What we're learning putting AI to work
Playbooks, essays, and notes from live deployments.
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 ·
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 ·