BigID leverages agentic AI to move beyond traditional LLMs, enabling secure, autonomous data discovery, governance, and real-time decision-making at enterprise scale.
Testcontainers enables realistic integration testing with broad language support while balancing fidelity, performance, and nuanced adoption strategies.
Learn about two fundamental architectural patterns reshaping how we build intelligent systems. Explore ToolOrchestra, Mixture of Experts (MoE), and other AI patterns.
AI makes code cheap, not thinking. When cost disappears, Agile principles supply discipline so teams don’t build the wrong thing faster at scale with AI.
Proven techniques for production vector search, including when to use each one, how to combine them effectively, and trade-offs to understand before deployment.
H100 GPUs are best for flexibility, fast iteration, and custom CUDA work. TPU v5p wins on GCP for large-scale LLM training with better cost efficiency and scaling.
This article demonstrates a "Threat-Model-First" workflow where we use AI not just to write code, but to aggressively attack our logic before we implement it.
Engineers rely on rollback to keep systems stable—but sometimes it isn’t possible. This article explores irreversible changes and why baking and testing matter.
This article combines practical mentoring experience with an analysis of how AI alters the junior career path, focusing on what teams should realistically expect today.
The 7 Rs framework helps you choose the smartest path to modernize every application, reduce legacy risk, and align your tech stack with future business goals.
High-concurrency systems — especially retail, travel, ticketing, or any “hot product” scenarios — often face cache stampedes (aka "thundering herd", "dogpiling"). Here's a practical pattern for managing concurrent data requests.
In this article, I want to take a closer look at the pitfalls of popular SaaS scaling strategies, drawing on my own experience, and share the lessons learned.
A real Gemini Pro session shows how AI can look “done” while skipping uploaded data and ignoring STOP commands — creating silent failure risk without verification.
Cloud systems drift when exceptions accumulate, and decisions lose connection to original objectives. Clear requirements and early security design prevent sprawl.