
Art credit @Madison Harney
Spark of the Week
This week I had two big meta themes in focus -- Emerging organization models and AI Security reality.
Emerging org models - Founder Mode (sub-plot Dorsey Mode) vs. Grower Mode
Founder Mode v. Grower Mode
In Sept 2024 Paul Graham wrote a point of view about founder mode. Last week Jack Dorsey took this to the next level (h/t Brian Halligan for "Dorsey Mode") - then Postman piled on I expect we will see more of these as the year progresses.
Amy Wilson and I have a few thoughts on that topic summarized here and here.
The bigger point I'd like to push on, is that yes the need to re-think organization structures and operating models is real and urgent. This is an opportunity to re-evaluate not only how we optimize with technology, but also how we expand execution modalities to deliver business strategy. We only get to the next level value when we are very clear on the purpose. We need a yes... and, approach here, where we are not just focused on removing cost and complexity, but that we are also asking what new things can we create.
This is why I'm in the camp of Amy Wilson Grower mode. Lean on that mode to build new paths to growth. This is a moment where culture has an outsized role to play. CXOs who lean in on intellectual humility will have a material edge.
AI Security reality
Prevention alone is no longer sufficient
This week has also elevated the conversation of security supply chain attacks from theory to reality. This at the same time that Anthropic announced the delay of their Mythos model due to the expanded security risk (and the creation of project Glasswing to give everyone a fighting chance). Taken together it becomes clear that thinking of security posture as a prevention activity is an existential risk.
The probability that you will have an incident even if you do things right is very high. It's time to recognize that every software business needs to improve their incident readiness protocol.
Reading and Pondering
Who isn’t marrying (and why) - an insightful piece that shows the data that it’s actually non college women (oopsie I guess you can’t blame ambitious career women after all) – in fact, if we want to fix marriage we need to invest in marriageable men. Now I’m outside of this demographic too long to have much more to say on specifics here, (although I do have some things I would encourage my kids to value in a life partner in case anyone is in need of a target list). A long way to say, that Scott Galloway is on to something (for all the irritation I have on his views about childbirth) … I think this is a solid reminder similar to the ATM narrative in Issue 17, that much of what we believe we know about things might not be right and we should check.
How markets might change with agents. – once again it makes me ask a different question - are we thinking too small when we imagine the future. I suspect that is true and that we are only just scratching the surface on the concepts of evaluating operating systems and operating models. Maybe the real game is evaluating markets. h/t Nick Mehta
Since we are on the topic of future - HUGE shout to Amy Webb ’s SXSW call to action - the discussion is all about Convergence with a nice summary
4. 1B company built with 1 person milestone achieved. (hired 2nd person this year so really 2)
5. OpenAI buys TPBN - This is probably old news for everyone but just in case.
6. Trust and Liability of AI - Companies are waking up to the real risks of AI efficiency. This is a predictable outcome for the reality that AI speeds up automation and automation creates a scale/surface area that few properly comprehend. A few big thoughts on this
In the end your company is liable for what it does - whether employees or autonomous agents. Plan/Act accordingly.
“Humans in the loop” is a nice idea but has a lot of assumptions underneath this inclusive of an assumption that humans have the capability and capacity to manage said agents. There is a reason everyone is excited about the scale up of agents…
Security posture and risk is real and will become more obvious over time. There are threat actors who are smarter than you are about AI and now have a lot of opportunity to do harm.
The software moat is trust - and that is going to be tested. Companies that are investing in both outcome based models (note: here it’s less about the pricing model and more about ownership of the outcome) and liability protection will be the most durable solutions. This is actually an insurance/actuarial topic NOT a software quality topic.
7. That’s a lot of wallet drop off for non-AI tech.
8. The reality of data (quality, access, context) in enterprises today is pretty fragmented. This directly impacts the usefulness of AI on the most important parts of your business. Digiomica shares some research and recommendations on what to do. h/t Maureen Blandford
9. More on the topic of security in an AI world - we are WAY over our skis right now that is for certain. If you are not up to date on the topic of supply chain attacks I recommend you might want to do a bit of reading. Here is a good start.
10. The decision trace opportunity in b2b software. Ashu Garg - this is a good drilldown connecting the dots between where we are today (transactional SORs as SaaS) and what the opportunity looks like when we add context graphs AND systems to capture the why of decisions as they are made. These are all pieces that will become more robust as agents increase their value and capability into operational workflows.
11. AI native businesses have nearly 2x the revenue with 40% less capital - still early days but the obvious has data now - there is a huge advantage for companies starting today and the gap for incumbents is real. These results are for the 90th percentile - there are still a lot of hacks out there but the real challenge is less the tooling and more in the business building. The picture becomes more clear on where you need to invest in value creation – you cannot spend all your time on low hanging fruit - you have to dig in to understand where and how the game has changed and move there.
12. OpenAI economic policy proposals - Interesting overlap with the Scott Santens discussion we had on the pod (Episode 27). Meg POV: I do think we need a massive re-think on both the capital v. labor discussion and the way we fund government programs. Feels harder to have when so much of the budget is going to defense spending and debt service. It’s no surprise, that I’m solidly in the butter camp (vs. guns) and that I think decoupling healthcare from employment would be a massive benefit to everyone
13. Ronan Farrow does a deep dive on Sam Altman highlighting many ethics concerns. Full article in the New Yorker
14. The story of Ramp’s AI journey (and the importance of culture). “We had a culture that turned out to be the right raw material, and we just kept doing things with the people and technology in front of us and watched it compound. The most important lesson is the simplest one - just get started.” The intersection of framework building + culture + get started is a solid flywheel and one that most companies are thrashing about trying to find. One thing that I see in this story is the Heath Brother’s “Path Shaping” concept that I think matters a lot for scaled engineering teams.
15. Lies, Damn Lies and Recurring Revenue - A SaaSpocalypse context with a deep dive of the Annual Recurring Revenue past/present and future in the Only CFOs newsletter ( thanks Nick Mehta ).
16. An important reminder of how EBITDA hides stock based compensation (one of the reasons Charlie Munger called it bullshit earnings).
Work and Jobs
For my comp committee friends or anyone who works in corporate compensation roles (and/or those looking to calibrate an offer) a useful report on equity trends. I suspect these will continue to shift as macros evolve.
Enshittification and P(catastrophe)
In the Holy shit we misunderstand context category - Google just mentioned that quantum computing can break encryption and of course, in the cartoon category we have this fantastic submission
Anthropic delays Mythos release due to how good it is at finding and exploiting security vulnerabilities.
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** Typos and poor grammar either because I'm too lazy to edit properly, or to make you feel confident this was written by a flawed human and not AI generated.


