Ai

There’s something appropriately meta about using an AI coding assistant to build an AI-powered news aggregator. QuantumExecBrief monitors quantum computing industry news, filters for business relevance, and generates weekly executive briefings using Claude. The whole thing was built with Claude Code as my primary development partner. The story here isn’t the subject matter, that could be anything. Here’s what I learned about the workflow. The Project in Brief QuantumExecBrief does a few things:...

Plain text should be the default. Not an alternative. Not a niche choice for technical users. The default. This isn’t a new argument, but AI has made it undeniable. Every piece of knowledge stored in a proprietary format is a piece of knowledge your AI tools cannot access. Every note locked in Notion, every document trapped in a closed system, every insight buried in an app’s database - invisible to the tools that could help you use them....

The Christmas break gave me something I rarely get during the year: time to learn without urgency. Two threads of exploration converged in interesting ways - one practical, one theoretical, both about AI’s role in how we work. Hands-On: Claude Code I spent part of the break experimenting with Claude Code, finally putting it through its paces on a problem that had defeated me for years: refactoring my Emacs configuration. Seven minutes of AI-assisted work accomplished what months of Sunday afternoons couldn’t....

I’ve had to declare “configuration bankruptcy” a few times now,1 each time promising myself this would be the clean, well-organized config I’d maintain going forward. And each time, within months, my init.el would devolve into a sprawling maze of half-commented code blocks and sections titled things like “Misc” and “TODO: organize this.” In 2022, I made a serious attempt to fix this. Sunday afternoons at a local coffee shop became my ritual - laptop open, config file sprawled across my screen, the goal clear: create a well-documented, properly organized init....

Intro I recently wrote about gptel - the Emacs package for interacting with LLMs via APIs. It’s brilliant, but every query costs money and requires an internet connection. For quick tasks like code explanations, refactoring suggestions, or drafting text, those API calls add up. Enter Ollama and Ellama. Ollama lets you run LLMs locally on your machine, and Ellama provides a clean Emacs interface to interact with them. No API keys, no costs, no internet required....

In large enterprises, responsible AI lives or dies in the gap between strategy decks and what actually ships. The WEF “Advancing Responsible AI Innovation” playbook gives a useful language for that gap - but it only becomes real when it’s translated into operating habits across product, risk, and technology teams. Here I want to spend some time thinking about how the nine plays in the framework can be used as a practical scaffold for enterprise AI programmes, rather than a poster on the wall....

I’ve been seeing lots about how AI, and the ever-growing use of LLMs, is creating slop that is killing the internet - making us angry and breaking our brains. I wrote about how this might impact scientific publications in 2023, but I think we should revisit this topic in light of a quote that shifts how I think about content today. In her video, My 17 Minute AI Workflow To Stand Out At Work, Vicky Zhao makes the point that, “in 2025, it will take you longer to read something and comprehend it than the amount of time it took to create it”....

I have heard wonderful things about gptel - the Emacs package that gives an interface to various LLMs. I will admit however I really struggled to get this working using my OpenAI API key with the Docs in their GitHub. Below is a quick guide for anyone else that got stuck - running a Linux machine. First things, get gptel installed - add the below to your config: (use-package gptel :ensure t) (setq gptel-api-key (getenv "OPENAI_API_KEY")) You will notice here we have to specify out OpenAI API key....

In the whirlwind of technological evolution, generative AI emerged as a beacon of transformative potential. Less than two years ago, the advent of ChatGPT set the tech world ablaze with predictions of a seismic shift that promised to redefine industries, economies, and the fabric of our daily lives. Goldman Sachs, with the precision of seasoned soothsayers, foretold the displacement of 300 million jobs.1 Yet, as we stand eighteen months into this future, the landscape is markedly different from what was prophesised....

Thoughts here are my own In the ever-evolving landscape of technology and artificial intelligence (AI), the decision by the new Labour government to shelve £1.3bn of funding promised by the previous Conservatives leadership for tech and AI projects will cast a long shadow over the future of AI, and scientific compute, innovation in the UK.1 This move, while framed as a necessary adjustment to restore economic stability, underscores a deeper, more systemic issue: the vulnerability of technological advancement to the whims of political change....