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Notes on AI, agents, web technologies, and building with LLMs
Technical articles on building with LLMs: agents and agent harnesses, MCP, evaluation, and the web technologies underneath. Worked examples with code, written for working developers.
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Understanding the Orchestrator-Worker Pattern
The orchestrator-worker pattern brings scalable structure to agentic AI workflows by cleanly separating high-level planning from specialised task execution. Through a practical trip planning example, this article demonstrates how LLMs can dynamically coordinate expert agents, grounded in schema-driven logic and real-world data.
InteractiveAgentic AIBuilding with Reflection: A Practical Agentic AI Workflow
This article explores how to implement a reflection loop-an agentic AI pattern where a model generates, critiques, and iteratively improves its output - using image captioning as a practical example.
InteractiveAgentic AIParallelisation as an Agentic Workflow
Unlock faster, more diverse reasoning by running multiple LLM prompts in parallel and aggregating their responses into a single, cohesive output.
InteractiveAgentic AIHow Transformers and LLMs Actually Work - A Developer's Guide with Code
A hands-on walkthrough for web developers to demystify large language models by actually building a mini Transformer from scratch.
Routing: Building Step-by-Step AI Reasoning
Explore how to intelligently route AI queries using schema-guided function calling and contextual categorisation.
InteractiveAgentic AIPrompt Chaining: Building Step-by-Step AI Reasoning
Learn how prompt chaining enables AI to tackle complex tasks through step-by-step reasoning, boosting both accuracy and interpretability.
InteractiveAgentic AILCP and low-entropy images
In this article we take a look at how to see if an image has low-entropy for LCP calculation.
Compare how different image formats load on the web
WebP, AVIF, JPEG XL, Progressive JPEG - how do these image formats compare in terms of their load speeds and how can we measure it? In this article we review a small app that gives us a visual answer.
Google Chrome introduces a new Performance Insights panel
A new performance insight panel has been added to Chrome which helps with tracking down performance bottlenecks in a much easier fashion compared to the classic performance panel
call vs apply vs bind
In this article we take a look at the differences between call(), apply() and bind().