Thomas opened by interrupting his own talk. He had two things to do first: answer an email from Julian, who wanted a team ticket for Just Product and needed an offer to start his purchasing process, and act on Sebastian's complaint that the website button was boring. He typed both requests into chat, asked for three playable button prototypes, told the AI not to ask questions and let it run. Then he explained the year behind that casual move. In October 2025, at a client hackathon, an engineer and product manager interviewed a colleague, pulled the photo book selection algorithm from GitHub, brainstormed changes with AI and had a prototype in two hours. That used to take Thomas four weeks. He went home convinced everyone was going to be replaced.
The second moment came at the end of January. Thomas, who has never written a line of code, built a working app for a side business over one weekend, with filters, a map and listing pages. Sebastian, a software engineer, asked how long it took and estimated two to three months for himself. From then on the two co-founders agreed they had a problem, including the uncomfortable question of whether anyone would still come to the Product Masterclass if AI can explain everything. At the same time, daily work looked nothing like superintelligence. A voucher request meant hunting through Eventbrite, checking Fastbill, downloading a PDF and drafting a mail. Twenty to thirty minutes, or two days of putting it off.
So they decided to automate every workflow. Publish a blog post: does Webflow have an API? Build a skill. Write an invoice: does Fastbill have an API? Connect it to Claude, build a skill. Tools without full API access, such as the newsletter tool and the old website builder, got replaced with ones that had it, and some were replaced with self-built applications. Step by step that became the Product Masterclass operating system: connections to tools and GitHub repos, the business context, and skills that encode the processes, all handed to an agent. Back on stage, the first task was done. The AI had created the Eventbrite voucher, looked Julian up in Pipedrive, created a five ticket offer in Fastbill and drafted the Gmail reply.
Thomas counted the gain: five to ten times faster for that one chore, and they have around 46 such skills. The bigger effect is new capacity. After each participant's half hour review call, the AI turns the recording into an alumni story page, picks the angle and the video segments, cuts the clips, writes subtitles and the blog post. Two hours on the side instead of three days of focused work. Questions like who visited the website or whether someone is already registered get answered on the spot. Then the second live result: three button prototypes, the audience voted for the third, and Thomas told the AI to write a ticket, implement it and push to main, with 250 people as QA. Normally two sprints.
For product managers the recipe is short. Connect your AI to Jira, Confluence and GitHub and you have a first product operating system. AI will not replace PMs, but PMs who use AI will replace those who do not. Sort your workload into protect, augment and automate, master the protected part (customer understanding, strategy, product sense) and automate the rest. Fundamentals matter more than ever because AI is a lever: a fool with a tool is still a fool, a great PM with AI feels superhuman. The new job looks like a three star chef at the pass, inspecting every plate the agents cook and sending back anything with a hair in the soup. Master AI in your field, and remember a tiny team can have huge impact.
