Andrew Miles Davis answers three questions from recent training sessions, starting with the one he gets asked most often across every workshop he delivers, whether the free AI plan is genuinely enough or whether the monthly subscription is worth it. His answer is direct and comes with no commercial interest behind it. He also revisits the jobs question with a different angle, arguing that the more interesting territory is not what AI cannot do but what people will still choose a human for even when AI can technically do it just as well. The final question comes from a recent vibe coding session, covering whether to do all your planning and prompting inside a tool like Google AI Studio or to use a large language model first, and why the answer has a real financial implication if you are paying per credit. Subscribe to In AI Nutshell for daily ten-minute episodes built around the questions real people are asking about AI right now.

Andrew Miles Davis covers two significant feature updates and one new tool on this week's Cool Tools Tuesday, starting with ChatGPT's new memory sources panel that shows users exactly which past conversation each piece of stored information came from, making it far easier to audit, correct, and control what the model thinks it knows. He then covers what he considers one of the most useful updates he has seen in two years, the full integration of both ChatGPT and Claude directly inside Excel, allowing users to speak or type prompts and have the model act on the spreadsheet in real time without switching between platforms. The third tool is Scrunch, a brand audit platform that evaluates how often a company or its competitors are being cited inside AI platforms like ChatGPT, Claude, Gemini, and Perplexity when users prompt for something relevant to that industry. Subscribe to In AI Nutshell for three new tools every Tuesday with honest verdicts from someone using them in real work.

Andrew Miles Davis breaks down the five mistakes he sees people make with AI almost every single day, drawing on years of face-to-face training sessions with marketing teams, corporates, and individuals across the UK. From giving AI zero context and expecting a tailored result, to jumping between fifteen tools and mastering none of them, to underestimating how much your own expertise and story shapes the quality of the output, each mistake is explained with the same directness Andrew brings to his training rooms. The most common and most damaging mistake he saves for number one, using AI without a clear goal or outcome, which means the model has no direction and will produce confident but generic results every time. The episode closes with a reframe that applies to anyone who has ever felt like they are simply not good at AI. Subscribe to In AI Nutshell for daily ten-minute episodes that close the gap between where most people are with AI and where they need to be.