Welcome to the confusion matrix where we have lively and candid discussions about data, data science and AI in day to day life, business and beyond.
Reading the feed…
Alex and Pete follow up on their OpenClaw experiment after several more weeks of use. They discuss the upsides — always-on research, async collaboration on their website rebrand, and cheap DeepSeek running costs — alongside persistent frustrations: skills that get ignored, sycophancy in group chats, and the model flip-flopping between users. Alex digs into the […]
In this episode, Alex and Pete take their first deep dive into OpenClaw, the open-source AI agent framework that’s taken GitHub by storm. Alex walks through how he went from building a simple Ada bot for their group chat to running a full agentic orchestration layer across his art practice, podcasting, consultancy, and life admin. […]
Alex and Pete are joined by consultant Toby Dykes to challenge the production-line view of software delivery. They discuss Agile, Scrum, AI as an amplifier, constraints, risk, feedback loops, and why better outcomes come from experimentation, collaboration, and learning faster rather than simply pushing more work through broken processes. Mentioned in this episode: Jira — […]
Alex and Pete discuss Alex’s experiment building a PowerPoint presentation with a single AI prompt while making bread, achieving surprisingly decent “middling” results and debating homogenization versus creative excellence in AI-generated corporate content.
Alex and Pete dissect whether AI agents can actually replace knowledge workers, discussing why language models excel at testable tasks like coding, but fare less well at more general business activities that often require navigating the messy political realities of the corporate landscape.
Alex and Pete discuss how AI agents are collapsing the software development lifecycle (SDLC), eliminating manual coding steps whilst creating new requirements for testing, monitoring, and managing increasingly complex automated workflows at unprecedented scale.
Alex and Pete discuss our problematic tendency to project human characteristic on LLMs, and use anthropomorphic language when discussing them.
Alex and Pete grapple with the ethics of using generative AI in creative work—balancing utility against copyright theft, environmental impact, and career pressure whilst acknowledging there’s no easy resolution.
Alex and Pete examine whether AI will replace jobs within 18 months, discussing automation history, current limitations, and Microsoft’s predictions regarding workplace displacement.
Alex and Pete discuss AI coding agents’ limitations after Alex’s LLM client build revealed extensive bugs and missing features. They explore testing challenges, agent reliability metrics, and corporate liability concerns preventing enterprise adoption. This episode will make a lot more sense if you listen to the previous episode first.
Alex and Pete discuss Alex’s rebuild of his perma-regenerating LLM chat client. This time he did it properly! No messing, just hardcore, disciplined, systematic, agent-coding goodness. Join them as he walks Pete through the process in excruciating, step-by-step detail. The Vanishing Gradients episode Alex mentions.
Alex and Pete examine OpenAI’s comprehensive report on ChatGPT usage patterns, analysing classification methodologies and user behaviour across consumer and workplace contexts. They discuss the shift from advice-seeking to task execution, the dominance of writing and information-seeking functions, and implications for future AI adoption and market opportunities.
Pete and Alex examine AI model evaluation methodologies, comparing traditional machine learning metrics with the qualitative assessment challenges of large language models. They discuss the collaborative requirements between technical and business teams to establish evaluation criteria for generative AI systems, highlighting the subjective nature of testing conversational outputs versus binary classification tasks. With the help […]
Pete and Alex dig into cybersecurity risks with AI agents and generative AI systems. They cover two main problems: people coding dodgy applications without security knowledge, and hackers directly exploiting AI agents that have access to tools and data. Despite the scary possibilities, they reckon most vulnerabilities are manageable with decent security practices. Practical AI […]
Pete and Alex recap their recent AI discussions, covering why language model “hallucinations” are actually normal behaviour, how most AI proof-of-concepts fail due to poor ideas rather than technical issues, the impact on jobs and graduate recruitment, and the rise of AI coding agents that are reshaping software development. Practical AI – Dealing with increasingly […]
Alex and Pete discuss MIT’s study revealing 95% of GenAI projects fail despite massive enterprise investment. They explore why companies struggle to scale beyond pilots, the “shadow AI economy” of employees secretly using personal AI tools, and practical strategies for successful implementation including adaptive systems and treating AI procurement like business process outsourcing.
Alex explains his slow but unstoppable gravitation to text based interfaces and an “everything via the terminal” mentality. After all, who needs graphical operating systems? To do this, Pete and Alex take a ramble through the history of nerd-first user interfaces, discuss why keyboard layouts are stupid, how this relates to window based OSes and […]
Pete and Alex ponder whether we are at the point where LLMs are as good as they are going to get, and what the implications of this are. This requires a dip into the murky depths of what businesses exist to do and how the randomness that the LLMs generate is antithetical to how businesses […]
Join Alex and Pete as they discuss building software that suits only your needs and idiosyn-crazies using AI. Surely this is a good thing, and not just another apocalypse in disguise? There’s only one way to find out!
Pete and Alex discuss the challenges of deploying language models in end-user facing systems, the dilemma of diversity vs accuracy of output, and how all of this is a giant headache for data scientists and software engineers alike.
Pete and Alex discuss the challenges of training models for accuracy, reliability and capability, and various techniques that are being used to ensure these. They talk about how to think about how the models work, why they get things wrong and Alex makes an impassioned case for why cheese should be considered a fruit!
Alex and Pete battle the demons of unruly technology to give you a brief history of Business Intelligence and their relationship with it. They lament that it all seems to still be about dashboards, why this sucks and offer some alternatives. And yes, AI makes an appearance. Alex also recounts mysterious case of Strategy, the […]
Pete and Alex discuss the range of views on the impact of GenAI on jobs, the seemingly intractable situation that decision makers find themselves in regarding AI adoption, the marvels of modern enterprise procurement procurement, and the AI pricing problem. Oh, and we also get an update on the state of Alex’s thumb.
Alex recounts his harrowing tale of vibe coding hubris, a rogue AI agent, a busted deadline and a bruised ego. He and Pete discuss the need for a measured approach to using AI agents for mission critical work, the need for actual tech skills when using agents, and how managing them is not really that […]
Alex takes us on a vibe coding adventure, fixing a bug using an AI agent live (ish), before our very ears! Ada makes a rather fruity appearance, as she and Pete are dazzled by unreasonable effectiveness of AI coding agents. Finally, Pete and Alex discuss the implication to their discipline, the tech industry as a […]
