AI needs more uncertainty
AI has a confidence problem. Human intelligence was shaped by an uncertain world, and uncertainty is exactly the ingredient AI is missing.
The blog · since 2015
Essays, playbooks and field notes from our CTOs, architects and leads. Written for people shipping real product.
AI has a confidence problem. Human intelligence was shaped by an uncertain world, and uncertainty is exactly the ingredient AI is missing.
Learn about the importance of SBOMs and software licensing for your SaaS startup.
How to manage technical debt effectively to keep startups agile with strategies for documenting and prioritising technical debt, integrating it into your roadmap, and creating a culture of continuous improvement. Keep your codebase healthy and your team productive with these actionable tips.
Discover strategies to optimise developer onboarding, minimise costs, and improve time-to-market. Learn how to tackle challenges like code complexity, technical stack adaptation, knowledge transfer, and team integration while fostering a supportive and productive environment for new hires.
Large language models (LLMs) transform problem-solving by enabling natural, iterative conversations, ideal for fields like healthcare and legal services. They scale expertise and accessibility but face challenges like reliability and cost.
Labels like "junior" and "senior" often fail to capture a developer's true value. True impact comes from initiative, ownership, and proactive contribution—not just years of experience. We value "pull developers" who actively seek improvement, ensuring the product's success beyond assigned tasks.
A technical moat is often seen as a product's defensive edge, but does every product really need one? For AI products, the choice between building proprietary tech or leveraging existing solutions like OpenAI is complex. True value lies in solving customer problems—not just in owning the technology.
Many product companies are eager to leverage tools like ChatGPT. But how do you go from experimenting to running in production? Let's explore choosing the right large language model (LLM) to understand hosting options, ensuring an efficient and sustainable AI implementation.
Today's digital age may seem hyper-connected, but remote work often lacks genuine human connection. We’ve created a culture of cohesion using dedicated bonding, safe spaces, and custom tools to ensure no one feels isolated.
Being an expert isn't about always having answers. It's about balancing confidence and humility, knowing when to admit you don't know, and valuing collaboration. True expertise grows through listening, learning, and contributing meaningfully, not just knowing everything.
"use cache" is an experimental Next.js 15 Canary feature and may change. In this tutorial, we explore "use cache" for caching, covering fetching and inserting comments with Drizzle to reduce database calls and improve performance while maintaining control.
In recent audits, I've noticed a less obvious pattern: overly talented start-up teams. While smart, experienced teams thrive early on, they struggle to scale. Scaling requires structure, documentation, and room to grow talent in-house.
Learn how to navigate the challenges of becoming a squad leader as an introverted senior engineer. Discover strategies for effective 1-1s. Overcome the anxiety of leadership by focusing on clarity, communication and creating an inclusive atmosphere where your team can thrive.
Strava's new AI-driven Athlete Intelligence brought me back to Addapp, the startup I co-founded nearly a decade ago. We used data from devices like Apple Watch to offer insights, like how your run affected your sleep, using traditional data science. Being ahead of time is not always good.
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