• in AI
  • 3 min read

AI and Marketing Content

The Microsoft Revolution

About 20 years ago there was a major shift in document processing which had profound repercussions for the AI world, years before it started. With Office 2007, Microsoft made a major change in their document formats. Up until that point, Microsoft had preferred closed, proprietary, customer lock-in of content into silos of information. But during the 2000s the rise of Apache OpenOffice and its open document formats, along with governmental demands for interoperability, put pressure on Microsoft to introduce OOXML. Of course it had added benefits - competition alone rarely encourages change. The new format was up to 75% smaller, improved corruption recovery and improved security.

  • in AI
  • 6 min read

AI, Tailwind, and The Future of Media

Recently there was an announcement that Tailwind was laying off 75% (3 of 4) of its engineering team because of revenue collapse. The initial hint came from a comment on a PR and was followed up with a podcast on X. This has caused a lot of discussion in the IT world. But I want to take a different approach. What does this mean for the media industry and the future of how we find out news?

  • in AI
  • 10 min read

AI Coding - Thoughts About The Future of Development

Vibe coding is probably the term of the year. Since being coined by Andrej Karpathy in a tweet in February the term has gained widespread adoption. My job is research, so I'm not one to accept code without review. But I absolutely need to be aware of new technologies and approaches, and evaluate their usefulness. And all technologies improve over time. So AI-assisted coding has been a regular part of my work for 18 months. Over recent weeks I've used it more and more, for a wide variety of purposes. And research is not just about trying things, it's about extrapolating and anticipating future usage.

  • in AI
  • 8 min read

Effective AI Usage: Understanding Brains

I've talked about the (current) moving parts of AI and AI-fu. But a fundamental aspect of AI-fu is being aware of how we think and how that's different to how LLMs "think". It's probably true that most people are not consciously aware of how they think or aware of how colleagues thinking works differently. So it's well worth raising that topic, because it's crucial to the quality of results.

  • in AI
  • 7 min read

Effective AI Usage Part One - What is AI?

In my last blog post I talked about some lessons I've learned from using AI. I talked about a follow-up article talking about AI use at a higher level. Recent experience has reinforced my thinking on this. In this blog post we're going to focus on what AI is, the initial interaction, and training.

  • in AI
  • 7 min read

More AI Lessons

A little while ago I blogged on developing at speed. The obvious omission from all aspects was AI. But AI – like an IDE – is just a tool. Unless you understand what it can and can't provide, unless you use it intelligently, you will not reap the benefits. But unlike an IDE, AI doesn't come with a set of menus that hint at what it can and can't do. AI doesn't come with a marketplace of extensions that provide functionality shared by the community. And it's so new that we're all working it out. So what are my thoughts?

Supercharging Input to Domino REST API Agents

One of the things I learned when building HCL Volt MX LotusScript Toolkit was that calling a web agent with ?OpenAgent URL populates the NotesSession.DocumentContext with various fields containing useful information from the request. So when I was building agent processing functionality into the POC that became Domino REST API, I utilised the same approach to provide opportunities to pass contextual information across to an agent.