AI turns products from deterministic functions into probabilistic systems. That requires expanding old playbooks (SLOs, funnels, siloed finance), and reasoning in terms of trajectories, Minimum Viable Intelligence thresholds, and data as company operating system.
What will the next wave of generational companies look like? What’s the shape of fund returners going to be, in the next decade? How will they affect startups formation and funds performance?
Some big news to share. I’ve been granted an O1 visa for extraordinary abilities, and i'm moving to NYC. Who would have thought that a random guy from a small Italian town would end up living in the US? and yet!
I have yet to find a sucessful ed-tech model that works at scale. Issue abound. Often it comes down to how ed-tech growsn and how it monetizes its audience. Let's start with growth:
This is an old story about love, hacking, and bad UX. An Odyssey of getting cut off my Instagram account, fighting to get it back, and ending up falling in love.
Replit is blurring the lines between localhost and staging environments, between coding and shipping, thinking and making, learning and building. The Bundling of Software Development.
One of the biggest pitfalls of OKRs is that they make life… a little bit stressful. After using them for the better part of 2020, I decided to make some changes. Enter: TAHs.
Online content makes edutainment the norm among curious and intelligent people, who don't realize that they aren't actually learning what they think they are.
Founders want speed. Devs want careful planning. The tension can be looked as a variation of the exploration-exploitation trade-off, and its mathematical solution shows an Ebb and a Flow of Product Development in early stage startups.
First-time CTOs with a good dev background and no startup experience prioritize scalability and robustness over deployment speed. A few ideas to change approach.