AI, Actually
Tired of the AI hype? So are we.
Welcome to AI, Actually: the podcast that cuts through the noise and gets real about how artificial intelligence can work for your business.
Feb 10, 2026
Ep. 14: Autonomous Agents in the Enterprise and How AI is Disrupting SaaS
This week the gang tackles the question everyone’s avoiding: we’re not just talking about productivity tools anymore, we’re talking about onboarding non-human employees. Complete with email addresses, Slack accounts, budgets, and human supervisors who are accountable for their work. The conversation closes with the build versus buy debate, examining why SaaS stocks are tanking despite strong earnings and whether enterprises should now build their own software. As Stew puts it: “Things are going to get really weird, really fast.”
Jan 27, 2026
Ep. 13: Building Software 10x Faster with AI: A Real-World Walkthrough
This week the gang hosts a live demo and discussion as they walk through a working CRM built in just a few weeks using AI coding agents. But this isn’t about showing off a new CRM—it’s about revealing what next-generation software development actually looks like. The conversation unpacks how a small team leveraged Claude Code, Cursor, and multiple LLMs to build production-grade software at 10x the traditional speed. They demonstrate AI-powered lead capture from audio files, automated email workflows following custom playbooks, and an action inbox that actually enables salespeople instead of burdening them. The discussion reveals fundamental shifts: build vs. buy is being rewritten, product managers might need to code, and enterprises should be buying flexible building blocks rather than finished products. Most striking: when source code becomes readable to AI agents, maintenance stops being a specialist job and becomes a generalist capability
Jan 13, 2026
Ep. 12: Agent Ops: Why Keeping AI Agents Running Is Harder Than Building Them
This week the gang takes a deep dive into what might be the most important emerging discipline in enterprise AI: Agent Operations (AgentOps). As enterprises move from impressive demos to production agents doing real work, a critical question emerges: who’s responsible when these digital workers drift off task? The conversation reveals that this isn’t just “DevOps for AI”—it’s fundamentally different. There’s no blue screen of death when an agent subtly degrades. Performance changes aren’t binary failures but gradual drift across three levels of complexity. And the skills required span business objectives, AI knowledge, and IT expertise in ways that traditional organizational structures aren’t designed to handle. The team tackles the hardest question: should IT or business own agent operations? And why the answer determines whether your AI initiatives succeed or fail.
Dec 16, 2025
Ep. 11: Open AI’s Playbook for Scaling AI, Why Generalists Are Winning, and Revenue-Driven ROI
This week the gang unpacks OpenAI’s recent white paper “From Experiments to Deployments: A Practical Path to Scaling AI.” But this isn’t just a review—it’s a reality check based on years of front-line experience helping enterprises actually do this work. The team tackles the central thesis: the old IT playbook is dead. Quarterly releases don’t work when models change every two weeks. Throwing requirements over the wall doesn’t work when the last mile requires deep business context. And thinking about “AI projects” misses the point entirely—these are business problems that happen to use AI. The conversation reveals hard truths about organizational structure, the shift from specialists to generalists, and why mid-market companies have an unprecedented opportunity to leapfrog their larger competitors. Plus, Alon shares fresh insights from building with GPT-5.2 Pro and why the speed of prototyping is fundamentally changing what’s possible.
Dec 2, 2025
Ep. 10: Gemini 3 Deep Dive and Bold Predictions for 2026
Fresh off Gemini 3’s launch, the team goes deep on what’s actually different, how it stacks up against GPT-5.1 and Claude, and why Google’s play is about ecosystems, not just models. But this episode isn’t just a model review—it’s about what these advances mean for enterprises navigating vendor lock-in, the commoditization of LLMs as primitives, and the critical importance of scaffolding over raw intelligence. The second half delivers bold predictions for 2026: from content exhaustion and the IT reckoning to agents working autonomously for hours (or longer than most employees). The team explores why the business model hasn’t caught up to LLM advances, and why 2026 might be the year enterprises finally figure out how to build real intelligence into their systems.
Nov 18, 2025
Ep. 09: What’s Actually Working in Enterprise AI: Business Value, Success Predictors, and Agent Ops
In this episode, the AI, Actually crew tackles the elephant in the room: MIT’s famous study claiming 95% of AI initiatives fail. But instead of accepting that narrative, the team digs into what’s really happening in enterprise AI—from the “easy button” fallacy to why mid-market companies might leapfrog their larger competitors. The conversation reveals critical insights about the gap between IT and business expectations, why “agent operations” is becoming a discipline as important as DevOps, and why treating AI like a new employee changes everything about how organizations should approach implementation.
Nov 4, 2025
Ep. 08: The Decade of the Agent, Enterprise AI Reality Check and Why Waiting Will Cost You
In this episode, the AI, Actually crew tackles the gap between AI hype and enterprise reality. Pete Reilly, Alon Goren, Mike Finley, and Jim Johnson break down why current LLMs aren’t perfect, why that doesn’t matter for ROI, and how smart companies are capturing value right now versus waiting ten years. From coding agents that ship features overnight to the organizational challenges of keeping AI solutions on the rails, this is your practical guide to navigating the AI landscape today.
Oct 21, 2025
Ep. 07: OpenAI Dev Day Reactions and What It Takes to Get Agents in Production
In this episode, Jim Johnson steps in as host alongside Mike Finley, with special guests Nicole Kosky (who leads AnswerRocket’s AI Business Transformation Practice) and Reilly Carrolll (Senior AI Solutions Consultant). Together, they tackle the practical, nitty-gritty challenges of bringing agents to life for enterprise clients—from gathering requirements that users don’t know they have, to managing the surprising differences between what stakeholders say they need versus what they actually ask once they’re hands-on with an agent.
Oct 7, 2025
Ep. 06: Breaking Down Nate B. Jones’ 6 Engineering Principles for AI Agents
In this episode, the AI, Actually crew unpacks six critical engineering principles for building reliable AI agents—principles that separate proof-of-concepts from production-ready systems. Pete, Mike, Andy, and Stew break down insights from AI expert Nate B. Jones, translating technical concepts into business-focused guidance. They explore why AI memory isn’t just about storage, how to bound uncertainty without killing creativity, and why monitoring AI systems requires a completely different approach than traditional software.
Sep 23, 2025
Ep. 05: The $10 Trillion AI Opportunity, Forward Deployed Engineers, Year of the Agent Check-In, and Replit Agent 3
In this episode, the AI, Actually crew tackles the gap between AI’s promise and its practical deployment in the enterprise. From bold predictions about agent automation to Palantir’s forward deployed engineer model, we explore what it really takes to move beyond ChatGPT licenses to actual business transformation.
Sep 16, 2025
Ep. 04: Kimi, Shadow AI, Machine Learning vs. LLMs, Prompt vs. Context Engineering, and Local Models
The AI Actually crew tackles the pressing concerns keeping enterprise leaders up at night: shadow AI infiltrating organizations, the crucial distinction between machine learning and LLMs, and why context engineering matters more than prompt engineering. Jim Johnson takes the moderator chair, joined by regular Mike Finley and special guests Andy Sweet (Advanced Models Practice Lead) and Shanti Greene (Head of Data Science and AI Innovation).
Sep 9, 2025
Ep. 03: AI Pilot Failures, Agent Disruption, and the AI Talent War
In this episode, the AI, Actually crew tackles the hard truths about why enterprises struggle with AI implementations and what separates the toys from the tools. The conversation kicks off with AnswerRocket CEO Alon Goren sharing his journey from pre-PC era computing to building AI solutions that actually work
Sep 2, 2025
Ep. 02: Why 95% of AI Pilots Fail, Building Effective Agents, Computer Use, and MCP
In this episode, we dig into why companies are hemorrhaging money on AI that never delivers real value, and what the successful 5% are doing differently. Forget vendor promises and get ready for some uncomfortable truths about why your text-to-SQL dreams might be nightmares waiting to happen.
Aug 25, 2025
Ep. 01: Vibe Coding, Enterprise AI Struggles, and GPT-5
Is your company’s AI strategy stuck in the sandbox? You’re not alone. Despite the endless hype, many large companies are finding their AI projects are stuck in the experimental stage. In this episode, we get real about why organizations are struggling and what you can actually do about it. Forget the hype and join us for a candid discussion on the real-world challenges and opportunities of enterprise AI. We cut through the noise to give you a practical playbook for moving forward.