FOMO, Audacious Leadership, Pre-Product Market Fit (Startup Observations #2)
A short newsletter to VC, Investor and People Ops folks I have connected with. My intention is to provide a regular update on the human issues I’m seeing show up in the tech leaders and organizations I work with.
FOMO ("He has a house in Cabo”)
“He has a house in Cabo”, says one client. “They don’t seem to have any of the internal problems that we do”, says another. “We only grew at 90% this year”, says a third (I gently point out that 90% growth is ... really pretty good).
The truth is that it's always hard. The myth is that other people hit it big effortlessly, without friction. But nobody writes a substack about their embarrassing faceplants, their ugly messes and their 4am fears. In the current AI world the successes look enormous and instantaneous (some of them are). But that's from outside. You don't know the inside Comparison with a public highlight reel is useful as a reminder to check, carefully, what you’re actually building and why and ground yourself in the next step forward. But that’s all.
Audacious Leadership Works for AI Behavior Change
“The team came to me and said that the new feature would take two weeks. I’d spent the weekend using the new coding tools, so I had a feel for them. I told them they had four hours. They were back that afternoon with the feature” CTO client.
Audacity in leadership - the right push at the right time - is a skill I love to see, and nurture, in my clients. If the CTO had said a week, the team would have taken a week. Sitting through an AI demo is not the same as direct experience. Having the team build in hours not weeks makes the point. The speed of AI adoption rewards audacious choices.
The Revolution Seems Pretty Quiet
“We just post a feature we want on Slack, talk about it, copy Cursor in, and it gets done”, Startup PM Client, San Francisco
I have been surprised by how quiet the AI revolution seems in product and engineering. This is the first substantive change in how software is developed in over fifty years so I would expect more turmoil. Maybe it’s the people I work with, but aside from occasional sticky patches (usually overcome by a carefully timed push - see above), product and engineering orgs are rapidly adopting the new tools and seeing immediate benefits. Compare this to the introduction of Agile practices back in the day, which were often laborious, painful and incomplete.
Playbook vs Canvas - Generative Rather Than Convergence Thinking
“I keep saying - we have a set of playbooks. We need a canvas. Or a lot of them”, SAAS Client
In the last twenty years or so, we have created playbooks: for SAAS, for Product/Engineering relationships, for design and prototyping and on and on. With AI tools we have a canvas (or set of them): a place to play, experiment, draft and redraft. The tools encourage a generative rather than converging approach. “Let’s try…” vs “the next step in the process is…”. Which means a looser sense of iteration and process. This fires up the more open-field people in a team, and can make the process-oriented pretty uncomfortable.
Pre-Product Market Fit is Hard
“We just don’t know when it’s going to work” Multiple clients at different times
Pre-product market fit is a kind of limbo. You keep working (hard), sending emails, taking meetings. Potentual cusotmers are polite, interested, bit nothing really hits. Or worse, it looks like it hits with a customer or two, and then it doesn’t. Searching for PMF is a prime period for FOMO (see above) and doubt. There isn't a fix here except persistence. It’s a case of believing in what you're doing, loving what you're building and listening, carefully. Often this period is what separates real founders from the rest of humanity. They just keep going.
I coach founders, CEOs and execs in rapidly scaling startups. Interested? Get in touch.