AI Impact HubFor the person with forty open tabs about AI and no idea which one matters.
Try it right here ↓Free to read. The try-it part runs on a free account.
There is more AI news every week than anyone can hold. The self-learning system is a project that knows who you are, what you do and which tools you use, so when something new appears, you feed it in and force a decision: ignore it, park it, test it or adopt it. Sometimes the answer is ignore it. That answer alone pays for the setup.
The setup is one project that knows you: your role, your organisation, the tools you already pay for. Have the AI interview you, drop in the strategic plan and last year's impact report, and that context becomes the engine everything else gets read against.
Then the habit. Anything you come across, a video, a release note, a new model, goes in with one question: based on everything you know about my work, my tools and my role, does this apply to me, and where would it give me value?
The best answer is often no. Do not bother watching it, there is nothing in there you do not already do: 45 minutes handed back. And when something does matter, the system does not summarise it. It walks the idea into your own work, which no summary ever did.
Every source gets read against your work rather than against the general public, and comes back with a decision: ignore, park, test or adopt. The ignores are what make the system pay for itself.
This does something else. It takes the idea and walks it into your week, your tools and the report you already have to write.
The whole loop, working: build the context, decide what deserves attention, plan a safe test, save what worked and set the review. Then two more prompts for the habit around it.
Five steps, one real source. Your answers stay on this device.
Work through one real source. The loop only keeps what you choose to keep, and your answers stay on this device.
Review what it knows. Correct what it assumes. Add what is missing. Tap a chip and write one line.
Using the information already available in this project or workspace, create a Personal AI Context Profile that will help you evaluate new AI tools and techniques against my real work. Include my role and organisation, current priorities and projects, recurring tasks and workflows, tools and systems, constraints, policy or privacy boundaries, working preferences, and success measures. Separate confirmed facts from assumptions. Flag anything uncertain or outdated. Ask no more than five questions to fill the most important gaps. Do not invent details. Show me the draft before saving it.
Copying adds whatever you wrote above, so the AI starts from what you already know.
The coach that starts the whole thing, and the monthly look at how you actually use AI.
Run both inside a project that holds context about you.
Based on everything you can find in this project, I'd like you to coach me in adopting AI. Ask me one question at a time until you have enough context about who I am and the work that I do. Then use everything you have access to to design a personalised AI adoption plan for me and my organisation.
The adoption coach. Run it inside a project that holds context about you.
The guide is free to read. This part is a working exercise, and a free account opens it and keeps your progress across the Hub.
The line the theme grew from, “you don't need an AI strategy, you need an AI learning system”, is Nathaniel Whittemore's, on the AI Daily Brief.
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