AI Strategy Isn’t Tool Selection

I came back from coffee with a colleague this morning where we’d been talking about AI strategy. I sat down, opened my feed, and read about the current problems at GitHub. They posted a write-up sharing recent exponential growth.

My assumption: this is an unintended consequence of AI. GitHub planned for normal growth — developers writing code at human speed, opening pull requests at human speed. AI agents and AI-assisted developers don’t operate at human pace. Demand bent past where their capacity, contracts, and internal tooling were sized to handle.

I’m also curious about the economics. Is their revenue or profit model built around an average number of pull requests per seat? If so, AI changes that math fast — same seat, many more requests, costs climbing while revenue stays flat.

So what does this mean for you?

AI strategy isn’t picking coding tools, adding workflows, implementing chatbots. You have to think deeper about your operations, your customers, your suppliers, your competitors, and your market. Your cost, revenue, and profit models.

Nobody has the answers yet — things are changing rapidly. Take time to think strategically instead of tactically about how things might impact your business.

Source: GitHub’s availability write-up

Originally published on LinkedIn — view the original post for comments and reactions.