PostgreSQL Query Rewriting Techniques The previous articles in this series covered performance problems you fix by adding indexes, restructuring joins, or tuning memory. This one is about the queries where the plan is "fine" — every node is doing something reasonable — but the query itself is asking the wrong question, producing unnecessarily large intermediate results or forcing the planner dow
Run the same brand-query through ChatGPT, Gemini, Perplexity, Claude, and Grok. Read the citations. The cited URLs will not be the same, the brands featured will not be the same, and in roughly a third of cases one tool will cite your brand confidently while another does not mention it at all. The temptation is to reach for an algorithmic explanation different rerankers, different summarisation st
This is the follow-up to What I Actually Learned Building a Side Project in 5 Days With AI. That post was about AI. This one is about what happens after you ship — when you actually have to run the thing. I lost a freelance client last year because I forgot to send a monthly report. Not because I didn't do the work. I did the work. I just never wrote it down in a place I'd actually look. The repor
SQL is widely known for data querying and manipulation but systems do grow; data becomes larger; processes become repetitive and operations become sensitive. SQL has some features which enables it to be considered a fully fledged programming language. Some of the features which I discuss in this article are procedures, functions and transactions. Each of these concepts serve distinct purposes. Sto
Hi 👋, In this post we shall explore Bedrock's structured KB with this architecture: Upload CSVs to S3 > SNS Queue > Crawl data with Glue > Query with Redshift > Bedrock KB > Query with LLM. Let's do some of this with code. Let's get started. Clone the repo and switch to the project directory. git clone [email protected]:networkandcode/networkandcode.github.io.git cd structured-kb-demo/ Do a uv sync
A few days ago, I read a fascinating post here by @404Saint about Arkoi, a tool designed to detect SEO poisoning. It struck a chord with me. If attackers can manipulate search engine results to push malware, what’s stopping them from manipulating the Latent Space of LLMs to misrepresent critical Web3 protocols? As the founder of HUTMINI, I’ve been obsessed with a new problem: AI-Era Visibility. We
TL;DR: I shipped image → PDF conversion but spent most of the week on SEO content instead of the planned batch UI and landing page. The numbers say that was the right call. Organic search became the #1 traffic source for the first time. Convertify is a free image converter I'm building solo: Rust + Axum + libvips on the backend, Next.js 16.2 SSG on the frontend, PostgreSQL for landing page content
We run thecalcs.com—a big library of small, single-purpose calculators. Adding “one more page” is easy; building something trustworthy is the hard part. This is how we approached one tool end to end: stack, where we draw the line on accuracy, and how we nudge search engines when we ship. The site is Next.js (App Router), with calculator logic in plain TypeScript modules and UI in React components.