<![CDATA[AfterThePrompt]]>AfterThePrompt is a show about what happens when AI moves faster than people, companies, and culture can keep up.

Hosts Jay and Greg share field notes from the real world: why adoption lags, what finally makes it click, and how these tools change the way we work, decide, and communicate. Most episodes stay grounded in everyday use and organizational reality, with occasional special conversations that zoom out to the wider ripple effects.

Practical where it matters. Curious where it’s headed.

]]>www.afterthepromptcast.comRiverside.fm (https://riverside.com)Thu, 28 May 2026 00:06:07 GMTFri, 16 Jan 2026 21:12:16 GMT60Jay & Greg<p><b>AfterThePrompt</b> is a show about what happens when AI moves faster than people, companies, and culture can keep up.</p><p>Hosts Jay and Greg share field notes from the real world: why adoption lags, what finally makes it click, and how these tools change the way we work, decide, and communicate. Most episodes stay grounded in everyday use and organizational reality, with occasional special conversations that zoom out to the wider ripple effects.</p><p>Practical where it matters. Curious where it’s headed.</p>episodicJay & Gregjaymkania@gmail.comno<![CDATA[Stop Prompting, Start Managing: The Rise of AI-Run Teams (Ep 5)]]>The conversation delves into the lessons learned from using vibe coding and the challenges faced in managing handoffs and processes in AI-centric development. It explores the need for a shift in mentality and management mode when transitioning from vibe coding to market-ready production. Additionally, it emphasizes the importance of managing handoffs and the impact of AI on traditional software development processes. The conversation delves into the impact of fast prototyping, challenges with agile implementation, misalignment between business and development, the importance of prototyping sessions, transitioning to managing AI teams, human barriers and mental shift, challenges for developers turned managers, transitioning roles in the business, shift in business and technical roles, increasing proper stakeholders, iterative process and checks & balances, evolving work processes, building and iterating specialists, and the future of specialized teams.

Takeaways

  • Lessons from using vibe coding
  • Managing handoffs and processes in AI-centric development Fast prototyping enables individual contributors to build what a whole team would have previously built.
  • The shift to fast prototyping requires a mental shift and upskilling of individual contributors.

Chapters

  • 00:00 Managing Handoffs and Processes in AI-Centric Development
  • 35:00 The Impact of Fast Prototyping
  • 40:14 Agile Methods Across the Enterprise
  • 46:25 Human Barriers and Mental Shift
  • 52:34 Increasing Proper Stakeholders
  • 58:33 Building and Iterating Specialists
]]>434cac43-1ff1-4777-aec3-eb8939f09290Thu, 05 Mar 2026 11:00:00 GMT<p>The conversation delves into the lessons learned from using vibe coding and the challenges faced in managing handoffs and processes in AI-centric development. It explores the need for a shift in mentality and management mode when transitioning from vibe coding to market-ready production. Additionally, it emphasizes the importance of managing handoffs and the impact of AI on traditional software development processes. The conversation delves into the impact of fast prototyping, challenges with agile implementation, misalignment between business and development, the importance of prototyping sessions, transitioning to managing AI teams, human barriers and mental shift, challenges for developers turned managers, transitioning roles in the business, shift in business and technical roles, increasing proper stakeholders, iterative process and checks &amp; balances, evolving work processes, building and iterating specialists, and the future of specialized teams.</p><p></p><p>Takeaways</p><ul><li>Lessons from using vibe coding</li><li>Managing handoffs and processes in AI-centric development Fast prototyping enables individual contributors to build what a whole team would have previously built.</li><li>The shift to fast prototyping requires a mental shift and upskilling of individual contributors.</li></ul><p></p><p>Chapters</p><ul><li>00:00 Managing Handoffs and Processes in AI-Centric Development</li><li>35:00 The Impact of Fast Prototyping</li><li>40:14 Agile Methods Across the Enterprise</li><li>46:25 Human Barriers and Mental Shift</li><li>52:34 Increasing Proper Stakeholders</li><li>58:33 Building and Iterating Specialists</li></ul>no00:52:5815Stop Prompting, Start Managing: The Rise of AI-Run Teams (Ep 5)full<![CDATA[From Idea to App: Building with AI (What’s Real vs Risky) (Ep 4)]]>The conversation delves into the impact of AI on software development, exploring its evolution, role as a force multiplier, impact on the development workflow, improvements in AI-assisted tools, defining constraints and guardrails, considerations for AI in software projects, and a personal experience with AI-assisted software development. The conversation delves into the impact of AI on development, highlighting the evolution of the development experience, the response of developers to AI integration, and the benefits and cautions associated with leveraging AI for prototyping and stakeholder understanding. It also addresses challenges in infrastructure and provides a future outlook on AI's role in software development.

Takeaways

  • AI-assisted software development
  • Impact of AI on software development AI continues to lower the entry barrier, but the responsibility is scaling with the impact
  • AI can be leveraged for prototyping and mocking up applications, but caution is needed when dealing with sensitive data

Chapters

  • 00:00 Introduction to AI-Assisted Software Development
  • 07:16 AI as a Force Multiplier in Software Development
  • 13:08 Improvements in AI-Assisted Software Development Tools
  • 21:15 Considerations for AI in Software Development Projects
  • 30:00 Navigating High-Stakes Development
  • 35:03 Developer Response to AI Integration
  • 41:54 AI's Role in Prototyping and Stakeholder Understanding
  • 47:03 AI's Benefits and Cautions
]]>94784a53-043a-41c5-8146-d8fb5217d835Thu, 05 Feb 2026 11:30:00 GMT<p>The conversation delves into the impact of AI on software development, exploring its evolution, role as a force multiplier, impact on the development workflow, improvements in AI-assisted tools, defining constraints and guardrails, considerations for AI in software projects, and a personal experience with AI-assisted software development. The conversation delves into the impact of AI on development, highlighting the evolution of the development experience, the response of developers to AI integration, and the benefits and cautions associated with leveraging AI for prototyping and stakeholder understanding. It also addresses challenges in infrastructure and provides a future outlook on AI's role in software development.</p><p></p><p>Takeaways</p><ul><li>AI-assisted software development</li><li>Impact of AI on software development AI continues to lower the entry barrier, but the responsibility is scaling with the impact</li><li>AI can be leveraged for prototyping and mocking up applications, but caution is needed when dealing with sensitive data</li></ul><p></p><p>Chapters</p><ul><li>00:00 Introduction to AI-Assisted Software Development</li><li>07:16 AI as a Force Multiplier in Software Development</li><li>13:08 Improvements in AI-Assisted Software Development Tools</li><li>21:15 Considerations for AI in Software Development Projects</li><li>30:00 Navigating High-Stakes Development</li><li>35:03 Developer Response to AI Integration</li><li>41:54 AI's Role in Prototyping and Stakeholder Understanding</li><li>47:03 AI's Benefits and Cautions</li></ul>no00:44:0514From Idea to App: Building with AI (What’s Real vs Risky) (Ep 4)full<![CDATA[AI Is a Mirror: Clarity, Taste, Ego (Ep 3)]]>The conversation delves into the concept of AI as a mirror, reflecting the user's input and output, leading to feelings of competence and ego. It emphasizes an iterative approach and a shift to a leadership mindset when working with AI. The chapters cover the introduction to AI as a mirror, the clarity mirror, the taste mirror, the ego mirror, and the trust ladder and rules for working with AI.

Takeaways

  • AI as a Mirror
  • Iterative Approach
  • Shift to Leadership Mindset

Chapters

  • 00:00 Introduction to AI as a Mirror
  • 09:35 Clarity as the First Mirror
  • 18:08 Taste as a Mirror
  • 26:33 Ego as the Final Mirror
  • 38:42 Trust Ladder and Rules
]]>366875ae-48a2-48db-b0fa-b1fbfa76e93dThu, 29 Jan 2026 13:30:31 GMT<p>The conversation delves into the concept of AI as a mirror, reflecting the user's input and output, leading to feelings of competence and ego. It emphasizes an iterative approach and a shift to a leadership mindset when working with AI. The chapters cover the introduction to AI as a mirror, the clarity mirror, the taste mirror, the ego mirror, and the trust ladder and rules for working with AI.</p><p></p><p>Takeaways</p><ul><li>AI as a Mirror</li><li>Iterative Approach</li><li>Shift to Leadership Mindset</li></ul><p></p><p>Chapters</p><ul><li>00:00 Introduction to AI as a Mirror</li><li>09:35 Clarity as the First Mirror</li><li>18:08 Taste as a Mirror</li><li>26:33 Ego as the Final Mirror</li><li>38:42 Trust Ladder and Rules</li></ul>no00:43:3913AI Is a Mirror: Clarity, Taste, Ego (Ep 3)full<![CDATA[Why AI Adoption Stalls: Fear, Friction & Overload (Ep 2)]]>The podcast introduces a name change and discusses the challenges of AI adoption, focusing on fear, friction, and overload as barriers. It explores the types of fear, privacy concerns, and low-drama ways to overcome fear. Additionally, it delves into the concept of friction in AI adoption. The conversation delves into the complexities of human interaction with AI, exploring the nuances of human interaction with other humans, computers, and AI. It also addresses the friction involved in AI adoption, highlighting the challenges and expectations associated with interacting with AI. Additionally, the overload of AI tools and the process of tool selection are discussed, shedding light on the overwhelming options and the need for careful consideration.

Takeaways

  • AI adoption challenges
  • Fear, Friction, and Overload as barriers to AI adoption Human Interaction with AI
  • Friction in AI Adoption

Chapters

  • 00:00 Introducing After the Prompt
  • 07:33 Fear of AI Adoption
  • 14:24 Types of Fear
  • 22:07 Overcoming Fear
  • 28:33 Friction in AI Adoption
  • 34:44 Overload and Tool Selection
]]>85e54b66-3df1-40c9-a1a0-a09082173f16Thu, 22 Jan 2026 11:00:00 GMT<p>The podcast introduces a name change and discusses the challenges of AI adoption, focusing on fear, friction, and overload as barriers. It explores the types of fear, privacy concerns, and low-drama ways to overcome fear. Additionally, it delves into the concept of friction in AI adoption. The conversation delves into the complexities of human interaction with AI, exploring the nuances of human interaction with other humans, computers, and AI. It also addresses the friction involved in AI adoption, highlighting the challenges and expectations associated with interacting with AI. Additionally, the overload of AI tools and the process of tool selection are discussed, shedding light on the overwhelming options and the need for careful consideration.</p><p></p><p>Takeaways</p><ul><li>AI adoption challenges</li><li>Fear, Friction, and Overload as barriers to AI adoption Human Interaction with AI</li><li>Friction in AI Adoption</li></ul><p></p><p>Chapters</p><ul><li>00:00 Introducing After the Prompt</li><li>07:33 Fear of AI Adoption</li><li>14:24 Types of Fear</li><li>22:07 Overcoming Fear</li><li>28:33 Friction in AI Adoption</li><li>34:44 Overload and Tool Selection</li></ul>no00:50:1912Why AI Adoption Stalls: Fear, Friction & Overload (Ep 2)full<![CDATA[AI Innovation Is Exploding Why Is Adoption So Slow? (Ep 1)]]>The conversation delves into the rapid pace of AI innovation, the slow adoption of AI technology, and the impact of AI on professional roles. It begins with an introduction to Prompt and Circumstance, followed by discussions on the impact of AI innovation, observations on AI adoption, the chasm between early and late majority, and the paradox of slow adoption.

Takeaways

  • AI innovation is moving at a rapid pace
  • Slow adoption of AI technology
  • The impact of AI on professional roles

Chapters

  • 00:00 Introduction to Prompt and Circumstance
  • 08:06 Observations on AI Adoption
  • 17:33 The Chasm Between Early and Late Majority
  • 33:16 The Paradox of Slow Adoption
]]>1e7a21ee-b8c2-47f3-80bb-d2871a59dc99Wed, 21 Jan 2026 00:25:48 GMT<p>The conversation delves into the rapid pace of AI innovation, the slow adoption of AI technology, and the impact of AI on professional roles. It begins with an introduction to Prompt and Circumstance, followed by discussions on the impact of AI innovation, observations on AI adoption, the chasm between early and late majority, and the paradox of slow adoption.</p><p></p><p>Takeaways</p><ul><li>AI innovation is moving at a rapid pace</li><li>Slow adoption of AI technology</li><li>The impact of AI on professional roles</li></ul><p></p><p>Chapters</p><ul><li>00:00 Introduction to Prompt and Circumstance</li><li>08:06 Observations on AI Adoption</li><li>17:33 The Chasm Between Early and Late Majority</li><li>33:16 The Paradox of Slow Adoption</li></ul>no00:44:25AI Innovation Is Exploding Why Is Adoption So Slow? (Ep 1)full