AI won't just change what you do - it'll change what your company looks like

Friends,

your weekly AI briefing is here - designed to help you respond to AI, not react to the noise. No curveballs. No chaos. Just clarity.

🎓 Want to give your leadership team the headspace to think clearly about AI?

Our AI strategy workshops use a "superpower framing" - your team solves real business problems by imagining superpowers, not wrestling with technology. It works. Teams leave with a clear, prioritised action plan they actually own.

👉 Book a free discovery call and let's find your starting point.

📰 This was the week that was...

This was the week that AI stopped being about adding a tool and started being about redesigning the whole company.

European AI lab Mistral launched Forge, a system for enterprises to train frontier-grade AI models on their own proprietary data - partners already include ASML, Ericsson, and the European Space Agency. And Manus (now owned by Meta) released My Computer, a desktop app that brings AI agents out of the cloud and onto your laptop - reading files, controlling apps, running multi-step tasks locally.

The direction is clear. AI is moving from something you log into, to something that lives inside your business - in your data, on your machines, embedded in your workflows. The question for leaders is not "should we use AI?" but "if we were designing this company today, would we design it the way it currently exists?"

Let's get into it.

🔥 Urgent Priorities

✅ No fires to fight this week

✅ The shift from "AI as tool" to "AI as operating model" is accelerating - this is strategic, not tactical

✅ Time to move from Job 1 (understanding AI) to Job 3 (reinventing the business)

This isn't a week for panic. It's a week for sketching what your company looks like if you started it tomorrow.

🎯 Strategic Insight

Tension: There are three jobs every business needs to do with AI. Job 1: create the headspace to understand it. Job 2: make room in the P&L by using it. Job 3: reinvent the business itself. Most organisations are still on Job 1 or Job 2 - and that's fine. But this week's news makes it clear that the leaders pulling ahead are already on Job 3. If you were designing your company today, would you design it the way it currently exists?

Optimistic insight: Stuart Winter-Tear's Unhyped AI newsletter introduced a phrase worth borrowing: "tolerated vagueness". Most firms survive on it - ownership is supposedly clear, escalation paths are supposedly known, exceptions are supposedly handled. People absorb what the formal system never resolved. AI exposes all of it. That's uncomfortable. But it's also an extraordinary opportunity. Because fixing those gaps doesn't just make your AI work better - it makes your whole organisation work better.

What's shifting: The smart question is no longer "How do we bolt AI onto our existing structure?" but "What would this company look like if we designed it today?" Fast Company argues that AI doesn't just automate tasks - it exposes how much of an organisation's structure existed to compensate for inefficiency, fragmentation, and internal inertia. That's a mirror most boardrooms haven't looked into yet.

Why this matters now: If you only plan for "AI as a productivity layer", you'll likely optimise a structure that's already outdated. If you instead plan for "AI as redesign catalyst", you get three benefits: a leaner cost base, faster decision-making, and a business that's genuinely hard to compete with.

👉 Takeaway: Block 90 minutes with your leadership team this month and ask three questions:

• If we were founding this company today with AI available from day one, what would we build differently?

• Where in our business does "tolerated vagueness" slow us down most?

• Which of our processes exist because coordination was expensive - and what happens when it becomes cheap?

If you'd like help facilitating that conversation, reply and we'll set up a workshop.

🤓 Geek-Out Stories

1️⃣ LumberChunker: every frustration you have with AI is being worked on, every day

Researchers at Carnegie Mellon published LumberChunker, a new method for splitting long documents into meaningful chunks for AI retrieval. Instead of chopping text at arbitrary points, it uses a language model to find where the narrative actually shifts - producing chunks that preserve context and meaning. In benchmarks, it significantly outperformed every other approach tested.

Why it matters: If you've ever asked an AI a question about a long document and got a vague or wrong answer, this is why. The way AI systems break up your documents before searching them has been a quiet bottleneck. LumberChunker is one example of a much bigger pattern: every frustration we have with AI today is being actively worked on. The tools are getting better, fast. And the organisations that are already building their AI capability are compounding their advantage with every improvement.

👉 Action: Next time your team says "AI can't handle that" - pause and check. The limitation they hit three months ago may already have a solution. Build a habit of revisiting what's possible every quarter.

👉 Read the CMU research

2️⃣ MiroFish: predicting the future just got more human

MiroFish is an open-source AI prediction engine that takes a radically different approach to forecasting. Instead of crunching numbers in a spreadsheet, it spawns thousands of AI agents - each with unique personalities, memories, and perspectives - and lets them interact in a simulated world. Opinions shift. Coalitions form and break apart. What emerges is a prediction that accounts for the messy, social reality of how humans actually behave.

Why it matters: Traditional forecasting treats the world like a maths equation. But business decisions play out among people - customers, regulators, competitors, staff - who react to each other in unpredictable ways. Tools like MiroFish are early building blocks for much, much better predictions. In a world of increasing uncertainty, the ability to model scenarios that include human messiness is becoming a genuine competitive edge.

👉 Action: Pick one strategic decision you're facing this quarter and ask: "What would change if we could simulate how our customers, competitors, and regulators would actually react to this?" That's the direction forecasting is heading.

👉 Explore MiroFish on GitHub

3️⃣ Comprehension debt: the hidden cost of AI-generated code

Addy Osmani (Google engineer) published a sharp piece on comprehension debt - what happens when AI generates code faster than humans can understand it. An Anthropic study found that engineers using AI for code generation scored 17% lower on comprehension tests than those who used AI to ask questions and explore trade-offs. The tests pass. The velocity looks great. But nobody truly understands what was shipped.

Why it matters: This isn't just a developer problem. It's a leadership problem. As AI generates more of the work - reports, analyses, strategies, code - the role of the leader shifts from "producer" to "comprehender". The checks and balances matter more, not less. Are you building the governance to match?

👉 Action: Ask your technology and operations leads: "What percentage of our AI-generated output do we genuinely understand? And what's our plan when something breaks that nobody can explain?"

👉 Read the full piece

🎨 Weekend Playground

This weekend, try Gamma, the AI-powered design tool that turns prompts into polished presentations, documents, and landing pages.

Gamma has recently been upgraded with new templates and now connects directly with Claude via its MCP integration - meaning you can research and create a presentation in one seamless flow. Give it a messy set of notes and watch it produce something you'd actually be happy to present on Monday.

Why this matters: The cost of creating a polished visual output is collapsing. What used to take a designer half a day now takes five minutes and a decent prompt. That's the "cost of doing approaching zero" principle in action.

👉 Mission:

• Create a 5-slide deck summarising your team's top priorities for Q2

• Try at least three different themes and see how the framing changes

• Ask it to generate a one-page document version of the same content

• Share the best version with a colleague and see if they can tell it was AI-made

• Bonus: connect Gamma to Claude and try creating a deck from a voice note or messy brief

📢 Share the Optimism

If The AI Optimist helps you think more clearly, forward it to someone else navigating the shift. If it's not quite landing, hit reply and let me know - I read every message.

Stay strategic, stay generous.

Hugo & Ben