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The top pitfalls I keep seeing when reviewing Agent Skills, and what to do instead
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Using KL divergence to rank MLX quantisations of Qwen 3.6 (27B dense and 35B-A3B MoE)
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A regression in external display support on Apple Silicon M4/M5 generation chips prevents full HiDPI modes on 4K monitors, limiting users to either blurry non-HiDPI or reduced workspace HiDPI.
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I spend a lot of my time helping people who are getting started with Claude Code.
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NVIDIA artificially restricts peer-to-peer (P2P) GPU communication to their enterprise cards.
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An observation on functional correctness without domain quality.
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If you’re building MCP servers, you should be adding the ability to disable individual tools.
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A single, modular MCP server for AI coding agents.
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The two common themes I see with engineers adopting agentic coding tools
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Recording of a demo and Q&A session on my Agentic Coding workflow and Cline use.
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From Creative Exploration to Production Quality
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An overview of my Setup, Plan, Act, Review & Iterate workflow for agentic software development.
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A practical guide to LLM sampling parameters for Ollama, llama.cpp, and MLX
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A curated learning path for engineers looking to gain practical experience with AI and agentic systems.
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The cost of not leveraging agentic coding is likely far greater than you think.
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The Democratisation Paradox: What History Teaches Us About AI.
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What is prompt caching and why is it so important for Agentic coding?
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Video recording of a brownbag presentation / live demo I ran on Agentic Coding using Cline/Roo Code
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K/V context cache quantisation has been added to Ollama.
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It's probably not so much AI itself you have to fear.
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Generating diagrams with AI / LLMs
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A CLI tool for parsing directories into LLM-friendly markdown
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A web app to explore the effects of different inference parameters on LLMs.
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Integrating AI into Daily Development
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AI/LLM Quantisation Visualised
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Subjective ratings of the notable AI tools I've tried.
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Gollama is a Go-based client for Ollama for managing models.
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Download Confluence Spaces as Markdown, Summarise with Ollama
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Nvidia GPU Monitoring API
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SuperPrompter is a Python-based application that utilises the SuperPrompt-v1 model to generate optimised text prompts for AI/LLM image generation (for use with Stable Diffusion etc…) from user prompts.
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This is a simple command-line tool that allows you to easily link Ollama models to LM Studio's directory structure.
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Using an ESP32 S3 Box 3 with Willow, Home Assistant and Large Language Models (LLMs) create a locally hosted, offline, AI powered Siri / Alexa replacement.
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This reusable snippet will generate a menu of targets from the Makefile.
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"MBA Washing" refers to the phenomenon where individuals or companies, often with a strong theoretical or academic background but limited recent practical experience, adopt and reinterpret industry-specific terminology and cultural movements.
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A talk I gave to some peers on creating your own SDXL LoRA models from my tinkering around over the last few weeks.
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Enabling the new AMD P-State Driver on Fedora with Kernel 6.4
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Before adding this to my shell config, I would manually add –depth=1 to all my git clones.
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NPS Surveys are corporate spam
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Effort is non-linear and multi-dimensional.
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A high level intro to LLMs that I'm writing for a few friends that are new to the concept.
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Publicly documenting my subscription and license expenses
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Deployment / Delivery Frequency I often end up needing to advocate for more frequent delivery/deployments with clients.
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My Z-Shell configuration, scripts and hacks
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Using YAML Anchors and Aliases to make config files more DRY
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Github Actions Reusable Workflows vs Composite Actions
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My Z-Shell configuration, scripts and hacks
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Contributing to Open Source is important to the quality and maintainability of the software and engineering communities we rely on every day - so why is it that so many developers/engineers never participate?
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We create more value by having conversations in public instead of behind closed doors.
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Near the end of each year I note down a summary of the best apps I’ve enjoyed using throughout the year, here’s 2022.
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We’re (still) not deploying enough It’s 2022 and not deploying frequently enough is still one of the most common causes of software failure.