You have to pay a price for your distinctiveness, and it’s worth it.
The fairy tale version of “be yourself” is that all the pain stops as soon as you allow your distinctiveness to shine. That version is misleading. Being yourself is worth it, but don’t expect it to be easy or free. You’ll have to put energy into it continuously.
The world wants you to be typical – in a thousand ways, it pulls at you. Don’t let it happen.
What is a webinar in the age of AI?
It’s a blog post. And a podcast. And a video. And a meme.
Let me explain.
For many webinars, I’ll send a notetaker in my place, a robot to record the conversation & summarize it in the way I ask. A personal journalist in a sense.
Instead of watching & listening to a conversation, I’m transmogrifying the subset of the content that matters to me into the format I prefer : a summary in a template, in other words, a blog post.
I remember the day I received it : my first Blackberry. A few weeks later I lost it in the back of a taxi cab in Paris. But I haven’t forgotten the chiclet keyboard, its subtle click with each keypress.
A year later, the iPhone presented the world with an all glass keyboard. Who would type on a flat surface, detractors asked? In the end, all of us.
This week, I saw another user interface for a phone : dictation only.
Is tech M&A back?
Google announced its intention to buy Wiz for $32b today. If approved by regulators, it would be the 6th largest technology M&A ever.
This transaction would make Wiz the 5th most valuable pure-play security company.
For Google, this would be its largest acquisition ever second to Motorola for about $12b. Notably two of the top three acquisitions are security. Mandiant sold for $5.4b.
Engineering teams within AI application startups are much smaller than a classic software company - maybe half the size or less.
Let’s run an experiment : let’s assume every public software company benefits immediately to the same extent & cuts R&D spending by half.1
How would the value of these businesses change?2
72% of unprofitable SaaS companies would become profitable.
Public SaaS companies’ growth rates have halved since 2023, as David Spitz pointed, from 36% to 17%.
Why? There are few, fast growing, younger SaaS companies to sustain the growth rates.
The top quartile companies are growing at slower rates today than the bottom quartile companies in 2016. The median has never been lower in the last ten years.
Monday’s analysis cost about 27 cents to produce.
This little screenshot is of Claude Code, the product I use now to write the analysis of datasets like estimating the value of a venture firm.
I didn’t expect to find this feature initially as useful as I do now.
But it makes me feel great because of how inexpensive it is to be productive. 27 cents for a statistical analysis of a small dataset is a bargain considering the battery of statistical tests the AI applied.
How do you position and scale an AI company in a rapidly evolving market?
Join us for an in-person Office Hours session in San Francisco with Alan Hsia, VP of Marketing at Fireworks AI.
Alan brings deep expertise in go-to-market strategy and will share insights on:
📅 March 25, 2025, 5:30pm
📍 San Francisco
🔗 Register here
A small spin-out from a publicly traded behemoth launched with the ambitious vision of transforming their entire industry. Within just a few years, as capital markets shifted in their favor, they emerged simultaneously as both innovators & titans in their field.
We don’t often think of private equity this way, but that’s exactly what happened when KKR spun out of Bear Stearns and Michael Milken at Drexel Burnham Lambert catalyzed the junk bond boom of the 1980s.
Imagine if every time you edited a document, the word processor forced you to retype everything that had been written before that edit.
How expensive would that be for a company?
This is exactly how data transformation works today. Each time a data engineer modifies some part of the data stack, the Cloud Data Warehouse & its transformation layer recalculates everything.
What if the system were designed so that it only recalculated the metrics needed? How much less expensive would it be?