Musings

Startup paradoxes

Every list of startup advice contradicts the last one you read. Be patient but move fast. Stay focused but stay open. Hire slowly but scale quickly. After a while you start to think the real lesson isn't in any individual piece of advice — it's that following any one of them too religiously is what kills you.

Compounding returns of AI workflows

Using Claude Code daily for as much of your work as possible creates compounding returns that are hard to see at first. Once your plans, preferences, brand kit, past work, and key numbers all live in markdown, every next task gets incrementally easier. That benefit compounds into a system where everything becomes dramatically more efficient. The longer you wait to start building that system, the more ground you're giving up.

Creative flow state and AI

AI has completely changed where the real work happens for me. I spend two hours on a walk with Wispr Flow, getting ideas down on my phone in a stream of consciousness — speaking at three times the speed I could ever type. The creative thinking and the flow state are the hard bit now. The execution is the easy part once you're back at your desk with your terminal window open.

Age of the generalist

I'm slightly tooting my own horn here because this describes my background, but I genuinely believe this is the age of the generalist. The people I've always looked to hire are the ones with a logical brain, a habit of tinkering with tech tools, and the ability to operate well across product, engineering, and commercial work. A broad base of knowledge across many domains, combined with strong technical ability, can turn someone into a 10x or 100x contributor — especially now that AI handles so much of the deep specialist work.

Software engineering in nine months

Software engineering as a profession won't look anything close to what it looks like today nine months from now. The same is true of product management and most other roles that sit between an idea and its execution. The people who adapt fastest won't be the ones defending their job title.

Small teams, good people

Right now, a small team of exceptional people with strong horizontal knowledge across many domains will outperform a larger, less AI-fluent team every single time. The economics of headcount have fundamentally shifted and I think most companies are still staffing for the old world.

Taste as the bottleneck

When implementation becomes nearly free, the bottleneck shifts entirely to taste and judgement. Knowing what to build, and what to say no to, matters far more than knowing how to build it. The best founders I know have always operated this way — AI just made the gap between them and everyone else more visible.

AI fluency as baseline

At some point the conversation about AI at work shifted from "should we try this?" to "why aren't you already using this?" One major company now requires managers to prove AI can't do a task before they're allowed to hire for it. The gap between people who've embraced these tools and people who haven't is widening every week.

The gentle shift

The most remarkable thing about this AI shift might be how unremarkable it feels day to day. What was mind-blowing in January becomes a default expectation by June. You only notice how much changed when you look back.

English as programming language

We've quietly entered a new era of software where the interface is just English and the building blocks are autonomous agents. The most important programming language of the next decade might just be clear, precise prose.

Writing is thinking

As AI handles more of our writing, people will quietly stop learning to do it themselves. But writing is how you learn to think clearly. Outsource the writing and you risk outsourcing the thinking along with it.

Startup Zen #1 — Shoshin

Shoshin — beginner's mind — is probably the most useful Zen concept I've come across as a founder. The moment you think you've figured out your market is usually the moment you stop listening to it.

Startup Zen #2 — Kanso

Kanso is the Zen aesthetic of simplicity — not minimalism for its own sake, but the discipline of stripping away everything that isn't essential. Jobs took this literally, saying no to hundreds of product ideas so Apple could focus on a few. Most product teams I've worked with could do with that kind of ruthlessness.

Startup Zen #3 — Non-attachment

Zen teaches that clinging to outcomes is the root of suffering. In startups, I keep seeing the same thing — founders who won't let go of their original product vision when the market is clearly pointing somewhere else. Listening requires letting go first.

Economic signals

Most AI predictions are based on benchmarks and demos. The more interesting signal is what's actually happening in the economy — businesses forming faster, scaling faster, and reaching milestones in months that used to take years.

Roles dissolving

The walls between product person and technical person are coming down fast. When a product manager can build a working prototype in fifteen minutes and an engineer can test product hypotheses at near-zero cost, the old job titles start to feel like artificial boundaries.