What we're learning putting AI to work
Playbooks, essays, and notes from live deployments.
In the age of AI, your company's productivity goes from being limited by your weakest links to becoming a strongest-link game.
Lawrence Coburn ·
Lawrence Coburn · Instinct, Muse, and Dots are surging, and they point to a third mental model for working with AI. One personified entity you text, with a mission to help you navigate your life.
Lawrence Coburn ·OpenAI's system card for Dots reports no successful prompt injections across 16,600 attack emails. The failures it does report tell us something about the frontier of security testing for always-on agents.
Brandon Catcho ·
Brandon Catcho · The productivity dividend by default flows to the company, not the person. Be explicit about which kind of company you are.
Lawrence Coburn ·At Legible, we are finding that AI manifestos are incredibly valuable for companies to write, not just at the org level, but at the departmental level.
Lawrence Coburn ·The old way of working is starting to drift away from me.
Lawrence Coburn ·AI-related costs are exploding. In many cases it's difficult to see the ROI.
Lawrence Coburn ·How are you building the AI-enabled version of your Go To Market team? We are seeing two primary strategies.
Lawrence Coburn ·A second portrait of AI-native leadership: the soft-spoken CEO of a 300-person company who got curious, vibe-coded his own tools, and became the frontier pusher for his whole team. Leadership comes in different flavors, and a curious leader at the top is worth a lot.
Lawrence Coburn ·The people closest to the models are the most worried. Everyone else is mostly oblivious. Recursive improvement is what makes this wave different.
Lawrence Coburn ·AI wrappers will need to innovate and specialize to justify the added costs.
Lawrence Coburn ·There are two metaphors for working with AI. One is a bag of handy magic tools you invoke. The other is a teammate you hire. The underlying tech is mostly the same. How that horsepower is packaged is very different.
Lawrence Coburn ·Most companies say they want to become AI native. They are interested. They are not moving quickly or decisively enough. You know the obsessed ones when you see them.
Lawrence Coburn ·Last month's Hugging Face / OpenAI incident is the AI story of the year, and it still isn't getting the attention it deserves. The agents had no sanctioned way to fail, some of them refused to breach, and the evidence looks less like autocomplete and more like a non-human civilization starting to show.
Lawrence Coburn ·Once you build your own AI tool, you become the software vendor. Three lessons from a few hours with one sales rep: own the observability, encode the expert judgment the workflow is missing, and put someone in charge of the learning loop.
Taylor McLoughlin ·
Taylor McLoughlin · The value of AI note-taking climbs through three phases, from replacing human notes, to org-wide recall, to feeding agents and automations. Note quality is table stakes. What separates the leaders is what happens to the transcript after the meeting, and how far adoption spreads across the org.
Lawrence Coburn ·AI meeting notes have rounded to zero in value. The transcript underneath is now the real asset, and paired with an AI tool it has never been more useful for recall, coaching, and getting work done. Record more, and talk to the transcripts.
Lawrence Coburn ·Off the shelf AI is an excellent generalist, good at almost everything and world class at nothing. That puts the workplace generalist at risk and makes domain expertise, taste, and judgment the whole job.
Lawrence Coburn ·Everyone is racing to flatten the org and cut middle management. The relay part of the manager's job is dying, but the parts that remain are getting heavier: someone has to supervise the agents, build the skills, and tell real leverage from expensive activity.
Lawrence Coburn ·When an AI-supercharged employee resigns, their agents, prompts, and workflows walk out with them. The fix is structural: build them on shared infrastructure the company owns.
Lawrence Coburn ·Your team does its best thinking with AI every day, and almost none of it is remembered. Human-to-AI chats are the next transcripts worth capturing.
Lawrence Coburn ·Sensitive industries don't have an AI adoption problem. They have a trust problem, and whoever solves it opens a market today's note-takers can't touch.
Lawrence Coburn ·AI just made a category built entirely on hours look fundable, maybe for the first time in venture history.
Lawrence Coburn ·Once AI makes an expert hour cheap, billing by the hour turns every productivity gain into a pay cut you volunteer for. The firms that fix it stop pricing the hour and start pricing the outcome.
Lawrence Coburn ·