In the last few weeks, we’ve been thinking more clearly about how to describe what Anapoly AI Labs is for and how we intend to run it.<\/p>\n\n\n\n
The idea, from the start, was not to teach AI or to promote it, but to work out what it\u2019s actually good for. Not in theory, but in the real day-to-day work of people like us. We\u2019d do this by setting up simulated work environments (labs) and running real tasks with current AI tools to see what helps, what doesn\u2019t, and what\u2019s worth doing differently.<\/p>\n\n\n\n
To sharpen that thinking, I used ChatGPT as a sounding board. I gave it access to our core documents, including the notes from a deep dive discussion in NotebookLM about what we\u2019re trying to build. Then I asked it to act as a thinking partner and help me write a strategy.<\/p>\n\n\n\n
The result is a good working draft that sets out our purpose, stance, methods, and measures of success. It\u2019s a helpful starting point for discussion. One thing we\u2019ve been clear about from the start: we don\u2019t claim to be AI experts. We\u2019re practitioners, working things out in public. That\u2019s our stance, and the strategy captures it well.<\/p>\n\n\n\n
We\u2019ve published the draft as a PDF. It explains how Anapoly AI Labs will work: how the labs are set up, what kind of people they’re for, how we plan to run sessions, and what success would look like. We now want to shift focus from shaping the idea to working out how to make it happen.<\/p>\n\n\n\n