Upskilling for what comes next
From asking a chatbot to deploying a colleague
You have the tools. Maybe you even have a few people making progress on their own. But for most teams I work with, AI still means copy-pasting between tabs and using someone else's prompts. And the hardest part of leveling up from there is figuring out where to start and what's worth the effort. I help teams answer those questions, then build alongside them.
Where are you right now?
Chat
You ask, AI answers. Useful, but it still feels like a search engine.
Context
You’ve built custom bots that know your work. Tailored, but you’re still driving every interaction.
Automation
AI handles defined tasks in the background. You review and approve.
Colleague
AI operates as a team member managing tasks, making calls within boundaries you’ve set.
If you’re at level 1 or 2, you’re in good company: that’s where most teams are. The gap to Colleague looks huge. It isn’t, but you need a clear process to get there.
How I take you where you want to go
Map
Before we touch any AI tool, we map your team’s workflows. Starting with the repetitive workflows that everyone wishes they could delegate, we lay out the tasks required and answer key questions. Where does data come from? Where does output go? What’s the work that eats your week but doesn’t use your best thinking?
Test
We start small. Maybe it’s one task (a real one, with real data) where we test the best way to get AI on the playing field. Maybe it’s a short series of tasks with clear checkpoints where you review and approve before anything goes further.
Integrate
Once you know what works, we connect and expand. We plug into your tools and data sources. We make it accessible to everyone across the org who needs it and flesh out your team’s quality standards. This is when it stops being a side experiment and becomes part of how your team actually operates.
Compound
Much like a trusted colleague, your AI-powered system should get better and better the longer you work with it. We will build in a continuous improvement loop so feedback gets routed back to the system and the outcomes improve the more you use it.
Three ways in
Learn for free
My video tutorials and newsletter put this process to work on real tasks at every level of the Chat → Colleague scale. Subscribe to get practical AI for knowledge workers who hate hype.
Workshop
A single session or series where your team augments a real workflow with AI. You leave with something that works, not a slide deck. Excellent for teams ready to move from Chat to Context, or from Context to Automation.
Embedded consulting package
All four steps — Map, Test, Integrate, Compound — deployed across your team, wherever you are on the Chat → Colleague scale. We map every task, identify the opportunities with the biggest impact, build custom tools connected to your data and conventions, and train internal champions to keep it running and improving. This is how you get to the Colleague level.
Working solo?
If you’re an individual — a founder, creator, or operator building your own AI workflows — I also offer limited 1-1 coaching. Same process, tailored to your setup.
What people are saying
Are you ready for what comes next?
Hi, I’m Louise, founder of Cleverest.
For several years now I’ve been working on a book called From Romans to Robots. It chronicles my learnings from teaching university-level Greek and Latin to leading robotics training programs. The TLDR: Whether it’s ancient languages or the future in motion, I’m really good at helping people master systems that scare them.
I’ve been working with AI since before ChatGPT existed. Back in 2019, I was building chatbots with Google’s Dialogflow to support online learners. They were primitive looking through today’s lens, but they worked.
I’ve led AI workshops that turned skeptical teams into confident builders, developed custom automation workflows that collapsed months of manual work into hours, and trained everyone from startup founders to enterprise teams on how to stop talking about AI and start shipping with it.
My own business also runs on AI. Every system, every workflow, every recommendation I make has been battle-tested in my own operations. Because if it’s not good enough for me, it’s not good enough for you.
