Episode 32: Why AI Didn’t Work When You Tried It

In Episode 32 of Anthony and Greg on Intelligence (AGI), Anthony Moggio and Greg Prost go back to the basics — because one of the most common things they hear is: “I tried AI, and it didn’t work.” But often, the issue is not the AI. It is how the tool is being used. Anthony and Greg break down why different AI tools are designed for different jobs. A large language model like ChatGPT is not the same thing as an image generator, a video tool, a retrieval system, a spreadsheet assistant, or an agentic workflow. Using the wrong AI tool is like using a hammer when you actually need a screwdriver. The conversation explains several core concepts in plain language, including: -why AI models may not know current information, -how generative AI creates answers, -why the same prompt can produce slightly different responses, -what “context” really means, -why voice prompting can be more effective than typing, -how retrieval tools differ from large language models, -and why agents are becoming the next major phase of AI. Anthony gives a simple example using dinner planning: asking “dinner?” gives the AI almost nothing to work with. But explaining what meals you already had, how much time you have, what equipment you can use, and what constraints you’re working around gives the AI enough context to provide a much better answer. That same principle applies in professional work. The episode then turns to a practical local government example: grant writing and grant reporting. Anthony walks through how AI can help organize grant agreements, reporting requirements, vendor expenses, project details, financial exports, and supporting documentation. Instead of spending hours trying to reconstruct what happened across multiple departments, AI can help identify the reporting requirements, categorize expenditures, draft the needed tables, and prepare a report for human review. The key point: AI is not magic. It is a tool. And like any tool, the result depends on whether you know what it is built to do, what information it needs, and how to guide it. If you have tried AI and felt disappointed, this episode is a practical reset. Anthony and Greg explain how to think about AI more clearly, how to avoid common mistakes, and how to start getting more useful results. Subscribe for grounded, real-world conversations about how AI is actually changing work, government, finance, and decision-making.