O TYM PODKAŚCIE 🔗

Częstotliwość aktualizacji:
every 17 days
Średnia długość dźwięku:
42 minutes
Wywiady gościnne
Język angielski
Stany Zjednoczone
27 odcinków
od 25 sierpnia 2025
episodic

NAJNOWSZY ODCINEK 🔗

Your AI agents work great for you. Getting your team to use the same AI agents is a completely different problem, and it's one most companies trying to scale AI haven't solved yet. This episode breaks down why single-player AI tools like Claude Code and Codex don't automatically scale into team-wid…

WYSZUKAJ MINIONE ODCINKI

Wyszukaj minione odcinki AI, Actually.

POPRZEDNIE ODCINKI

Most AI is still billed like a utility. You pay for usage and hope it adds up to something worth the spend. That model breaks down once an agent starts finishing entire jobs instead of just responding to prompts. The real story: pricing has to be tied to what the agent actually delivers, not how mu…
Managing AI costs has become increasingly difficult. Uber’s CTO made headlines when he shared the company had burned through its entire 2026 AI budget in just 4 months. That's the problem this episode tackles head on. Token prices are falling for a given level of intelligence, but most companies' a…
A tweet from Peter Steinberger asking whether AI builders should still be "talking loops" or "shifting to graphs" hit three million views and split the AI world into camps. Most business leaders have no idea what either term means, or why the answer changes how much your AI systems cost, how reliab…
The token bills are arriving, and a lot of teams do not like what they see. Halfway through 2026, the promise of cheap, abundant intelligence is colliding with enterprise reality. Behind the headlines about new models and rising prices is a simpler story about whether your AI spend is actually buyi…
Everyone is waiting for the next model to make their AI problems disappear. The teams getting real value already figured out the model was never the hard part. In this episode, the crew reacts to Nate B. Jones and his argument that the trillion dollar opportunity sits in completed workflows, not sm…
Everyone is waiting for the next model to make their AI problems disappear. The teams getting real value already figured out the model was never the hard part. In this episode, the crew reacts to Nate B. Jones and his argument that the trillion dollar opportunity sits in completed workflows, not s…
Most enterprise AI projects don't fail because of the model. They fail because of data, specifically, the gap between having data and having data an AI can actually understand and act on. This is the last mile problem, and it's quietly killing AI ROI across the enterprise. That's the real story be…
Popularized by Palantir, the term "Forward Deployed Engineer" is everywhere right now.But what does it actually mean, and is it even the right label? In Episode 19, the AI, Actually crew digs into one of the hottest buzzwords in enterprise tech, separating the signal from the noise and getting real…
Most companies are announcing AI strategies and running pilots that go nowhere. Meanwhile, individuals using AI every day are quietly getting 10x leverage on their work, and the gap is widening. The real story isn't about tools or models. It's about people, habits, resistance, and what it actually…
Zastrzeżenie: Podcast i grafika osadzone na tej stronie pochodzą z AnswerRocket, który jest własnością jego właściciela i nie jest powiązany ani wspierany przez Listen Notes, Inc.