AI, Actually – Episode 14: Autonomous Agents in the Enterprise and How AI is Disrupting SaaS

Welcome to Episode 14 of AI, Actually! This week Pete Reilly hosts Jim Johnson, Shanti Greene, and Stew Chisam for a conversation about three interconnected developments forcing enterprises to rethink everything from organizational structure to software procurement. The discussion opens with OpenClaw (formerly ClaudeBot and briefly MoltBot)—an open-source AI assistant that doesn’t just suggest actions […]

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AI, Actually – Episode 13: Building Software 10x Faster with AI: A Real-World Walkthrough

Welcome to Episode 13 of AI, Actually! This week takes a different format—Pete Reilly hosts a live demo and discussion with Alon Goren, Mike Finley, and Andy Sweet 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

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AI in Business Podcast: Reducing R&D Cycle Time in Pharma Without Increasing Regulatory Risk

Featuring Vaithi Bharath, Associate Director of Data Science & AI Solutions at Bayer. In a recent episode of the AI in Business Podcast sponsored by AnswerRocket, Vaithi Bharath, Associate Director of Data Science & AI Solutions at Bayer, joined host Matthew DeMello, Editorial Director at Emerj AI Research, to explore one of pharma’s most persistent

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AI, Actually – Episode 12: Agent Ops: Why Keeping AI Agents Running Is Harder Than Building Them

Welcome to Episode 12 of AI, Actually. This week features Jim Johnson as host, joined by Joey Gaspierik, Nicole Kosky, and Stew Chisam for 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

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Beyond Benchmarks: How to Choose Between Gemini 3, GPT 5.2, and Opus 4.5

Co-authored by Stew Chisam, Operating Partner, StellarIQ If you blinked recently, you might have missed a major shift in the AI landscape. In the span of just a few weeks, the industry has delivered a rapid succession of sophisticated releases: OpenAI’s GPT 5.2, Anthropic’s coding specialist Claude Opus 4.5, and Google’s efficiency engine, Gemini 3 Flash.

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AI, Actually – Episode 11: Open AI’s Playbook for Scaling AI, Why Generalists Are Winning, and Revenue-Driven ROI

Welcome to Episode 11 of AI, Actually! This week features Pete Reilly as host, joined by Jim Johnson, Alon Goren, and Shanti Greene to unpack 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

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Don’t Wait for Perfect AI: Why the ‘Decade of the Agent’ Means Start Today

Why Karpathy’s “Decade of the Agent” Means You Need to Start Today Andrej Karpathy just handed executives everywhere what might sound like permission to wait. In a recent Dwarkesh Patel podcast, the AI expert said 2025 isn’t the “year of the agent,” it’s the “decade of the agent.” I can already hear the boardroom conversations:

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AI, Actually – Episode 10: Gemini 3 Deep Dive and Bold Predictions for 2026

Welcome to Episode 10 of AI, Actually! This week features Pete Reilly as host, joined by our technical dream team: Andy Sweet, Shanti Greene, and Stew Chisam. 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,

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The People Problem of AI: Navigating AI Transformation When Half Your Team Isn’t Convinced

You must take a human-centric approach to engage a skeptical workforce. Picture this: You’re a leader introducing new AI tools that promise to revolutionize how work gets done. The executives are thrilled. The consultants are celebrating. But when you look around your team, you see crossed arms, furrowed brows, and a Slack channel full of

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AI in Business Podcast: Turning Consumer Goods Data into Real-Time Business Decisions

Featuring Mike Finley, CTO at AnswerRocket Our own Mike Finley, CTO at AnswerRocket, recently joined Matthew DeMello, Editorial Director at Emerj AI Research, on the AI in Business Podcast to continue the conversation about enterprise AI in CPG. Building on Jim Johnson’s earlier appearance, Mike dives deep into the technical and strategic realities of moving

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AI, Actually – Episode 9: What’s Actually Working in Enterprise AI: Business Value, Success Predictors, and Agent Ops

Welcome to Episode 9 of AI, Actually! This week features Jim Johnson as host, joined by three voices from the front lines of AI implementation: Joey Gaspierik (Sales Director who meets with clients daily), Shanti Greene (Senior Data Scientist with deep technical expertise), and Nicole Kosky (leader of our AI Business Transformation practice). This episode

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AI in Business Podcast: CPG Data Challenges to Business Value with Agentic AI

Featuring Jim Johnson, President at AnswerRocket Our own Jim Johnson, President at AnswerRocket, recently joined Matthew DeMello, Editorial Director at Emerj AI Research, on the AI in Business Podcast to explore how agentic AI is revolutionizing consumer packaged goods (CPG) analytics. The conversation cuts through the hype to reveal practical strategies for companies drowning in

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AI, Actually – Episode 8: The Decade of the Agent, Enterprise AI Reality, and Why Waiting Will Cost You

Welcome to Episode 8 of AI, Actually! This week features Pete Reilly as host, joined by Alon Goren (founder and CEO), Jim Johnson (who leads our services organization), and Mike Finley (our guide through the LLM landscape). The team tackles one of the hottest debates in enterprise AI: is 2025 really the “year of the

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AI, Actually – Episode 7: OpenAI Dev Day Reactions and What It Takes to Get Agents in Production

Welcome to Episode 7 of AI, Actually! This week features Jim Johnson stepping in as host (while Pete enjoys 30A), joined by Mike Finley, and two special guests from our AI Business Transformation team: Nicole Kosky, who leads the practice, and Reilly Carroll, Senior AI Solutions Consultant. Fresh off client meetings in Europe, Jim brings

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AI, Actually – Episode 6: Breaking Down Nate B. Jones’ 6 Engineering Principles for AI Agents

Welcome to Episode 6 of AI, Actually! This week features Pete Reilly as moderator, joined by Mike Finley, Andy Sweet, and Stew for a deep dive into the engineering principles that separate successful AI implementations from failed proofs of concept. This episode unpacks six critical engineering principles from AI thought leader Nate B. Jones, translating

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Forward Deployed Engineers: The Critical Role That Drives AI Success

AI is at an inflection point. Models are powerful, tools are plentiful, and pilots are easy to launch. Yet most organizations stall when moving from prototypes to meaningful transformation. The constraint isn’t intelligence; it’s execution. The solution is not new. For decades, the best engineering outcomes have come when builders sit close to users. Palantir

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AI, Actually – Episode 5: The $10T AI Opportunity, Forward Deployed Engineers, Year of the Agent Check-In, and Replit Agent 3

Welcome to Episode 5 of AI, Actually. This week features Pete Reilly as our moderator, joined by Alon Goren (CEO and co-founder), Shanti Greene (Head of Data Science and AI Innovation at AnswerRocket), and Stew Chisam (Operating Partner at StellarIQ). This episode tackles three major themes shaping enterprise AI today. First, we dive into Sequoia’s

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Data Science Democratized: Why ML Models and LLMs are a Powerful Combination

The ML vs. LLM Debate Is Missing the Point “Should we build ML models or just use LLMs?” This is the wrong question, but I hear it constantly. Companies either pour millions into enterprise LLM licenses hoping they’ll handle everything, or they build sophisticated ML models that only data scientists can understand and translate. Most

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AI, Actually – Episode 4: Kimi, Shadow AI, Machine Learning vs. LLMs, Prompt vs. Context Engineering and Local Models

Welcome to Episode 4 of AI, Actually! This week brings a fresh lineup with Jim Johnson stepping into the moderator role, joined by Mike Finley, Andy Sweet (leader of AnswerRocket’s advanced models practice), and Shanti Greene (senior data scientist and our resident “mad scientist running more models locally than OpenAI”). This episode dives deep into

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Western Specialty Contractors Announces Partnership with AI Solutions Company AnswerRocket to Improve Bidding Outcomes

ST. LOUIS, MO (Sept. 16, 2025) – In construction, an accurate bid can mean the difference between a profitable year or continuous delays and costly overruns. Many contractors continue to rely on spreadsheets, fragmented data, or gut instinct to prepare bids. This leaves too much room for errors.  Bidding in construction is complicated by inflated

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AI, Actually – Episode 3: AI Pilot Failures, Agent Disruption, and the AI Talent War

Welcome to Episode 3 of AI, Actually! This week, we’re joined by Alon Goren, our CEO and co-founder who’s been leading AnswerRocket since 2013. Together with Pete Reilly, Mike Finley, and Jim Johnson, we dive deep into three critical topics shaping the AI landscape right now. First, we tackle the infamous MIT study claiming a

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CABI Lunch and Learn: AI Survival Guide Navigating the Pitfalls Nobody Warns You About

WashU Olin’s Center for Analytics and Business Insights (CABI) hosted Andy Sweet and Shanti Greene from AnswerRocket for a candid Lunch & Learn on what it really takes to succeed with enterprise AI. Key Topics Covered: Perfect for: CTOs, data science leaders, business executives, and anyone responsible for AI strategy and implementation in mid-to-large enterprises.

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Why 95% of Enterprise AI Projects Fail: The Field Lessons MIT’s Study Missed

MIT’s NANDA initiative just published a study that confirms what those of us in the trenches have been seeing: 95% of enterprise generative AI pilots fail to deliver measurable business value. Despite $30-40 billion in enterprise investment, only 5% of pilots progress beyond early stages to achieve rapid revenue growth. Let me break down what’s

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AI, Actually – Episode 2: Why 95% of AI Pilots Fail, Building Effective Agents, Computer Use, and MCP

MIT just dropped a bombshell study revealing that 95% of enterprise AI pilots are failing to achieve revenue acceleration. But here’s the twist – it’s not because the technology is broken. In this episode of AI, Actually, we dig deep into why companies are struggling with AI implementation and what separates the successful 5% from

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