Browser Rendering Explained: From HTML to Pixels
Understand the browser rendering pipeline, critical rendering path, layout, paint and compositing — and where performance really gets lost.
Archive
Every article
All 17 posts across Tech and AI, newest first. Search filters the whole archive instantly.
/
Image Optimization for the Modern Web
A practical image optimization guide covering dimensions, modern formats, responsive images, loading priority and the mistakes that hurt LCP.
Caching and CDN Strategies for Fast Static Sites
Learn how browser caching, immutable assets, cache-control headers and CDNs work together to make static websites faster and cheaper.
Embeddings Explained: How AI Turns Text into Vectors
A practical explanation of embeddings, similarity, vector dimensions, chunking and how embeddings power search, RAG and recommendations.
Vector Databases Explained: Indexes, Metadata and Retrieval
Understand vector databases, approximate nearest-neighbour indexes, metadata filtering and the design decisions behind production retrieval systems.
AI Agents vs RAG: What Is the Real Difference?
A practical comparison of AI agents and RAG: retrieval, tools, planning, memory, failure modes, costs and when to combine both.
LLM Inference Optimization: Latency, Throughput and Memory
Learn the core levers for faster LLM inference: quantization, batching, KV cache, context length, speculative decoding and model choice.
Prompt Engineering for Production AI Systems
Move beyond clever prompts with production patterns for instructions, structured outputs, examples, failure handling, evaluation and prompt versioning.
Technical SEO for AI Websites: Crawlability, Canonicals and Sitemaps
A developer-focused technical SEO checklist for AI and tech sites covering crawlability, canonical URLs, robots.txt, sitemaps, internal links and indexing diagnostics.
Internal Linking for Topical Authority
A practical internal-linking framework for building topical authority: pillar pages, supporting articles, anchor text, click depth and link maintenance.
30 ChatGPT Prompts That Save an Hour a Day
30 ChatGPT prompts I actually use for email, meetings, spreadsheets and writing - copy, paste, replace the brackets. Plus the three prompts I stopped using.
RAG vs Fine-Tuning: How to Choose
RAG vs fine-tuning explained with a clear decision framework: cost, freshness, accuracy, latency and when to combine both approaches.
Core Web Vitals Checklist for 2026 (INP, LCP, CLS)
A field-tested Core Web Vitals checklist for 2026: how to pass INP, LCP and CLS on real devices, with the exact fixes that move the numbers.
AI SEO: Building Topical Authority That Ranks #1
How to build topical authority with AI-assisted workflows: entity coverage, internal linking clusters, structured data and content that survives AI search.
How to Cut JavaScript Bundle Size by 60%
A repeatable process to cut JavaScript bundle size by 60%: measure, split, replace heavy dependencies and delete dead code — without losing features.
Run a Local LLM on 8GB VRAM: Practical Setup
A practical guide to running a local LLM on 8GB VRAM: model choices, quantisation levels, context limits, throughput expectations and tuning tips.
Self-Hosting vs Serverless: The Real Cost Breakdown
Serverless or a $12 VPS? A concrete cost and operations comparison across traffic tiers, cold starts, egress fees and engineering time.
Latest updates
Newest four, auto-generated.
Browser Rendering Explained: From HTML to Pixels
Understand the browser rendering pipeline, critical rendering path, layout, paint and compositing — and where performance really gets lost.
Image Optimization for the Modern Web
A practical image optimization guide covering dimensions, modern formats, responsive images, loading priority and the mistakes that hurt LCP.
Caching and CDN Strategies for Fast Static Sites
Learn how browser caching, immutable assets, cache-control headers and CDNs work together to make static websites faster and cheaper.
Embeddings Explained: How AI Turns Text into Vectors
A practical explanation of embeddings, similarity, vector dimensions, chunking and how embeddings power search, RAG and recommendations.