— Introduction — Reframing agentic AI as an evolution that demands first principles thinking0:50 — What companies are getting wrong at the very start — the fascination phase2:13 — Is agentic AI truly novel or just a rebrand of what we already had3:03 — The right questions to ask — knowledge context tooling and instruction4:51 — Pilot purgatory — AI projects stuck in QA that never make it to production5:46 — First principles have not changed — what problem are we solving and what outcome do we want8:50 — Are we implementing true agentic AI or just rebranding existing workflows9:59 — Generative AI as a vending machine vs agentic AI as a sous chef11:51 — Model in the loop — when you are really just calling a more sophisticated API13:33 — Where agentic AI adds the most value — exception handling in enterprise workflows16:40 — Governance as an enabler — why dirty data is a governance failure not an AI failure18:19 — What feels familiar and what feels genuinely new about AI adoption today20:29 — The importance of foundation before implementation — and the rush that bypasses it23:29 — 40% of AI projects will fail by 2027 — and the bank that ran 350 use cases25:18 — What actually determines AI success vs quiet failure26:28 — Human in the loop vs human on the loop — why design matters from day one29:41 — Agentic AI is a business project not a technology project31:05 — Do we want true autonomy or accountability? The answer is both🔔 Don't forget to Like, Subscribe, and hit the notification 🔔 ✔ Subscribe: https://www.youtube.com/jonmyer/?sub_confirmation=1📱 Social Media Twitter: https://twitter.com/_JonMyerWebsite: https://jonmyer.comLinkedIN: https://www.linkedin.com/in/jon-myer/Spotify: https://open.spotify.com/show/0wjJzdIwctq4o4pTXM2KSFLike my sounds? Here's my audio source: https://www.epidemicsound.com/referral/fj9o9k#aws #awscloud #podcast #podcasting #costoptimization #finops #cloudcost #cloudoptimization