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RAG vs Fine-Tuning: An Honest Decision Framework

AI/ML

April 20269 min read

RAG vs Fine-Tuning: An Honest Decision Framework

RAG and fine-tuning solve different problems, and most teams pick wrong. A practical framework for deciding which one your LLM feature actually needs.

April 20269 min read

MCP Explained: What the Model Context Protocol Actually Solves

MCP is the USB-C of AI integrations: one protocol between models and your systems. What servers and clients are, and when building one makes sense.

Cloud

April 202610 min read

Cloudflare Workers vs Vercel Edge: Cold Starts, Pricing, Lock-In

Two very different bets on serverless compute. Comparing Cloudflare Workers and Vercel Functions on cold starts, pricing models, DX, and exit costs.

April 20267 min read

How I Combine Opus 4.7 and Sonnet 4.6 in Claude Code

My practical workflow: use Opus 4.7 for critical planning and Sonnet 4.6 for cost-efficient execution loops.

Platform Engineering and Internal Developer Platforms: Building the Paved Road for Your Team

DevOps

April 202611 min read

Platform Engineering and Internal Developer Platforms: Building the Paved Road for Your Team

A comprehensive guide to building an Internal Developer Platform (IDP) using Backstage, golden path templates, and DORA metrics. Learn how platform teams reduce cognitive load for developers, improve deployment frequency, and implement Team Topologies principles in practice.

Building Production RAG LLM Applications: Architecture, Chunking, and Evaluation

AI/ML

March 202612 min read

Building Production RAG LLM Applications: Architecture, Chunking, and Evaluation

A practical guide to architecting production-grade Retrieval-Augmented Generation systems using LangChain, pgvector, and RAGAS evaluation metrics. Covers chunking strategies, vector store setup, retrieval optimization, and how to measure answer quality in real deployments.

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