The Confusion Matrix

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.