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.
Your codebase degrades the same way shared resources do: not from malice, but from missing governance. Elinor Ostrom proved the commons can survive. Her principles map to software teams with uncomfortable precision.
Business users love Lovable. Engineers tend to panic. A real-world case study of how to wrap an AI builder in guardrails so non-technical teams can move fast without quietly rewriting the systems that give your product its edge.
I used to teach people to code. And looking back, I was teaching students to write it by hand while the tools that write it for them were getting better every single month. So what should a coding classroom actually look like now?
Every legacy codebase is a palimpsest: layers of decisions written on top of each other, none fully erased. Geoffrey Dhuyvetters argues that what looks like technical debt is often stratigraphy, and you read it before you rewrite it.
The claude -w flag spins up an isolated git worktree in seconds, so you can keep coding while a long-running task occupies your main session. No conflicts, no context pollution, no waiting.
In 2010, every business convinced itself it needed a mobile app. Fast forward to 2025, and the script is identical, just with AI replacing mobile as the technology everyone insists they can't afford to be without.
The quick fix isn't cheaper. It's cheaper today. Bram Devries traces how deferred fixes compound into emergencies, and argues that naming the trade-off out loud is the only way to break the cycle.
Half of today's AI best practices are coping mechanisms for temporary scarcity, not timeless engineering insights. Geoffrey Dhuyvetters traces the arc from SMS bundles to token limits, and argues the price curve only goes one direction.
After auditing 190+ SaaS companies, the same patterns keep showing up: a CTO who does everything, documentation nobody updates, a backlog from 2019. Here's what the bingo card looks like, and what AI is changing about it.
The standard AI-assisted dev loop has created a new bottleneck: us. Peter Eysermans describes how deterministic orchestration via n8n, with GitHub as shared memory, gets the human off the loop without sacrificing quality.
When an AI agent gets a requirement wrong, the mistake lives in the test assertions, not the implementation. Domain knowledge catches it, not coding skill.
"Vibe coding" has become shorthand for bad engineering to some people, but does the label hold up? This post unpacks how a playful term coined by Andrej Karpathy became a verdict, and why that's costing teams more than they realise.
Ever wanted to build your own Google Docs-style document service? This post introduces WOPI, the open protocol that lets web applications embed Office document editing directly in the browser, while keeping your app in control of storage and permissions.
A mobile app, past its usefulness, was days from being phased out. One email reversed the decision. No discussion. No input from engineering. This is what happens when decision-making drifts too far from the work.
In part three, we look at both sides of the AI contribution debate. A working patch, real demand, never submitted, rejected because AI was involved. But maintainers are unpaid volunteers, and AI halved the cost of contributing without touching the cost of review. Both sides have a point.