From our SaaS audits
What we find inside SaaS companies
Patterns from the technical due diligences we run for investors and boards.
Newsletter
A bi-weekly letter from our CEO Andreas Creten for SaaS leaders and CTOs: what we see in audits, AI engineering and the companies we work with.
From our SaaS audits
Patterns from the technical due diligences we run for investors and boards.
Developers don't skip standards because they're careless, they skip them because there are fifteen things to remember and the code was the hard part. The real question isn't which tasks your LLM handles well. It's what's still slipping through ungated.
The AI wave is here, and the industry is already splitting into two: those adapting fast and those falling behind. The gap is widening quickly.
The machines aren't replacing developers, they're promoting them. You're no longer just writing code; you're managing agents, reviewing output, and setting standards. Three Claudes walk into a codebase, and suddenly you're a manager.
Last week, we deleted 16,000 lines of code, rewrote 11,500, migrated frameworks, ripped out React, and swapped our entire CSS setup with AI. It took less than 6 hours.
Technical debt used to justify meetings, trade-offs, and dedicated sprints. AI has changed that. Cleanup is now fast, cheap, and continuous. Teams that stop debating and start fixing unlock faster delivery and better outcomes.
Conductor by Melty Labs makes parallel agent workflows practical by running multiple agents with separate tasks simultaneously. The trade-offs are real but manageable, and this is where development is heading.
A couple of months ago, I was copy-pasting prompts into ChatGPT. Now I'm shipping features, running tests, managing branches, and keeping documentation alive, with a team of agents doing the heavy lifting. All by myself.
Legacy codebases are messy, undocumented, and full of decisions nobody remembers making. But if you can explain it to a new developer, you can onboard an AI and that changes everything.
Agile was supposed to free us from bureaucracy. Many teams just rebuilt it with better branding. Now, AI-driven development is forcing the uncomfortable question: Were we ever truly agile, or just managing slow feedback loops?
This is Part 2 of Bots and Boundaries, a three-part series on AI agents in open source.
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
Founders juggle endless demands, investors, sales, suppliers, and employees, all while building the plane mid-flight. But with engineering often being your biggest expense, there's one responsibility you can't delegate: ensuring your team builds the right thing.
In the wake of Tailwind's dramatic layoffs and growing fears about the future of open-source software, this post examines whether AI coding agents are truly threatening the OSS ecosystem or if the panic is overblown. And it's a reaction to Andreas' idea that open source will no longer exist.
AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.
Here's part one of a post I shared with our team on the radical change and evolution of our jobs. AI won't make software engineers redundant. It will expose what engineering was always supposed to be about: understanding systems, not just writing code.