From our SaaS audits
What we find inside SaaS companies
Patterns from the technical due diligences we run for investors and boards.
AI
How we rewrote our tech stack in under a day
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 lost its excuse
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: running multiple AI coding agents in parallel
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.
I'm using my engineering colleagues as my personal agents
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.
Onboard the AI like you'd onboard a developer
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.
QA is the last bottleneck
Software development's feedback loop has compressed from years to minutes, but QA remains the last bottleneck, the one place still dependent on human judgment. AI is rapidly closing that gap, and before the year is out, that final human checkpoint may no longer be necessary.
The AI Agile Manifesto
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?
Bots and Boundaries: Who do you blame when the bot defames? (Part 2)
This is Part 2 of Bots and Boundaries, a three-part series on AI agents in open source.
Bootstrapping a birding database using GenAI (Part 2)
Part 2 of the article about Mossie, when it was faced with scaling to include every bird in the world, complete with photos, sounds, and icons.
Why AI makes engineering teams smaller, but not simpler
AI is changing what small teams can ship, boilerplate gone, prototypes faster, experimentation cheaper. But lower costs of building don't mean lower costs of building the wrong thing. It just means you can do it faster.
AI didn't change the economics of software engineering
AI made writing code faster, but the real economics of software engineering were never about typing code in the first place.
Stop obsessing over the perfect prompt
LLMs are built for conversation, not incantations. The value isn't in your opening message, it's in the back-and-forth: clarifying, correcting, refining. Iteration is cheap. The conversation is the work.
Bootstrapping a birding database using GenAI (Part 1)
A small birding app with 300 manually entered species faced an ambitious challenge: scale to include every bird in the world, complete with photos, sounds, and icons. This article explores how the team used GenAI to bootstrap a comprehensive birding database from scratch.
I gave 3 AIs a Murder Mystery PDF: One was Sherlock, one was high and one just ghosted me 7 times
Several AI models were given the same 36-page evidence file and the same strict instructions, no hints, no hand-holding. What followed was a revealing test of how each model actually reasons under pressure, not just pattern-matches its way to a tidy answer.
Out with multitasking, in with orchestrating
The return of multitasking, but not as we knew it. Running multiple Claude Code instances simultaneously isn't the context-switching productivity killer we've been warned about for years; it's orchestration