Gergely Orosz · 21 min read · Productivity
Pushing software engineering limits with “napkin math”
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This piece distills 'napkin math'—quick rough calculations that reveal why products cost more or run slower—and shows how Simon Eskildsen applied it from Shopify to turbopuffer. It connects a deep infra background and a focus on algorithmic efficiency to practical product decisions, including considerations around venture capital.
Key Takeaways
- Napkin math enables quick, rough calculations to surface compute and data-cost inefficiencies, guiding faster, more cost-effective product decisions.
- Deep infra experience (e.g., Shopify) builds intuition for scalable, reliable systems across regions and aging software.
- A focus on algorithmic efficiency and understanding theoretical compute limits can drive meaningful performance improvements, especially for AI-focused workloads.
- VC funding motivations are mixed: it can fund R&D and growth but may reflect ego; alignment with real business needs is essential.
Excerpt
Hi, this is Gergely with the monthly, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover Big Tech and startups through the lens of senior engineers and engineering leaders. If you’ve been forwarded this email, you can subscribe here . Subscribe now After I recently interviewed Simon Eskildsen, co-founder and CEO of turbopuffer, on the main stage at the AI Engineer’s World Fair, many people at the event told me they found him relatable and inspiring for his choices to stick with one company for close to a decade, his belief in the power of “napkin math”…