How building Helpmaton — a robust infrastructure layer for AI agents—helped transform one-off scripts into reliable, context-aware, and continuously evaluated AI workflows for projects like TimeClout.
How I built a fast, fully client-side semantic search system for AI customer service agents, using vector embeddings, Web Workers, and real-time doc updates — all without dedicated search infrastructure.
Why beautiful designs alone can't overcome the realities of complex systems — and why collaboration between designers and engineers is essential for building things that actually work.
Why over-engineering early is a trap, and how to build software with just enough architecture to get real results. Embrace the 'minimum viable architecture' mindset and learn practical, low-friction alternatives to heavyweight solutions.
While tRPC offers great developer experience with end-to-end type safety, GraphQL's client-side query customization provides architectural flexibility that shouldn't be overlooked. A deep dive into why GraphQL's advantages remain relevant.
A comprehensive exploration of Decipad's unit conversion system, detailing how the language integrates dimensional analysis, enforces unit correctness at compile time, and enables precise, error-resistant calculations for scientific, engineering, and financial applications.
Discover how Decipad's date system models time as intervals with built-in granularity, enabling intuitive operations like 'contains' and natural date arithmetic that matches human reasoning.
How we designed and implemented a reactive, type-safe, spreadsheet-inspired language with real-time updates, dependency tracking, and incremental computation.
A deep dive into why date handling in programming is more complex than it seems, and how to approach time-based problems correctly.
How we built an AI agent that can see and understand visual content, opening new possibilities for intelligent automation and assistance.
Discover how to create a fast, lightweight local development environment that closely mirrors AWS serverless infrastructure—without Docker or complex orchestration. Learn best practices, architecture, and tips for productive serverless development on your machine.
Learn how to automatically deploy every pull request to its own isolated AWS environment, complete with custom domains, SSL certificates, and full-stack infrastructure. This guide covers the architecture, CI/CD pipeline, and best practices for building robust, production-like PR deployments that supercharge your team's development workflow.