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 buying business value. In this episode of AI, Actually, Jim Johnson, Nicole Kosky, Shanti Greene, and Andy Sweet connect three topics that look unrelated on the surface: early results from Fable 5, the real cost of tokens and total cost of ownership, and how to think about AI ROI.

The throughline is one piece of math. Grow the numerator, scope the denominator honestly, and build the business case before you deploy.

Topics covered:

• Early field results from Fable 5 and why not all tokens are created equal
• Token pricing, the end of the subsidy era, and the surprise-bill problem
• What actually belongs in the denominator of an AI business case
• The human in the loop, AgentOps, and the trust gap that paces adoption

• Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/ 
• Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ 
• Jim Johnson, President, AnswerRocket - https://www.linkedin.com/in/jim-johnson-bb82451/
• Nicole Kosky, Senior Director of Services, AnswerRocket - https://www.linkedin.com/in/nicole-kosky-5b9a3b6/

Learn more about AnswerRocket: answerrocket.com

Chapters:

00:00     Introduction to AI topics and guest insights

02:20     Experimenting with Fable 5 and its value

04:00     Understanding token consumption and TCL

05:34     Cost and ROI considerations in AI models

07:52     The role of model reasoning and creativity

10:07     Managing costs and change in AI deployment

13:28     Strategic planning and business case development

15:02     Evolving models and maximizing value

16:51     Testing, evaluation, and human-in-the-loop

18:53     Leadership and organizational adoption of AI

21:15     The "Trust Gap" for Adoption

25:27     Closing thoughts and industry outlook

#EnterpriseAI #AIROI #AgenticAI #AIStrategy #LLM #AgentOps #AIActually

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 smarter chat.

This is AI, Actually, the show that cuts through the hype and gets practical about putting AI to work. We dig into why the model alone will never get you there, what happens to SaaS in an agentic world, and how to spot the workflows actually worth automating.

You'll learn:

• Why completed workflows, not models, are where enterprise value actually lands
• How to use evaluation and a clear definition of "what good looks like" as the starting point for any build
• What forward deployed engineers really do, and why the business person beside them matters just as much
• Why seat-based SaaS pricing is breaking and what replaces it
• How to pick a first workflow to automate using repeatability, ROI, and human in the loop
• What harnesses are and why they are becoming the next layer of value
  

Learn more about AnswerRocket: https://answerrocket.com/ 

Get Ethan Mollick’s book, “Co-Intelligence: Living and Working with AI” here: https://a.co/d/0jl6kAMd  

Follow the Gang:

• Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/ 
• Mike Finley, Co-Founder, AnswerRocket & StellarIQ  - https://www.linkedin.com/in/mikefinley/ 
• Pete Reilly, Co-Founder, AnswerRocket & StellarIQ - https://www.linkedin.com/in/petereilly 
• Ada Gil, Director, AI Business Transformation - Practice Lead - https://www.linkedin.com/in/ada-gil-84837648/ 

Chapters:
00:00     Introduction to AI Business Transformation
03:54     The Model Alone Isn't Enough
08:21     AI Won't Be Implementing Itself
11:43     Rebuilding Workflows and Embracing Change
13:25     The Future of SaaS and AI Integration
18:24     Navigating the Expenses of SaaS Platforms
23:14     The Evolution of Standards in AI
25:34     Understanding Workflows for Automation
28:34     Defining Success in Automation
32:35     The Value of Forward Deployed Engineers
34:47     Identifying Valuable Workflows
38:41     Economic Considerations in Automation
40:30     Concluding Thoughts & Harnessing AI
43:56     Evaluating Agent Performance
45:55     Combining Domain Expertise with Technology

#EnterpriseAI #AgenticAI #AIStrategy #AIAgents #CompletedWorkflows #ForwardDeployedEngineers #AIImplementation

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 behind the stat: 87% of AI projects never reach production.

This is Episode 20 of AI, Actually, the podcast that cuts through the hype to help business leaders get real value from AI. Jim Johnson is joined by Andy Sweet, Nicole Kosky, and Ben Titmus, who leads the data and infrastructure practice at AnswerRocket, to break down what it actually takes to make enterprise AI work at the data layer.

You'll learn:

• What "data readiness" actually means for AI, and why it's different from what your BI dashboards needed
• How to define and build a semantic layer iteratively, without a massive multi-year initiative
• Why throwing everything at an LLM produces confident-sounding wrong answers, and how guardrails prevent it
• How Microsoft Fabric, Snowflake, Databricks, and BigQuery are each approaching semantic layer infrastructure
• Why model-swappability, not model loyalty, is the right architecture posture right now
• What Chief Data Officers should do in the next 90 days to lead AI transformation from the front

This episode is designed for: Chief Data Officers, VP Analytics, data engineering leaders, and any executive responsible for making AI work inside a real business.

Learn more about AnswerRocket's enterprise AI solutions: https://answerrocket.com/ 

Speakers:

• Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ 
• Jim Johnson, President, AnswerRocket - https://www.linkedin.com/in/jim-johnson-bb82451/
• Nicole Kosky, Senior Director of Services, AnswerRocket - https://www.linkedin.com/in/nicole-kosky-5b9a3b6/
• Ben Titmus, Senior Director, Practice Leader - AI Data, Platforms and Infrastructure - https://www.linkedin.com/in/benjamin-titmus-a2817626/ 

Chapters:

00:00     Introduction and Milestones

01:40     The Data Dilemma in AI

02:59     Understanding Data Readiness

05:50     Defining the Semantic Layer

08:46     The Importance of Context in AI

13:08     Navigating AI's Limitations

16:44     Building Guardrails for AI

21:12     Achieving ROI in AI Projects

26:45     Recommendations for Chief Data Officers

#EnterpriseAI #AIStrategy #DataReadiness #SemanticLayer #AIActually #ChiefDataOfficer #AIAgents

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 about the skills, structures, and organizational shifts that matter.

This is a candid conversation about how AI is collapsing traditional role boundaries, and why the ability to understand a business problem may now be more valuable than the ability to write code. The crew also tackles why large enterprises are structurally misaligned with how this work actually gets done, and what education, apprenticeship, and org change need to look like going forward.

Topics covered:

• What "Forward Deployed Engineer" really means, and why "Forward Deployed Consultant" might be more accurate
• Why senior engineers are thriving and junior roles are evolving, not disappearing
• How AI is inverting the old software architecture model: solve fast, clean up later
• Organizational bottlenecks: why most companies are still structured around the wrong constraints
• The SAP paradox and why business process knowledge is now worth its weight in gold
• What universities and apprenticeship models need to look like for the AI era
  

Speakers:

• Nicole Kosky, Senior Director of Services, AnswerRocket - https://www.linkedin.com/in/nicole-kosky-5b9a3b6/
• Stew Chisam, Operating Partner, StellarIQ - https://www.linkedin.com/in/stewart-chisam-7242543/ 
• Jim Johnson, Managing Partner, AnswerRocket - https://www.linkedin.com/in/jim-johnson-bb82451/
• Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/

Chapters: 

00:00     Introduction

01:43     Understanding the Role of Forward Deployed Engineers

04:16     The Evolution of Software Engineering Roles

07:22     The Business Analyst vs. Forward Deployed Engineer

10:47     Organizational Challenges in Adapting to New Roles

12:10     The Importance of Clarity in Problem Solving

17:43     Navigating Change Management in Organizations

20:44     The Role of AI in Redefining Business Processes

28:42     The Future of Software Engineering and Business Skills

32:25     The Need for Educational Reform in AI Skills

37:58     Conclusion: Embracing the Renaissance Person in Tech

#ForwardDeployedEngineer #EnterpriseAI #AIRoles #BusinessAnalyst #TechnicalConsultant #AIOrgChange #AIWorkforce #AgenticDevelopment #EnterpriseSoftware #AIAdoption

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 takes to build a culture where AI creates compounding value.

In this episode of AI, Actually, host Pete Reilly is joined by Mike Finley, Nicole Kosky, and new AnswerRocket team member Michelle Hamilton, Director of AI Adoption and Change Management, for a candid conversation on how to move past fear, shadow AI, unused licenses, and the "is this going to replace me?" question that's quietly stalling enterprise adoption everywhere.

You'll learn:

• Why a people-first approach to AI matters more than which model you pick
• How to use "meta prompting" to get dramatically better outputs across any model
• What a personal AI "corpus" is and why it becomes your most valuable competitive asset
• Why the most successful AI adopters are building tools, not just using tools
• How to think about the crawl/walk/run framework for individuals and organizations
• What forward deployed engineers are and why everyone can be one now

This episode is designed for: Business leaders, team managers, and anyone who knows they should be using AI more but isn't sure where to start.

AnswerRocket: https://answerrocket.com/

Speakers:

• Nicole Kosky, Senior Director of Services, AnswerRocket | https://www.linkedin.com/in/nicole-kosky-5b9a3b6/
• Mike Finley, CTO, AnswerRocket  - https://www.linkedin.com/in/mikefinley/ 
• Pete Reilly, COO, AnswerRocket - https://www.linkedin.com/in/petereilly 
• Michelle Hamilton, Director, AI Adoption and Change Management - https://www.linkedin.com/in/michellehamiltonai/ 

Chapters: 

00:00 Navigating the AI Landscape

01:25     Embracing a People-First Approach to AI

05:45     Tools and Techniques for AI Adoption

08:36     Meta Prompting and Leveraging AI Models

11:38     The Challenge of Change in AI Integration

14:33     Collaboration and Knowledge Sharing in AI

17:06     Empowering Non-Technical Users with AI

20:18     The Future of AI and Human Collaboration

27:58     Using AI for Office Tasks

33:18     The Role of AI in Education

36:42     Evolving Workflows with AI

45:35     Getting Started with AI

#AIAdoption #EnterpriseAI #AIActually #ChangeManagement #GenerativeAI #AIStrategy #FutureOfWork

Every week, someone declares that AI will make consultants obsolete. What we actually see is AI breathing new life into consulting, with practically every model maker teaming up with consulting firms for delivery support.

The real story isn't about whether consulting is dead. It's about whether the consulting model your company is paying for is built for this era or the last one.

In this episode of AI, Actually, Jim Johnson hosts Evan Gatch, Nicole Kosky, and Andy Sweet for a candid conversation on what enterprise AI consulting actually looks like right now: what's working, what's failing, and what clients should be demanding from their partners.

You'll learn:

• Why IT-led AI initiatives consistently underperform and what the Fortune 500 failures have in common
• How the consulting business model is shifting from hourly rates to outcome-based and gain-share agreements
• Why prototypes are easier to build than ever and why that makes the POC-to-production gap more dangerous, not less
• What "enterprise grade" actually means when it comes to agentic AI solutions
• How to structure a use case prioritization framework before you start building
• Why organizational change management is the constraint that technology alone can't solve

This episode is designed for: CDOs, VP-level analytics and data science leaders, AI transformation leads, and enterprise consulting buyers navigating AI strategy decisions.

Learn more about AnswerRocket's enterprise AI solutions: https://answerrocket.com/

Speakers

• Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ 
• Jim Johnson, President, AnswerRocket | https://www.linkedin.com/in/jim-johnson-bb82451/
• Nicole Kosky, Senior Director of Services, AnswerRocket | https://www.linkedin.com/in/nicole-kosky-5b9a3b6/
• Evan Gatch, VP Consulting Sales, AnswerRocket - https://www.linkedin.com/in/evan-gatch-1531482/ 

Chapters

00:00 Introduction and Meet the Experts

02:10 Consulting in the Rapidly Evolving AI Landscape

04:14 The Changing Nature of Consulting Services

07:18 Aligning AI Solutions with Business Goals

14:02 The Role of Software Engineering Skills in AI

17:17 Organizational Change and AI Adoption Challenges

21:42 Enterprise-Grade AI Solutions and Production Readiness

29:28 Structured Approaches to AI Opportunities

32:45 Outcome-Based Pricing and Trust in Consulting

38:29 Closing Remarks and Future Outlook

#AIConsulting #EnterpriseAI #AIStrategy #OutcomeBased #AgenticAI #AITransformation #AIActually

Every week, someone declares that vibe coding will kill software development. Every week, they're wrong — but not for the reasons most people think.

The real story isn't about job loss. It's about an explosion in software creation that most business leaders aren't prepared for.

In this episode of AI, Actually, the crew breaks down what vibe coding actually means for enterprise software, why the "death of engineering" narrative misses the point, and what executives need to understand and do, before their competitors get there first.

You'll learn:

• Why Jevons Paradox predicts we'll have more software than ever, not less
• The "compound engineering" principle that separates durable AI-built code from slop
• Why every executive needs to personally try vibe coding, not just read about it
• What Jack Dorsey's layoffs at Block, parent company of Square, actually signal for enterprise workforce strategy?
• Agency vs. intelligence: the new career currency in an AI-powered world
• The socioeconomic upside of AI democratization that almost nobody is talking about

This episode is designed for: CTOs, engineering leaders, Chief Data Officers, innovation executives, and enterprise decision-makers navigating AI transformation and workforce strategy.

Learn more about AnswerRocket's enterprise AI solutions: https://answerrocket.com/accelerators/

Speakers

• Pete Reilly, COO, AnswerRocket | https://www.linkedin.com/in/petereilly
• Mike Finley, CTO, AnswerRocket | https://www.linkedin.com/in/mikefinley/ 
• Shanti Greene, AnswerRocket | https://www.linkedin.com/in/shantigreene/ 
• Stew Chisam, Operating Partner, StellarIQ | https://www.linkedin.com/in/stewart-chisam-7242543/

Chapters
00:00     The Evolution of Software Development
05:20     The Future of Custom Software
10:53     Agent-Friendly Interfaces and Integration
16:58     The Importance of Curiosity in Software Development
26:07     Re-architecting for Modern Standards
31:04     The Impact of AI on Traditional Jobs
38:11     Navigating Job Losses and Transitioning in the Workforce

#VibeCoding #EnterpriseAI #FutureOfWork #SoftwareDevelopment #AIStrategy #WorkforceDisruption #GenerativeAI

Enterprise AI adoption is accelerating — but most organizations are still stuck debating tools like ChatGPT while a smaller group is deploying AI agents that operate like digital colleagues.

The gap between experimentation and operationalization is widening.

In this episode of AI, Actually, leaders from AnswerRocket break down what’s really happening on the front lines of enterprise AI adoption — and share a practical framework for moving from pilots to measurable business impact.

You’ll learn:

• Why the shift from AI “co-pilot” to AI “colleague” is reshaping enterprise workflows
• The leadership mindset separating fast movers from stalled organizations
• A crawl-walk-run framework for AI adoption at the individual, team, and enterprise level
• How to measure AI ROI (including the adoption J-curve most leaders underestimate)
• Why there’s no such thing as an “AI project” — only business problems enabled by AI

This episode is designed for:
Chief Data Officers, Heads of Analytics, AI leaders, innovation executives, and enterprise decision-makers navigating AI transformation.

Learn more about enterprise AI strategy and operationalization:

https://answerrocket.com/

• Stew Chisam, Operating Partner, StellarIQ - https://www.linkedin.com/in/stewart-chisam-7242543/ 

• Jim Johnson, Managing Partner, AnswerRocket | https://www.linkedin.com/in/jim-johnson-bb82451/
• Pete Reilly, COO, AnswerRocket - https://www.linkedin.com/in/petereilly 
• Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ 

#EnterpriseAI #AIAdoption #AIROI #AIAgents #AIStrategy #DigitalTransformation #GenerativeAI

Artificial intelligence has crossed a major threshold. AI is no longer confined to answering questions in a chat window. It's sending emails, scheduling meetings, moving data between systems, and operating with its own credentials and access. This shift from suggestion to action is forcing every enterprise leader to rethink their AI strategy.

In this episode, Pete Reilly sits down with Shanti Greene, Jim Johnson, and Stew Chisam to examine three developments reshaping how businesses approach AI. From the OpenClaw experiment that briefly turned the internet into a Skynet-like scenario, to Anthropic's Cowork tool bringing agent capabilities to non-technical workers, to the fundamental question of whether enterprises should build their own software instead of buying it—this conversation tackles the practical implications of AI that actually does things.

Topics covered:

✅ How OpenClaw (formerly ClawdBot/MoltBot) represents the future of AI agents with their own identity, proactive behavior, and inter-agent communication

✅ Why enterprise leaders need to start thinking about "onboarding non-human employees" with email addresses, Slack accounts, and human supervisors

✅ Claude Cowork's approach to bringing agent capabilities to business users through local file access and workflow automation

✅ The shifting build-vs-buy decision as AI makes custom software development dramatically faster and cheaper

✅ Whether traditional SaaS companies like Salesforce can survive in an AI-first world

Follow the Gang:

• Stew Chisam, Operating Partner, StellarIQ - https://www.linkedin.com/in/stewart-chisam-7242543/ 
• Jim Johnson, Managing Partner, AnswerRocket | https://www.linkedin.com/in/jim-johnson-bb82451/
• Pete Reilly, COO, AnswerRocket - https://www.linkedin.com/in/petereilly 
• Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/ 

Chapters:

00:00 Introduction: The Evolution of AI in Enterprises

01:20 OpenClaw: The Next Iteration of AI Assistant

04:18 Implications of AI Agents in the Workplace

10:01 Understanding the Difference: Traditional AI vs. OpenClaw

14:48 Navigating Security and Accountability in AI

21:29 The Future of Non-Human Employees in Enterprises

26:42 Exploring Claude Cowork: A Shift in Focus

39:29 The Build vs. Buy Debate in CRM Development

#AIAgents #AutonomousAI #OpenClaw #ClaudeCowork #EnterpriseAIStrategy #AIWorkflows #AgenticOperations #BuildVsBuy #SaaSDisruption #AIEmployeeOnboarding

What happens when AI coding agents enter the development process? AnswerRocket's team built a production-ready CRM in just four weeks, showing what's possible with next-generation software development.

In this episode, Pete Reilly, Alon Goren, Mike Finley, and Andy Sweet pull back the curtain on what modern AI development actually looks like in practice. Using a custom CRM project as their case study, they demonstrate how coding agents, contextual design, and new architectural patterns are fundamentally rewriting the build versus buy equation for enterprise software.

This isn't theory—it's a live demonstration of software that would have taken 10x longer to build just six months ago, with insights on what this means for development teams, IT strategy, and the future of business software.

Topics covered:

• How AI coding agents reduced development time by 10x for production-grade software
• Why context is now more valuable than data entry in modern CRM design
• The shift from "system of record" to "sales assistant" in CRM philosophy
• How playbooks and workflows enable AI to follow company-specific processes
• Why the build vs. buy decision is becoming "build with composable blocks"
• What "vibe coding" means and why offshore development strategies need rethinking
• How maintenance changes when AI agents can read source code directly

Follow the Gang

• Mike Finley, CTO, AnswerRocket  - https://www.linkedin.com/in/mikefinley/ 
• Pete Reilly, COO, AnswerRocket - https://www.linkedin.com/in/petereilly 
• Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ 
• Alon Goren, AnswerRocket, CEO - https://www.linkedin.com/in/alon-goren-87889681/ 
  

Chapters

00:00 Intro: Demo to AI in Software Development

02:10 Understanding Customer Interactions and CRM Needs

04:39 Reimagining CRMs in the Age of AI

06:00 Demo Walkthrough of the CRM

20:02 What's Possible Now with AI-Assisted Development

21:25 Designing an AI-Compatible Stack

27:32 Flipping the Build vs. Buy Dilemma

32:59 AI's Impact on Offshore Development

35:57 The Future of Business and Software Customization

39:23 Maintaining AI-Assisted Software Solutions

#AIDevelopment #CodingAgents #CRMCustomization #VibeCoding #BuildVsBuy #EnterpriseSoftware #AIAgents #SalesAutomation #SoftwareDevelopmentLifecycle #ClaudeCode #AgenticDevelopment #ContextDrivenDesign