AI is changing how we work. For some, that means fear. For others, it means reinvention.

In this episode, Kyle James sits down with Riley Gerszewski, a longtime product design leader who used AI tools to go from designing products to actually building and shipping a full iOS app himself.

Not a prototype. Not a concept. A real healthcare app approved by Apple.

Riley shares what it felt like to be part of a reduction in force, how AI accelerated his learning curve, and how he transitioned from specialist to generalist in real time. We talk about identity shifts, go-to-market uncertainty, ethical guardrails, and what it means to build responsibly in the healthcare space.

The app he built, HerDiabetes, is designed specifically for women living with diabetes, a group of over 13 million in the United States alone, and addresses an underserved intersection of glucose data and hormonal cycle tracking.

This conversation is not about hype. It’s about figuring it out as you go.

If you’re a product leader, GTM professional, designer, or anyone trying to understand what AI means for your career, this episode is for you.

🔗 HerDiabetes Website: https://www.herdiabetes.com/

🔗 Connect with Riley on LinkedIn: https://www.linkedin.com/in/rileygerszewski/

If this episode resonated with you, consider subscribing, leaving a review, or sharing it with someone navigating their own AI reinvention.

We’re all working through this shift together.

Account based marketing was never broken. Execution was.

In this episode, Nick Bennett joins PROMPTED to unpack why focused ABM is finally working in 2026 and why AI is the real unlock. After years as an in house B2B marketer and now advising teams directly, Nick has seen firsthand what changed and what stayed the same.

The LinkedIn post that drove this discussion - https://www.linkedin.com/posts/nickbennett1_after-working-with-35-b2b-brands-in-3-years-activity-7408892892209008641-mhbl/

We dig into why most teams failed at ABM, how AI helps validate ICPs instead of guessing, how buying groups and signals are identified earlier, and how personalization finally scales without turning into noise. Nick also shares real examples of AI powered workflows booking meetings today, where humans must stay in the loop, and where automation creates false confidence.

If you have tried ABM before and walked away skeptical, or you are curious how AI actually fits into modern go to market execution, this episode is for you.

👇 Topics covered

1. Why ABM failed before
2. What “focused ABM” really means
3. How AI validates fit and disqualifies faster
4. AI powered personalization at scale
5. What should never be automated
6. Where ABM and AI go next in 2026

Connect with Nick Bennett - https://www.linkedin.com/in/nickbennett1/

Subscribe for more conversations on AI, GTM strategy, and real world execution.

Moltbook. MoltBot. OpenClaw.

A “Reddit for AI agents.” Bots talking to bots. A massive security breach. Headlines hinting at AGI and the singularity.

If you have been seeing this everywhere and wondering what actually happened and whether you need to care, this episode is for you.

In this conversation, Kyle James sits down with returning guest John Marcus III, someone he trusts to cut through hype and explain what is real, what is mostly nonsense, and what actually matters for go-to-market professionals.

We break down:

1. What Moltbook and OpenClaw really are, in plain language
2. Why this moment felt new even though the underlying tech is not
3. The real security and governance risks behind the headlines
4. Why AI orchestration matters more than chasing tools
5. What GTM professionals should do now, later, or safely ignore

This is not a demo and not hype. It is a guided walkthrough designed to help you shut the curiosity door, get back to work, and be better prepared for what is coming next.

Links & Resources

1. OpenClaw (GitHub): https://github.com/openclaw
2. Fractional Ventures: https://fractional.ventures
3. Connect with John Marcus III on LinkedIn: https://www.linkedin.com/in/jwmarcus/

AI agents are everywhere right now. But most go-to-market teams are experimenting without a clear sense of control, governance, or coordination.

In this episode of Builder Stories, Kyle James sits down with Jomar Ebalida to unpack why go-to-market does not have an AI problem. It has an orchestration problem.

Jomar introduces a powerful mental model built around the Bowtie Funnel, a looping view of the customer journey that connects marketing, sales, customer success, and expansion into one system. On top of that system, he explains the need for a control tower, a centralized way to see, manage, and guide AI agents across every stage of go-to-market, with humans always in the loop.

We explore:

1. Why buying AI tools first and figuring it out later is a backward approach
2. How the Bowtie Funnel becomes the map for orchestrating agents across the full customer journey
3. The control tower mental model and why pilots only fly the plane 11 percent of the time
4. The difference between basic workflow automation and reasoning-based agents
5. What “human-in-the-loop” really means and how reliability compounds over time
6. Why the GTM Orchestrator role is emerging as the next evolution beyond RevOps

This conversation is for anyone experimenting with AI in marketing, sales, or customer success who feels like things are moving fast, but not always in the right direction. If you want a clearer way to think about AI, governance, and scale without losing trust or quality, this episode gives you a new map.

Learn More and Connect with Jomar

1. Connect with Jomar on LinkedIn: https://www.linkedin.com/in/jomarebalida/
2. Learn more about Bowtie Funnel: https://bowtiefunnel.com/

What happens when the skills you spent decades building suddenly feel obsolete?

In this episode of Builder Stories, Tom Elliott shares the moment AI forced him to confront a terrifying truth. At 50 years old, after spending over a decade building a successful software consulting business, he watched an AI demo that made him physically ill. The machine could do most of what he had built his career on, faster and better.

What followed was not retreat, but reinvention.

Tom walks through the fear, the identity shock, and the decision to either master AI or walk away from knowledge work entirely. He explains how a single month of intense curiosity and hands-on learning flipped his mindset from panic to possibility, and how he went from marketing leader to building agents, voice AI, and production workflows without a traditional engineering background.

This is not a story about hype or shortcuts. It is a story about relevance, agency, and what it really takes to reinvent yourself in the age of AI.

If you have ever wondered whether you are falling behind, or whether it is too late to adapt, this conversation will feel uncomfortably familiar and deeply hopeful.

Learn more and connect with Tom Elliott:

1. Connect with Tom on LinkedIn: https://www.linkedin.com/in/tomelliottnh/
2. Learn more about Nutum: https://nutum.ai/

In this episode of PROMPTED, Kyle James sits down with Mike Lemire, a longtime customer success leader and advisor, to unpack what is really happening with AI inside CS teams.

AI was supposed to make customer success more proactive, more strategic, and more human. Instead, many teams are chasing “AI strategies” without clarity on outcomes, customer experience, or value.

Mike shares what he is seeing across CS organizations, including:

1. Why AI strategy has become theater instead of problem-solving
2. How investor pressure quietly shapes AI adoption in CS
3. Support teams as the earliest AI testbed and the risks of optimizing for deflection
4. The danger of over-indexing on sentiment and the “customer watermelon” problem
5. A hackathon story where vibe coding replaced a six-figure SaaS purchase
6. Why better product experiences could ultimately reduce the need for CS itself

This is a grounded, honest conversation for customer success, CX, and GTM leaders who want to use AI thoughtfully rather than chase the latest tool.

🎧 Listen for practical lessons, cautionary insights, and a clearer way forward for AI in customer success.

Learn more and Connect with Mike:

1. Connect with Mike on LinkedIn: https://www.linkedin.com/in/michaellemire/
2. Learn more about Harmonic Leadership: https://harmonicleadership.com/

Most people use AI like a faster Google or a writing assistant.

That is not where the real leverage is.

In this episode of Prompted, Kyle sits down again with Matthew Stein to break down seven practical ways to use AI as a true thought partner, not just a tool. From idea generation and structural support to persona simulation and strategic thinking, this conversation shows how modern professionals are using AI to think better, move faster, and avoid blind spots.

If you already use AI but feel like you are only scratching the surface, this episode is for you.

👉 Demo agent shown in the episode: https://agent.ai/agent/screen-test

What does it really mean to build AI agents in the real world, not just as demos, but as tools that save time, surface insight, and change how people work?

In this episode of PROMPTED: Builder Stories, Kyle sits down with Jason Burke, founder of AllStage and an experienced product builder and investor, to unpack how he thinks about AI agents and how he actually builds them. Jason shares how his background in engineering, product management, and early-stage investing shaped his approach to designing agent driven workflows that support founders, investors, and everyday life.

This conversation goes beyond theory. Jason walks through live examples of the agents he has built, including an AllStage business workflow agent that helps analyze investment opportunities, as well as personal productivity agents he created to solve real problems in his own life. Along the way, he breaks down what makes a workflow “agent ready,” where agents add the most value today, and why trust, risk, and human judgment still matter.

You will hear practical guidance on how to start building agents, why experimenting with personal use cases is often the best entry point, and how AI is lowering the barrier for anyone to become a builder. If you are curious about using AI agents to work smarter, think more clearly, or build something meaningful, this episode offers a grounded and inspiring look at what is possible right now.

Learn more and connect with Jason:

1. Jason on LinkedIn: https://www.linkedin.com/in/jmburke/
2. All Stage on LinkedIn: https://www.linkedin.com/company/all-stage-invest
3. All Stage Website: https://allstage.co
4. All Stage in All Stage: https://allstage.co/us
5. Deal analysis agent: https://agent.ai/agent/allstage
6. Company updates summarizer Agent: https://agent.ai/agent/allstage-company-updates-summary
7. Better prices/shopping assistant agent: https://agent.ai/agent/better-prices

Subscribe for more Builder Stories and visit agent.ai to start building your own agents.

What if the future of AI is not about learning more tools, building more workflows, or becoming more technical at all?

In this episode of PROMPTED we sits down with Jared Robin, Co-Founder of RevGenius, a global community of more than 60,000 go-to-market professionals, to explore where AI adoption is actually headed and why 2026 needs to be the year AI becomes human native.

Jared brings a rare vantage point, shaped by daily conversations with sales, marketing, RevOps, and customer success leaders who are navigating AI mandates, tool overload, and rising complexity. Together, they unpack why forcing GTM teams to become AI builders is the wrong long-term bet, why so many AI pilots fail, and how the next wave of AI tools must remove friction instead of adding it.

This conversation goes beyond tactics to focus on first principles. You will hear why creativity is becoming a competitive advantage, how human-native AI changes workflows for revenue leaders, and what strategic thinkers should focus on now as AI becomes easier to build but harder to stay ahead with.

This episode is especially relevant for GTM professionals who want clarity without hype, practical insight without heavy technical depth, and a clearer mental model for evaluating AI and agentic tools in the years ahead.

Topics covered include:

1. Why 2025 forced humans to become AI native and why that model breaks
2. What human-native AI actually means in day-to-day GTM work
3. The hidden cost and complexity of current AI tooling
4. Why data foundations still matter more than new tools
5. How creativity, category design, and strategy shape the future of AI adoption

Learn more and connect with Jared Robin:

1. Jared’s LinkedIn Profile: https://www.linkedin.com/in/jaredrobin/
2. His personal website: https://jaredrobin.com/
3. The RevGenius Website: https://www.revgenius.com/
4. The Post that kicked off this conversation: https://www.linkedin.com/posts/jaredrobin_2025-humans-need-to-be-ai-native-2026-activity-7402395343184699392-0KQR/

Subscribe for more conversations with builders, operators, and thinkers shaping the future of AI and go-to-market work.

Learn more about Agent.ai and explore practical AI agents at agent.ai.

What does AI actually look like in 2026?

In this special end-of-year Predictions episode of Prompted, Kyle James sits down with Matthew Stein to debate ten concrete predictions for where AI, agents, and go-to-market teams are headed next year.

This is not a hype episode. There are no demos and no buzzwords. Instead, Kyle and Matthew pressure test real second-order effects like:

1. Why AI onboarding will become standard practice
2. How model quality degradation and buyer fatigue collide
3. Why AI shows up directly in GTM job titles
4. What happens when personal context becomes portable
5. Why AI portfolios matter more than resumeas
6. How marketing video creation fundamentally changes
7. Why PageRank-style authority signals may return
8. The rise of zero-party data
9. Whether Anthropic beats OpenAI to an ads platform
10. Why most companies still struggle to show AI ROI

They also close with one wild bonus prediction that could reshape the entire AI landscape.

This episode is designed to spark debate.

Watch the full episode, then head to the comments and tell us:

1. What did we get right?
2. What did we miss?
3. Which prediction do you disagree with most?