what needs approval.
Read the skill →Skills you can copy. Case studies you can learn from. Sorted newest first.
A practical map for connected AI workflows: decide which app owns the truth, what AI may read, what it may draft, and what needs approval.
Read the skill →A practical map for choosing AI workflows by role, so teams focus on repeated inputs, useful outputs, review points, and measurable adoption.
Read the skill →A practical scorecard for proving whether AI is improving a workflow, not just increasing tool usage or creating faster first drafts.
Read the skill →A practical brief for asking an AI coding agent to build a small internal tool, spreadsheet helper, data cleanup script, or workflow automation.
Read the skill →A practical checkpoint for reviewing AI-generated plans, tickets, documents, and follow-ups before the team acts on them.
Read the skill →A practical habit for reviewing what an AI agent is about to read, click, write, send, or change before it touches real tools.
Read the skill →A practical checklist for deciding whether an AI agent is ready to share with a team, schedule, or connect to real business systems.
Read the skill →A 20-minute review loop for turning casual AI use into stronger prompts, safer workflows, and one concrete skill upgrade each week.
Read the skill →A prompt pattern for checking AI recommendations before spending money, changing plans, or acting on a suggested decision.
Read the skill →A practical decision ladder for choosing fast, focused, thinking, or expert AI modes based on task risk and consequence.
Read the skill →A practical checklist for reviewing which apps, files, inboxes, calendars, and business systems an AI assistant can access.
Read the skill →A prompt pattern for giving AI a goal, success criteria, non-goals, evidence, and final review report before it starts long work.
Read the skill →A practical checklist for using AI agents safely when they read webpages, emails, documents, reviews, or tickets.
Read the skill →A practical checkpoint for guiding AI research agents before they gather sources, write reports, or make recommendations.
Read the skill →A prompt pattern for turning AI meeting transcripts into decisions, owners, risks, and follow-ups people can trust.
Read the skill →A practical template for turning repeated prompts into reliable routines with cadence, inputs, output shape, and review rules.
Read the skill →A simple review pattern for deciding when an AI assistant may draft, stage, click, send, update, or stop for approval.
Read the skill →A compact delegation template for giving AI agents scope, checks, and stop conditions before they touch real work.
Read the skill →A compact note pattern for carrying context, decisions, constraints, and risks across AI sessions.
Read the skill →Connected AI can search your tools. This prompt makes it show the evidence map before it writes the answer.
Read the skill →Enterprise AI is moving from tools to workflows. Use this short brief before delegating recurring work to an AI agent.
Read the skill →Today's AI news is full of agents connecting to business tools. The useful skill is learning where to put approval gates before anything sends, pays, posts, or updates.
Read the skill →A copy-pasteable prompt that turns your week's bullet points into a concise, audience-calibrated update — without writing a word of it from scratch.
Read the skill →A repeatable prompt and routine for letting an LLM cluster, prioritise, and draft replies — without handing it your credentials.
Read the walkthrough →The actual tools, prompts, and review steps Mei used to turn 40 user interviews per quarter into a tight insight doc — with citations.
Read the case study →One prompt, three inputs, four outputs. The single habit that buys back the most calendar pain for the lowest setup cost.
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