In this episode, we break down how to build a working AI agent in about 30 minutes using modern AI coding tools like Cursor, Codex, or Claude Code.

Matthew Stein walks through a real, end-to-end example of building an agent from scratch. No fluff. No theory. Just a practical workflow you can follow and adapt to your own ideas.

👉 Agent AI Build Kit (GitHub): https://github.com/Chefmattrock/agent-ai-build-with-cursor

👉 Agent.ai Community (get help, share what you build): https://community.agent.ai/

You will see how to go from a rough idea to a functional agent using a simple but powerful process:

• Define the problem and user
• Generate a PRD (Product Requirements Doc)
• Use AI coding tools to build the agent logic
• Debug and refine outputs
• Ship a working version fast

This is not just about Cursor. The same approach works across today’s AI coding tools and models. If you have ever wanted to build your own agents but did not know where to start, this episode gives you a repeatable system.

This is best suited for intermediate users, but beginners can follow along by pairing this with your favorite LLM to guide setup and implementation.

If you are in GTM, product, marketing, or operations, this is one of the fastest ways to start turning AI into real workflows.

• How to build an AI agent from scratch in ~30 minutes
• Why everything starts with a simple PRD
• How to use AI coding tools to generate agent workflows
• How to debug and iterate when things break
• How to turn ideas into usable agents quickly
• A repeatable framework you can apply to your own use cases

Building AI agents is no longer slow or complex.

If you can clearly define the problem, AI can help you build the solution faster than ever.

Start simple. Ship fast. Improve from there.

In this episode of PROMPTED, Kyle James sits down with go-to-market strategist Kat Hill Contag to talk about the experience that completely changed how she thinks about AI and building products.

Kat is a GTM consultant who works with SaaS companies on product launches and market expansion. Like many operators, she was curious about AI but did not come from a technical background.

Then she decided to try something new.

Kat entered a women’s AI hackathon using the platform Lovable, gave herself two days to figure it out, and built a tool called AI Recess, a Duolingo-style platform designed to help teams learn practical AI workflows at work.

What happened next surprised even her.

In this conversation, Kyle and Kat explore:

1. What it is really like to participate in an AI hackathon
2. How non-technical professionals can start building with AI
3. Why operators may become the next generation of product builders
4. The mindset shift required to experiment with AI tools
5. Why more women need to be part of the AI conversation

If you have ever wondered whether you could actually build something with AI, this episode might change how you think about it.

Connect with Kat

1. LinkedIn - https://www.linkedin.com/in/khillcontag/
2. TikTok - https://www.tiktok.com/@kathillcontag
3. Personal Website - https://kathillcontag.com/
4. Try AI Recess - https://ai-recess.com/

Most companies think their go-to-market is solid. It’s not.

In this episode, Dale Zwizinski of Revenue Reimagined breaks down why AI will not fix a broken GTM foundation. It will expose it or amplify it.

We dive deep into why startups and growth-stage companies skip stabilization, rush toward scale, and avoid pressure-testing their ICP, value proposition, and sales motion. Dale explains the four stages of the Go-to-Market Gap framework, why repeatability cannot happen without foundations, and how AI should be used to eliminate blank-page work, not replace strategic thinking.

You’ll learn:

1. Why founders overestimate their GTM maturity
2. The difference between stabilization, foundation, repeatability, and scale
3. How AI can accelerate GTM work without creating chaos
4. Why most companies never revisit their ICP or value prop
5. How to build a human + agent collaboration model for 2026

If you care about building repeatable revenue in a rapidly shifting market, this conversation is essential.

🔗 Connect with Dale on LinkedIn: https://www.linkedin.com/in/dalezwizinski/

🔗 Visit Revenue Reimagined: https://www.revenue-reimagined.com/

🔗 Run the GTM Gap Report for your company: https://www.revenue-reimagined.com/gtm-gap

🎙 Subscribe for more conversations on AI, go-to-market strategy, and building modern revenue engines.

What if AI wasn’t just a productivity tool… but a judgment-free strategy room?

In this episode, I sit down with longtime friend and B2B SaaS executive Jeanne Hopkins to explore how she actually uses AI. Not for prompts. Not for hacks. But as a thinking partner.

Jeanne has spent decades leading marketing, sales, and revenue teams as a multi-time VP of Marketing and Chief Revenue Officer. In our conversation, she shares how she uses AI to pressure test decisions, challenge assumptions, and run weekly retros on her own performance.

We also go deeper.

Jeanne opens up about navigating grief, complex family dynamics, and how AI helped her de-emotionalize and think clearly through some of the hardest decisions of her personal life.

This is not a tools episode. It’s a mindset episode.

If you want to understand what executive-level AI fluency actually looks like, this conversation is for you.

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/