Ask what work a product completes and which existing tools it still depends on.
Topics to listen for
Relevant context
Lower costs could create demand for more work
The case for growth is that cheaper goods and services let customers buy things they previously could not afford. Businesses could then expand rather than simply produce the same amount with fewer people. Competition matters here: it could push companies to pass savings on through lower prices. The unresolved question is whether that extra demand creates enough work to offset the tasks being automated.
Relevant context
Entry-level careers need a new way to build experience
Junior lawyers and software developers often learn through tasks that AI can increasingly help perform. If employers remove that work without replacing the training it provides, the route into a profession could narrow. An alternative is to use AI alongside mentoring so new recruits become productive sooner. The question is whether firms redesign junior roles or simply recruit fewer people.
Questions worth asking
What real workflow gets materially better with the product, not just easier to demonstrate?
Which work still needs a person to check or take responsibility for the result?
Who they are
Martin Shkreli is a former pharmaceutical executive and a co-founder of DL Software. The company’s July 2024 announcement described products including Godel Terminal for financial information and Neets for generative-AI services. His pharmaceutical career also led to an antitrust judgment: in 2024, an appeals court upheld a lifetime industry ban and $64.6 million in disgorgement over the Daraprim monopoly scheme.
What they are working on
Financial tools, AI products and a consequential legal history.
DL Software’s announced portfolio ranges from market information to speech and image generation. Those product descriptions establish what the company set out to offer, not clinical validation or proof of commercial success. Shkreli’s software work and the pharmaceutical ruling are both material parts of his background; neither should erase the other.
Well, sure. I mean, this is the point. When we have better tools, we can do way more things, right? And when I hear people say, oh, maybe we're just going to have all these great tools and we won't do more things, we'll just do the same things with fewer people, it doesn't sound right to me. I mean, there'll be some of that, but I think most of it will be, we're just going to do a whole lot more things. We're going to solve a lot more problems. We're going to accelerate scientific discovery.
One thing that I think that last question misses, and I think a lot of the AI doomerism stuff misses, is that competition exists. And so if you, I don't think there's any scenario where you just do more for less, and all of a sudden everyone has 70% operating margins. That's not going to happen. Someone else is going to come along and do more for less and lower the price. And so the thing that could happen is we could have a productivity boom from lower price goods and services and the basket of goods that humans are able to buy gets cheaper and cheaper and cheaper. And that's been true in many categories. Unfortunately, it's offset by what happens in healthcare and other regulated industry.
And if you believe that all of this cap excess being invested in AI infrastructure, it's going to have a payoff, then the growth rates could be a lot higher. And that ultimately, I think, is the way to get out of the debt spiral is we need strong growth. Without that, we're not going to get out of this problem. So look, I think that if you believe in growth, then the situation is not quite as dire.
Entry-level careers need a new way to build experience
Jason Calacanis · Nov 7, 2025 · 48:08
But what I'm seeing on the ground, because I work with startups, and I work with young folks who are in them, their contemporaries are not finding jobs. And the companies that we see and the companies that are selling the technology solutions are getting rid of what I'll call the like entry-level white collar work.
I still am a big believer in college recruiting because at the end of the day, this is going to change the curve by which anyone can pick up proficiency in a code base, let's just say. It takes sort of just regular CS hiring. What has changed is perhaps for someone who comes in new into a team, and to be able to ramp up thanks to all of the markdowns, the skills, the fact that I can go ask the agent. Let me think about it. It's like having an unbelievable mentor who is getting you on-boarded onto a code base faster. So in some sense, the productivity curve of a college hire is going to be much steeper than it ever before.
The job will exist. The tasks will be different, right? In order to have a partner-driven model, you need to bring people up the ranks, right? In the same way as you do with software engineers. You need to have junior engineers so that one day you can have senior engineers who know what they're doing. But the way to get there is very different. The way of getting there today will not be, lock yourself in the physical data room, read through every single document, mark the errors, and go fax it. It's also no longer just look in the virtual data room and Control-F. It's orchestrating the agent that will be doing that work.