AI for Leaders
We build project management skills and workflows for several clients, and we use them internally too. The three we're showing here take real time off the parts of the job that eat the most hours: getting ready for meetings, keeping status current, and kicking off new projects.
One preps you before every meeting and turns the transcript into notes and action items in Trello or Notion afterwards. One reads a project's scope of work, checks it against similar past projects in the company's knowledge base, and once you pick the closest match, fills in the kickoff template. One pulls task status from Trello, GitHub and wherever else the work lives, checks it against the plan, and drafts the report.
You do not need to be using AI already to follow this. None of it lives in a clever prompt one person happens to be good at either: each is a defined workflow, same sources, same review step, same output, that any project manager on your team can run and get the same quality from.
We'll show both AI-assisted and agentic versions of these workflows. Assisted, a person still checks the notes, picks the template, and reviews the report before anything goes out. Agentic, the workflow writes to Trello, Notion, GitHub or your project management tool on its own.
We will show it all running, say where it fails, and be specific about what has to be true before you make that move.
We'll show the workflows running against real project documents, and the questions that decide how far you can take them.
You do not need an AI setup to begin. We show where AI earns its place first: the meeting nobody has time to prep for properly, the status update that eats an afternoon, the kickoff pack.
A prompt lives with one person. A workflow is a defined task, with its sources, its output and its review step, that any project manager on your team runs the same way and gets the same quality from.
Right now a person approves every output and nothing writes back. We show what changes when these workflows start acting on their own, what that asks of your governance, and how to tell when you are ready for it.
Running projects day to day, with or without AI in the mix today.
Responsible for how projects run across teams, and for making good practice stick beyond the keen individuals.
Project delivery is your constraint and you want a clear read on what AI changes about it.
Deciding how far to let agents act inside the tools the business already runs on.
We build these skills and workflows for several clients, and use them internally too. What you'll see here runs against real project documents, not a demo dataset. We show where it fails too.
We start from the work a project manager already does. If you have only ever used AI for the odd summary, this session is still built for you.
Where a human still approves, why we stopped short of writing back to a system of record, and what would have to change to move that line.
Sixty minutes, forty five of content and fifteen of questions, dense with working examples.
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