AI Automations for Business

The only actionable insight is 'wait a few weeks before updating automations to a new model' and 'consider self-hosted open-source models as a fallback' - both of which are thin observations stretched across 17 minutes of largely circular agreement and filler. There is almost no non-obvious analysis of the underlying regulatory or technical dynamics.

“I'm probably going to wait a couple of weeks before I'll test it, but then I'll wait a couple of weeks and then see if there's any backlash”

“a lot of the open source are a bit, um, how do I put it, they're not as good as the big models from the big three providers”

The discussion recycles standard AI-community talking points (open source as fallback, vendor lock-in risk, data sovereignty) without any contrarian framing or first-principles reasoning. The 'wake-up call' framing is invoked but never developed into a distinctive argument.

“I think it's just the, I think for me the biggest thing from it was the speed and the total loss of access to a model”

“hopefully one day in the UK we'll have our own frontier model”

There are no external guests - only two co-hosts. Noel presents as a hands-on automation practitioner but offers no verifiable credentials, no indication of business scale, and no professional context that would establish authority on AI risk or vendor management.

“normally what I would do is assess a new model, if it's any good, uh, or it fits my use case, I would then swap it out, uh, and put into my Automations”

“I use Claude code a hell of a lot on the desktop app”

A handful of concrete specifics appear - the cost comparison ('double the cost of Opus,' Sonnet doing the job 'for like 20') and named tools (Zapier, Make, DeepSeq, Mistral, Kimi 2.5) - but these are isolated data points in an otherwise vague conversation, and the central claims about 'Fable 5' and 'Mythos' appear to be factually unverifiable or inaccurate, undermining evidential credibility.

“it was double the cost of Opus”

“the price difference between Sonnet, which is still a very, very capable model, um, to Fable is huge”

Katie consistently follows up with purpose-driven prompts ('What does this actually mean for users?', 'Can you explain why you feel that way?') that advance the conversation, but she never challenges Noel's claims, pushes on vague assertions, or introduces any productive tension - making the exchange agreeable but not rigorous.

“Okay, so what does this actually mean for users?”

“When, in what sense do you say that? Like it's been a wake up call but like what, why would you, why are you saying that?”