Software is Cheap. Clear problems aren’t.

On roboagencies and our bet on biotech

Last year we ran (and eventually sold) an accelerator called Build, where we helped engineers launch over 1000 new products. A handful raised millions. A few went viral. But most failed - not because they were poorly built, but because they were solving problems that didn't really exist.

Build was our personal awakening, but 2024 seems to be the year everyone woke up to the idea that software is getting cheap. Even my mom spent time over Christmas worrying about whether my brother should abandon his job as a software engineer and go back to school.

So what becomes scarce if it isn't code? If software is cheap, then the most valuable thing to own is clear opportunities for software to drive impact. It's like electricity suddenly becoming 10X less expensive overnight - the winners wouldn't be startups, they'd be the companies where energy costs are currently limiting growth.

This sets up the central tension that will define 2025: Existing companies have backlogs of good problems to solve but struggle to transform how they work. New startups can build AI-native from the start but have to earn good problems to solve.

If existing companies are going to win the tug of war, they will have to increase their software capacity by a lot. But how?

Some argue AI means less software outsourcing — the internal team just uses AI to ship 10X faster. I couldn't disagree more. The surface area of what's worth solving with code is expanding by an order of magnitude.

It's not just that previously expensive solutions are now ROI positive — AI agents mean problems previously solved by humans can now be solved with software. Assuming an internal team can cover the breadth of problems a company should solve with custom code mistakes engineering capacity for expertise.

This is why 2025 will be the year of the specialized roboagency. Not general-purpose development shops, but teams focused exclusively on specific types of problems. Sales automation experts who've built dozens of sales agents. Support automation teams who deeply understand customer service workflows.

The best roboagencies will look like typical tech companies from the outside. They won't sell the service, they'll sell the value. Sierra isn't selling custom chatbots, it's selling automated customer support - the custom buildout is just a means to an end. Sierra’s goal is to build infra to increase the margins of serving the next customer. If they fully automate the whole thing then it becomes pure SaaS, but only time will tell if that's possible. Most will remain software and services, especially for larger deals. Enterprise SaaS is already not so secretly a service heavy model anyways.

Some people call these “AI enabled services” probably because it sounds more scalable to investors than roboagency (which I prefer just because it’s simpler), but under the hood it’s the same thing and they are popping up everywhere. 8090 is creating custom versions of enterprise SaaS, my friend Rick is building custom document automation for financial services firms at Strange Loop Labs, there’s versions for freight auditing and payment and countless others attacking different specific opportunities for custom code.

And that brings me to some news: We've decided to build Robo as a specialized roboagency to build agents for biotech companies. After starting my career in neuroscience labs at Johns Hopkins and UCSF and then spending years at ResearchGate and Benchling, it's the space where I understand the problems best and it’s where I met my cofounder Rapha. Cutting edge biotech companies have a unique opportunity to build custom agents to accelerate R&D and improve efficiency. We want to help them realize that opportunity so they can deliver world-changing innovations faster.

We have lots more to share about the agents we’re building for biotech, but in the meantime if you're interested in what we're building, or know someone at a fast-moving biotech company, I'd love to connect.