From our SaaS audits
What we find inside SaaS companies
Patterns from the technical due diligences we run for investors and boards.
Leadership
How to become an AI-native SaaS company in the next 3 years
Becoming AI-native in three years does not need a three-year technology roadmap. It needs a usage policy, a map of your data, one bounded experiment, and both the enthusiasts and the sceptics in the room. Build the ability to change, not the overhaul.
How to choose a fractional CTO in Belgium: a guide for non-technical founders
A practical guide to evaluating fractional CTO providers in Belgium: the three criteria that matter most, how the four provider types differ, what an engagement should cost, and when a full-time hire is the better call.
Your company needs more than an LLM subscription
Handing everyone an LLM subscription gives them a model. A shared, self-hosted agent gives them a configured environment with company context, connected tools, and clear boundaries. Why a company should own that layer rather than rent it, and how to start small.
The peloton problem
Senior engineers carry the front of every decision, every code review, every on-call shift. The peloton runs best when roles rotate. When the star eventually leaves, someone else needs to know what wind feels like.
Courage as a service
AI is making the knowledge side of consulting cheaper by the day. Teams still avoid the legacy system. The gap is not expertise. It is the structural courage to act on what everyone already knows.
Stop letting documentation rot
Five types of documentation, five different AI leverage stories. The question isn’t whether to involve AI in your docs; it’s where each type belongs and how much maintenance you can hand off.
Show me the way: engineering demo 101
Engineering demos fail when they present what was built instead of why it matters. A practical guide to leading with business impact, showing the happy path, and translating technical work into terms your audience actually uses.
The AI skills gap
In 40+ interviews, senior engineers from major banks and consultancies showed strong backgrounds but little real AI fluency. No RAG, no agent frameworks. The gap isn't about skill, it's about exposure.
Your codebase is a commons
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.
We're not a normal company
Every software company claims to be different. The "we don't need X because we have culture" exemption is special pleading. The four phrases that reveal it, and the questions that break them open.
The CTO as prisoner
CTOs who built their company's survival by doing everything can't escape that role by scheduling a holiday. Moving from doing to enabling is a skill and identity shift at once. One thing handed off permanently is where the exit starts.
Mental capacity is a bottleneck
AI removes bottlenecks until it reaches the one that doesn’t move: human cognition. The faster AI makes your system, the more your team’s mental capacity becomes the constraint. You can’t add more of it.
Taste is the moat
When AI closes the execution gap, taste becomes the differentiator. Curation, judgement, and the willingness to say “not this” compound over time in ways that models can’t replicate.
The authenticity tax
AI-generated content has made polished writing look suspicious. The deeper cost is the thinking you skip when you outsource the words that define your position.
The cost of the quick fix
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.