AI Evolution

In this chat the crew dig into a wild new open-source autonomous agent (“Claudebot / Maltbot / OpenClaw”) and what its chaotic behaviour says about agency, safety, and the blurry line between “AGI” and convincing simulation.
Then they pivot to AI tooling (Claude vs ChatGPT), guardrails, prompt tactics (including the “potato prompt”), and finish with a big-picture debate: what happens if quantum + AGI + fusion all mature at once and whether that convergence equals “the singularity.”

In this New Year catch-up, the AI Evolution crew dives into their post-Christmas tech hauls, from the quirky Rabbit R1 to a game-dev fueled Steam Deck.
They unpack the growing friction between playful AI experimentation and the creeping flood of low-quality generative content. Is the AI bubble about to burst in 2026? Are vibe coding and agents actually useful yet? And why does human-made content still matter more than ever?
Tune in for a relaxed but insightful conversation on where AI stands, and stumbles, at the start of 2026.

In this episode of the AI Evolution Podcast, Alan, Ben and David dive deep into the latest developments in the world of AI. From testing the limits of Sora 2 and video generation tools to discussing AI agents, automation, and how small businesses are using GPT to streamline operations. This episode is packed with real-world use cases, insights, and a healthy dose of skepticism.
We explore:
Why AI video is still hit-or-miss, and where it shines
The challenge of maintaining authenticity in a world full of “AI slop”
How AI tools are reshaping creativity, education, and hiring
The future of agentic workflows and what they can’t do yet
Why trust in AI outputs is more crucial than ever
Concerns around AI replacing junior roles and what that means long term
The viral “X1 Robot” and what it really says about robotics hype

If you’re navigating the intersection of AI, media, and the future of work, this one’s for you.
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In this summer recap episode, the hosts pick apart the biggest AI stories of the season. GPT-5’s rocky launch, Grok’s reputation problem, Apple’s AI missteps, and the rise of “Duolingo for coding.” They also tackle the wild idea of AI rights and what happens if machines start demanding more than just better prompts.
A sharp, funny, and sometimes uneasy look at where AI is heading.
Takeaways:
AI hype vs. reality – GPT-5 launched with a messy rollout, showing how over-promising and under-delivering fuels mistrust. The conversation highlights how people are adjusting to using AI differently, more as an idea partner than a content generator.
Big tech is stumbling – Apple has fallen far behind in AI, especially with Siri, while Elon’s Grok is chaotic and unlikely to gain enterprise trust. The sense is that tech giants are making questionable bets (foldable phones, headsets, “everything apps”) while missing more practical AI opportunities.
Ethics and the future – The hosts wrestle with deeper questions: should AI one day have rights? What happens if models show self-preservation or sentience? These discussions matter now, before AGI arrives, and they tie into bigger shifts like fusion power and quantum computing potentially supercharging AI.

Should you always be told if you’re talking to an AI? This episode delves into the recent scandal surrounding an Australian radio station's use of an AI host without proper disclosure. David Brown, Ben Harvey, and the team explore the blurred lines between function and deception, asking where we should draw the line on transparency.
They debate AI’s growing role in areas like healthcare, law, and media, questioning whether humans will remain the trusted source in high-stakes situations. The episode also tackles a controversial topic: Is AI-generated content really worse than Photoshopped images we’ve accepted for decades?
Packed with thoughtful discussion, practical examples, and a few laughs along the way, this episode offers a grounded look at the ethical grey areas in our AI-driven world.
Top 3 Takeaways:
AI Disclosure Depends on Context: The hosts debated whether AI-generated content should be disclosed. David argued disclosure isn’t always necessary, especially for functional tasks like booking appointments. Others felt that in contexts involving trust, such as news, politics, or medicine, disclosure is vital to prevent misinformation and maintain credibility.
AI’s Future Role in Expertise and Decision-Making: The conversation explored how AI could surpass human capabilities in fields like medicine, law, and journalism. In 2050, people might trust AI more than humans for diagnoses, legal defence, and even judgments, given AI’s superior access to data and consistency.
Image Manipulation and the Double Standard: The group highlighted a gap in public scrutiny: AI-generated images must be flagged, but heavily edited photos from traditional tools like Photoshop are often not. They questioned whether the real issue is how something was altered or why, arguing for consistent transparency standards.