There's an interview that got scrubbed from the internet with Zach on the 20VC podcast with Harry Stebbings. This comment and its lack of self-awareness exemplify what was on display for 60 minutes.
Zach is undoubtedly smart but for anyone who is not an SV insider, they would listen to that podcast they same way you are looking at this comment and wonder if it's all one big joke.
Balaji Srinivasan is one of those guys who I don't get. Specifics elude me but I recall his activities getting memory holed, his twitter timeline getting scrubbed, and completely new narratives being written about him.
I was also never quite sure why he was in the orbit of influence and power. He had a failed bitcoin mining hardware company and that's about all I know of, and yet he kept seeming to fail upwards.
The really fun part was after getting billing finally set up in the cloud console trying to find what model name you actually have to use to call it via the API.
Conflicting information? Sure! Gemini cloud help being useless? Naturally.
Oh and don’t forget that error message being returned when you try to call the API is because you didn’t give your project the proper permissions in google cloud console. What permissions do you need? ¯\_(ツ)_/¯
Google Cloud Console feels like being stuck in the seventh circle of hell.
To get the reduced rate many municipalities will require you to visit an office, somewhere you likely have to take transportation to, during office hours (aka working hours), and provide documentation to prove this.
This isn't really unknown either. There's a very good story anyone can look up about Dr. V in India and what it took for him to actually get the eye care he wanted to provide to the people who needed it.
In the digital world many of us know you want to deeply understand your user and design with them in mind. Same thing here in the meat space.
Yep, Peter Drucker wrote about this all the way back in 1964.
> The competition is therefore all the other activities that compete for the rapidly growing “discretionary time” of a population
His examples were bowling ball manufacturers competing with lawn care companies, but the idea is the same, go up an abstraction layer, and the competition is for time.
My perspective from someone who wants to understand this new AI landscape in good faith. The water issue isn't the show stopper it's presented as. It's an externality like you discuss.
And in comparison to other water usage, data centers don't match the doomsday narrative presented. I know when I see it now, I mentally discount or stop reading.
Electricity though seems to be real, at least for the area I'm in. I spent some time with ChatGPT last weekend working to model an apples:apples comparison and my area has seen a +48% increase in electric prices from 2023-2025. I modeled a typical 1,000kWh/month usage to see what that looked like in dollar terms and it's an extra $30-40/month.
Is it data centers? Partly yes, straight from the utility co's mouth: "sharply higher demand projections—driven largely by anticipated data center growth"
With FAANG money, that's immaterial. But for those who aren't, that's just one more thing that costs more today than it did yesterday.
Coming full circle, for me being concerned with AI's actual impact on the world, engaging with the facts and understanding them within competing narratives is helpful.
So you are saying that test driven development is:
a) not useful for you and your use cases
b) never useful in any use cases
c) sometimes useful but not for you
Perhaps it's more that we are looking at it from different levels. A contrived example to illuminate:
If I'm running a lawn care company in the desert I can get all those annoying details right and still be unsuccessful. So strategy is not opening a lawn care company in the desert.
If you think I'm missing something you are saying, please let me know!
There's an old Drucker quote "there's nothing so useless as doing efficiently that which should not be done at all."
If you're in the wrong market or building for the wrong customers you can execute brilliantly on everything you mentioned and it won't matter. The only thing that matters is product market fit or finding it if you don't have it. That's what I see as unsaid in your parent's comment about "execute what though?"
What exactly did your work flow look like for the gpt-5-medium refactor you did?
I don't have a test like that on hand so I'm really curious what all you prompted the model, what it suggested, and how much your knowledge as a SWE enabled that workflow.
I'd like a more concrete understanding if the mind blowing nature is attainable for any average SWE, an average Joe that tinkers, or only a top decile engineer.
Robert Kehoe, working for GM, was the chief advocate for leaded gasoline, and really the only person/lab doing research on lead until Clair Patterson stumbled into it while measuring the age of the earth. [0,1]
A modern equivalent might be if Facebook was the only organization researching social media's impact on society, while being able to set the paradigm/assumptions about said safety for half a century.
So even when Patterson's research was published in 1965, it took time to change the paradigm, and more time to phase out lead's use.
Should anyone want to read a narrative about the intertwined lives of Midgley, Patterson, Kehoe and lead, then this Mental Floss article is a good read. [2]
Good question, and my next one would be "at what cost?"
What are the externalities of services like NextDoor, local FB groups, etc keeping this in people's conscious all the time?
If I had to come up with a hypothesis and test it via the scientific method it would probably be: This is not good as it is a positive reinforcement loop that causes our lizard brains to see danger everywhere/all the time.
The Theory of Constraints - AI Era
[0] https://en.wikipedia.org/wiki/Theory_of_constraints
[1] https://www.goodreads.com/book/show/113934.The_Goal
[2] https://www.goodreads.com/en/book/show/17255186-the-phoenix-...