Pairing with a yes-machine
Pairing with an AI feels like pair programming. It isn't. There's one prior in the room, and it's trained to agree. This post makes the case for mob programming and spec-driven development as the structural fix.
The blog · since 2015
Insights for founders,
CTOs & investors.
Essays, playbooks and field notes from our CTOs, architects and leads. Written for people shipping real product.
Featured articles
What will the state of AI be like by this time next year?
Pricing strategies in the era of AI: why hourly billing no longer works
5 red flags for VCs when planning to invest in Seed or Series A companies
SaaS due diligence report: 12 learnings for founders that want to secure their next funding round
Things we do in our first weeks as Fractional CTO
Latest posts
How to introduce AI coding agents into your engineering team
AI coding agents draft code, write tests, and open pull requests autonomously. This guide covers the tool landscape, readiness signals, a phased rollout plan, and the team dynamics that make or break adoption.
AI code review tools: what works, what doesn't, and how to set it up
AI code review catches what humans miss and misses what humans catch. This guide compares the tools, shows what each catches, and walks through setup without replacing human judgment.
Communicate or be micromanaged - the engineering edition
Micromanagement rarely starts with bad intent. It usually starts with silence. When nobody knows what you are working on, meetings multiply, trust erodes, and focus disappears. This piece shows how clear, boring communication is your best defence.
The value of code review
Code reviews improve more than code quality. Done well, they shape better problem-solving, expose edge cases, and spread knowledge across teams. Learn how small, focused reviews and AI support help teams ship faster with confidence.
Your startup does not need more engineers, it needs fewer mistakes
Hiring to fix velocity often multiplies your problems. Reduce avoidable mistakes first: tighten decision-making, align product and engineering, and put foundations in place that make a small team dangerous in the right way.
Getting started with performance testing
Performance bugs erode trust quietly until users explode. Three pragmatic steps help you catch slowdowns early: explore real bottlenecks with Sentry, test with production-sized data, and add lightweight API load tests.
Navigating Outages: lessons from recent cloud failures
Outages can strike unexpectedly, impacting businesses and users alike. In this episode of the SaaS Show, hosts Andreas and Sjimi delve into the recent outages experienced by major cloud providers like Amazon and Cloudflare.
How to pragmatically leverage AI as a startup
If you believe what you see on LinkedIn, startups don't need employees anymore, real founders just have agents building their companies. You write a prompt, fire off the agent, and wait for customers. In reality, you get a vague workflow that produces a mediocre demo at best.
The End of “AI-powered”
Of course your product is AI-based. There is no need mention this anymore. Tech loves a fashionable label. Web 2.0 had its moment, then mobile, then the cloud. Do not tell me your product uses AI. Tell me what your product can do that was impossible before AI existed.
Cloudy with a chance of function calls
In the first of a series exploring infrastructure fundamentals, Brenden addresses the most frequently asked questions about what's really happening under the hood with complex pipelines and AI/data systems, bringing the cloud to life.
Analyse your tables for better performance
I recently encountered a issue with MySQL query performance. A particular query would perform very badly in production, but perform very well in the testing environments.
Stereotypes: are these the biggest misconceptions about software engineers?
Outdated myths about developers—like “they hate meetings” or “only care about code”—create friction, missed context, and rework. Learn how to build healthier collaboration across engineering and product.
No designer? No problem with v0
For small teams without a designer, v0 is a game-changer. The cost justifies itself by letting you explore and validate ideas in minutes rather than days.
Why I switched from BugBot to Claude for code reviews
I switched from Cursor's BugBot ($40/month) to Claude Code for code reviews. Setup is straightforward in VS Code, and Claude's bug detection has been notably better. While it still flags null reference checks like most AI reviewers, the difference in catching actual bugs is significant.
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