Insights, guides & engineering notes
Practical writing on web and mobile development, cloud, and building software that ships.
Best Vector Databases Compared: Pinecone vs Rivals
A vector database comparison covering Pinecone, Weaviate, Qdrant, and Milvus — benchmarked on recall, write throughput, and hybrid search so you pick right.
Test-Driven Development With Coding Agents That Works
Learn how agentic coding and TDD combine so failing tests become the agent's own guardrail — stopping hallucinated behaviour before it reaches your codebase.
Chunking Strategies That Make or Break RAG Quality
Learn which document chunking strategies actually improve RAG systems quality — and why chunk boundaries are a retrieval decision, not a preprocessing afterthought.
Multi-Agent Orchestration: Supervisor vs Swarm Models
Compare supervisor and swarm models for multi-agent systems. Learn which architecture ships reliable production workflows and when emergent coordination costs you.
How to Evaluate Software Vendors With a Scoring Guide
Master vendor selection with a weighted scoring guide that cuts through sales pitches and surfaces the trade-offs every stakeholder actually cares about.
useEffect Best Practices: When You Don't Need It At All
Learn useEffect best practices in React 19 and discover how derived state, event handlers, and the use() API replace most effects you reach for by habit.
Expo vs Bare React Native: Which Should You Pick?
Compare Expo vs bare React Native using the EAS-era prebuild model. Learn which workflow fits your team's native requirements, CI/CD setup, and long-term maintenance needs.
Edge vs Serverless: Choosing the Right Web Runtime
Understand edge vs serverless runtimes by latency profile, cold-start cost, and database compatibility — so you pick the right one for your app.
The AI Tool Stack Every Startup Should Consider
Build a lean AI tool stack for your startup that avoids vendor lock-in across model, gateway, eval, and observability layers — so you can pivot without a rewrite.
Spec-Driven Agentic Development: A Practical Guide
Learn how spec-driven agentic development workflows let coding agents produce verifiable code — write the spec first, let the agent treat it as an executable contract.
Fine-Tuning vs RAG: Choosing the Right LLM Approach
Decide between fine-tuning and RAG for your AI engineering project. Learn which LLM approach fits your use case, budget, and data reality.
RAG vs AI Agents: When Retrieval Beats Autonomy
Learn when RAG systems outperform AI agents: a practical decision rule based on task variance that saves latency, cost, and engineering complexity.