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I came across this article the other day, Chatbots Can Go Into a Delusional Spiral. Here’s How It Happens. which details how a 47 year old, corporate recruiter was convinced by ChatGPT that he had discovered a novel mathematical formula. Except he hadn’t. Over the course of 3 weeks, his interactions with ChatGPT led him down this spiral, only getting out of it when he used a different AI system to see if it made sense. It reminded me of one of the first Chat Bots, Eliza, from back in the 1960s. This bot was pretty effective, and all it did was reflect back to the user their own words. Some users began forming emotional attachments and shared personal and private data with it during their interactions. ...

Everyone’s talking about AI transforming how we work but how often do we actually use it to think better? America’s AI Action Plan was unveiled earlier this month. It focuses on 3 core pillars: Accelerate AI Innovation Build American AI Infrastructure Lead in International AI Diplomacy and Security. The full pdf is here: https://www.whitehouse.gov/wp-content/uploads/2025/07/Americas-AI-Action-Plan.pdf. Rather than write a post about the interesting things in this plan, I wanted to pivot this a bit and talk about how I use AI to interpret this plan to get a better understanding of it. We hear a lot about AI and how it can supercharge learning and understanding, but we see less examples of this in action. My approach works for me, and will evolve as my understanding and the tools evolve. This is also pretty basic, but it is intentionally so because some of this doesn’t have to be complex to immediately get better insights. ...

AI is going to fundamentally change the fabric of our society. Dr. Eric Schmidt suggests that within a year the vast majority of programmers will be replaced by AI programmers. Satya Nadella shared that Microsoft engineers are using AI to help write software (up to 20-30%) in a recent chat with Mark Zuckerburg. Even DARPA is creating exploratory models of Human-AI teams to understand how Humans+AI will work together. AI is forcing us to reflect on the work we do and ask ourselves the question of whether it has value or not. ...

AI, Agents, Workflows, LLMs - it all gets a bit confusing in today’s AI landscape around what all these mean. I want to break this down into a fairly simple framework to think about 4 distinct ways of using LLMs that get increasingly more complex. 1. Standalone LLM (Prompt in, Information Out) Standalone LLM This is the simplest and easiest way to engage a LLM. You enter a prompt into an LLM and it will respond based solely on its training data and the input you gave it in the prompt. This is most useful when you want a quick, self-contained answer that doesn’t require up-to-date data, personalization, or external reasoning, e.g. summarizing a paragraph, rewriting text, generating titles, or writing social media copy. You can also give it in-prompt context to help improve the answers - a concept often referred to as one/few-shot learning. ...

Model-Context-Protocol, or MCP as it’s more commonly referred to, came about in November 2024 when Anthropic introduced it to the world. But what is it really, why do we need it and how to get started? What is it? In its name, there are 3 elements: Model: This is the brain (the AI). It understands the question, figures out what it needs and when to ask for help. Context: Context of the situation (e.g. historical chat transcript) ...

The UK government recently released a report on their cross-department adoption and usage of M365 Copilot with some interesting results. It was an experiment that ran for 3 months across 20,000 government employees (Sept 2024 - Dec 2024) with a main goal being to understand how AI could impact productivity. Top-Level Insights From a positive persective, the key findings are as follows: Average Time Saved: Users reported saving an average of 26 minutes per day using M365 Copilot—equivalent to 13 working days per year. ...

The amazing leaps and bounds in the past few months with generative AI have changed the landscape for how AI will drive faster efficieny. ChatGPT is going to revolutionize development. Don’t believe me? Well here are 8 ways to interact with ChatGPT to super charge your development right now! Get started right here - https://chat.openai.com 1. Generate boiler plate code Ever sat down to start your next project and then had to go do a bunch of searching to figure out the right starting point. I have. Every. Single. Time. Probably because I am not coding everyday anymore but still, its a pain. ChatGPT makes this so much more efficient. Not only giving you the starting point but also a recommended structure too. ...

I have been exploring a bit around platform engineering. Its a new paradigm in software development, an evolution of DevOps. ...