When Models Lie and You're Still Paying for the Tokens

When AI models hallucinate confidently while burning through your token budget, you need more than better prompts you need better processes.In this episode, Kevin and Eli explore the reality of working with AI that lies while you pay, the evolution from saved prompts to voice-triggered workflows, and why validation loops matter more than model updates. From enterprise governance requirements to tech stack consolidation, this conversation cuts through the hype to reveal what actually works when deploying AI in real business contexts.Key topics covered:✅ Why model reliability requires systematic validation, not perfect AI✅ The shift from skills to snippets and voice-triggered workflows ✅ Enterprise governance requirements when litigation risk is involved✅ Tech stack consolidation as AI tools mature beyond experimentation✅ Cost economics driving procurement strategy changes✅ Building quality control loops that catch hallucinations before implementationTIMESTAMPS:00:00 — Intro and Sora commercial viability discussion05:30 — Video generation landscape: Veo, SeeDance, Higgs Field15:00 — Model quality regression and hallucination experiences 25:00 — Skills vs snippets: workflow evolution deep dive35:00 — Enterprise governance and validation requirements45:00 — Tech stack consolidation and platform comparisons53:00 — Eli's transition and mental health focusShow Notes & Links: https://www.spark6.com/podcast Submit listener questions: elijah@spark6.comkevin@ascendlabs.ai  Check out Kevin’s stuff:Ascend Labs: https://ascendlabs.ai/Follow Kevin on LinkedIn: https://www.linkedin.com/in/kevinguywilliams/ Check out Eli’s Stuff:SPARK6 Agency: https://www.spark6.com/Sign up for FREE AI Framework Friday Newsletter: https://www.spark6.com/newsletterFollow Elijah on LinkedIn:https://www.linkedin.com/in/elijahszasz/