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    <title>Runpoint: AI Business Transformation Podcast</title>
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    <description>Hosted by Runpoint Partners’ founders Sam Gaddis (tech entrepreneur &amp; AI builder) and Matthew Hall (PE operator &amp; growth strategist), Runpoint Podcast strips the hype from artificial intelligence and shows you how to turn it into concrete business results—fast.
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    <copyright>2025 Runpoint Partners</copyright>
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    <pubDate>Wed, 20 May 2026 12:02:49 -0500</pubDate>
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      <title>Runpoint: AI Business Transformation Podcast</title>
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    <itunes:summary>Hosted by Runpoint Partners’ founders Sam Gaddis (tech entrepreneur &amp; AI builder) and Matthew Hall (PE operator &amp; growth strategist), Runpoint Podcast strips the hype from artificial intelligence and shows you how to turn it into concrete business results—fast.
</itunes:summary>
    <itunes:subtitle>Hosted by Runpoint Partners’ founders Sam Gaddis (tech entrepreneur &amp; AI builder) and Matthew Hall (PE operator &amp; growth strategist), Runpoint Podcast strips the hype from artificial intelligence and shows you how to turn it into concrete business results—fast.</itunes:subtitle>
    <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
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      <itunes:name>Runpoint Partners</itunes:name>
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    <itunes:complete>No</itunes:complete>
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      <title>Runpoint 12: Agents Are Moving Into the Enterprise: Google, SAP, Salesforce, and the Future of Work</title>
      <itunes:episode>13</itunes:episode>
      <podcast:episode>13</podcast:episode>
      <itunes:title>Runpoint 12: Agents Are Moving Into the Enterprise: Google, SAP, Salesforce, and the Future of Work</itunes:title>
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        <![CDATA[<p>AI agents are no longer just standalone demos. They are moving directly into the systems where work already happens: Google Workspace, SAP, Salesforce, email, calendars, files, CRMs, and enterprise systems of record.</p><p>In this episode of the Runpoint Podcast, Sam Gaddis, Matthew, Ryan Mish, and guest Harrison Wells of Dodo Digital discuss the shift from flashy AI tools to operational AI workflows. They cover Google Spark and Omni, the SAP + Anthropic partnership, Salesforce’s reported engineering productivity gains, Pi agents, Codex 5.5, Claude, and why many companies are increasing AI budgets faster than they are building true AI readiness.</p><p>The big question: will enterprises actually transform around AI, or will they just bolt chatbots onto old systems and call it innovation?</p><p>Timestamps<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I">00:00</a> — Intro: agents are moving into real work surfaces<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=138s">02:18</a> — Pi agents, Codex 5.5, and custom AI workflows<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=360s">06:00</a> — Google Spark, Omni, and the Workspace distribution advantage<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=746s">12:26</a> — Could Google own the enterprise AI surface?<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=919s">15:19</a> — Agents making purchases and real-world decisions<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1263s">21:03</a> — SAP + Anthropic: Claude inside systems of record<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1405s">23:25</a> — Why chatbot-style enterprise AI often fails<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1530s">25:30</a> — Daily AI reports, heartbeat workflows, and what actually works<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1904s">31:44</a> — Salesforce’s AI engineering productivity claims<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=2241s">37:21</a> — AI budgets are rising, but readiness is lagging<br>39:48 — How companies should build real AI adoption<br>42:31 — Why engineering is ahead of the rest of the enterprise<br>43:21 — Closing</p><p><br></p>]]>
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        <![CDATA[<p>AI agents are no longer just standalone demos. They are moving directly into the systems where work already happens: Google Workspace, SAP, Salesforce, email, calendars, files, CRMs, and enterprise systems of record.</p><p>In this episode of the Runpoint Podcast, Sam Gaddis, Matthew, Ryan Mish, and guest Harrison Wells of Dodo Digital discuss the shift from flashy AI tools to operational AI workflows. They cover Google Spark and Omni, the SAP + Anthropic partnership, Salesforce’s reported engineering productivity gains, Pi agents, Codex 5.5, Claude, and why many companies are increasing AI budgets faster than they are building true AI readiness.</p><p>The big question: will enterprises actually transform around AI, or will they just bolt chatbots onto old systems and call it innovation?</p><p>Timestamps<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I">00:00</a> — Intro: agents are moving into real work surfaces<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=138s">02:18</a> — Pi agents, Codex 5.5, and custom AI workflows<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=360s">06:00</a> — Google Spark, Omni, and the Workspace distribution advantage<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=746s">12:26</a> — Could Google own the enterprise AI surface?<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=919s">15:19</a> — Agents making purchases and real-world decisions<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1263s">21:03</a> — SAP + Anthropic: Claude inside systems of record<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1405s">23:25</a> — Why chatbot-style enterprise AI often fails<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1530s">25:30</a> — Daily AI reports, heartbeat workflows, and what actually works<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1904s">31:44</a> — Salesforce’s AI engineering productivity claims<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=2241s">37:21</a> — AI budgets are rising, but readiness is lagging<br>39:48 — How companies should build real AI adoption<br>42:31 — Why engineering is ahead of the rest of the enterprise<br>43:21 — Closing</p><p><br></p>]]>
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      <pubDate>Wed, 20 May 2026 12:01:42 -0500</pubDate>
      <author>Runpoint Partners</author>
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      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2320</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>AI agents are no longer just standalone demos. They are moving directly into the systems where work already happens: Google Workspace, SAP, Salesforce, email, calendars, files, CRMs, and enterprise systems of record.</p><p>In this episode of the Runpoint Podcast, Sam Gaddis, Matthew, Ryan Mish, and guest Harrison Wells of Dodo Digital discuss the shift from flashy AI tools to operational AI workflows. They cover Google Spark and Omni, the SAP + Anthropic partnership, Salesforce’s reported engineering productivity gains, Pi agents, Codex 5.5, Claude, and why many companies are increasing AI budgets faster than they are building true AI readiness.</p><p>The big question: will enterprises actually transform around AI, or will they just bolt chatbots onto old systems and call it innovation?</p><p>Timestamps<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I">00:00</a> — Intro: agents are moving into real work surfaces<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=138s">02:18</a> — Pi agents, Codex 5.5, and custom AI workflows<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=360s">06:00</a> — Google Spark, Omni, and the Workspace distribution advantage<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=746s">12:26</a> — Could Google own the enterprise AI surface?<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=919s">15:19</a> — Agents making purchases and real-world decisions<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1263s">21:03</a> — SAP + Anthropic: Claude inside systems of record<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1405s">23:25</a> — Why chatbot-style enterprise AI often fails<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1530s">25:30</a> — Daily AI reports, heartbeat workflows, and what actually works<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=1904s">31:44</a> — Salesforce’s AI engineering productivity claims<br><a href="https://www.youtube.com/watch?v=CBtrRrbPO7I&amp;t=2241s">37:21</a> — AI budgets are rising, but readiness is lagging<br>39:48 — How companies should build real AI adoption<br>42:31 — Why engineering is ahead of the rest of the enterprise<br>43:21 — Closing</p><p><br></p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" href="https://runpoint.ai/" img="https://img.transistorcdn.com/iVKFh0X7FN21u2KB9aYTGg6-2pIWdPP09kYe8o67_Cg/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mM2M0/ZjU3MjNjZmQxOTFk/OTI3MWQ3NWMxMDk4/MWZjMS5wbmc.jpg">Sam Gaddis</podcast:person>
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      <title>Runpoint: E11 - Anthropic Event, Designing with LLMs, the Proliferation of AI Consultants</title>
      <itunes:episode>12</itunes:episode>
      <podcast:episode>12</podcast:episode>
      <itunes:title>Runpoint: E11 - Anthropic Event, Designing with LLMs, the Proliferation of AI Consultants</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/ce48cd1b</link>
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        <![CDATA[<p>Runpoint Podcast E11: Code with Claude, the SaaSpocalypse, and AI Consulting Goes Mainstream<br>Back after a couple months off, with a bigger crew this time. Sam and Matthew are joined by Ryan Mish, one of Runpoint's operator engineers, and Thanh Pham of Signal Advisory.<br>Matthew just got back from Anthropic's Code with Claude conference and gives a side-by-side of the vibe at Anthropic vs. OpenAI (he hit both in the same week). From there we get into the stuff that's actually on our minds:</p><p>The flood of new "AI consulting firms" charging $20K to install Claude Code and call it a deployment, and what separates real work from theater<br>Whether the SaaSpocalypse is real, when it makes sense to rip out HubSpot, and where SaaS still wins (network effects, niche infrastructure, the school district that no VC will ever touch)<br>Why mid-market companies often only use 10% of the software they pay for, and what changes when the data finally talks to itself<br>Getting good design out of LLMs: Claude's house style vs. Codex 5.5 with image-gen mockups, and why Claude Design is still a prototyping tool<br>Closing round of what each of us is using right now: managed agents, Pi as a harness for steering Claude and Codex together, a PNPM supply chain attack PSA, HTML artifacts instead of Markdown, and a $30 conference swag computer turned into a reading game for Matthew's daughter</p><p>Chapters<br>00:00 Intro and new faces<br>01:30 Matthew's report from Code with Claude<br>05:30 Anthropic vs. OpenAI, in person<br>10:15 The AI consulting gold rush<br>14:30 Change management and company size<br>30:00 Is the SaaSpocalypse real?<br>40:30 Replacing software you only use 10% of<br>45:00 Getting good design out of LLMs<br>52:00 What we're using right now: managed agents, Pi, PNPM, HTML artifacts, and a tiny computer</p><p>Guests<br>Thanh Pham, Signal Advisory</p>]]>
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      <content:encoded>
        <![CDATA[<p>Runpoint Podcast E11: Code with Claude, the SaaSpocalypse, and AI Consulting Goes Mainstream<br>Back after a couple months off, with a bigger crew this time. Sam and Matthew are joined by Ryan Mish, one of Runpoint's operator engineers, and Thanh Pham of Signal Advisory.<br>Matthew just got back from Anthropic's Code with Claude conference and gives a side-by-side of the vibe at Anthropic vs. OpenAI (he hit both in the same week). From there we get into the stuff that's actually on our minds:</p><p>The flood of new "AI consulting firms" charging $20K to install Claude Code and call it a deployment, and what separates real work from theater<br>Whether the SaaSpocalypse is real, when it makes sense to rip out HubSpot, and where SaaS still wins (network effects, niche infrastructure, the school district that no VC will ever touch)<br>Why mid-market companies often only use 10% of the software they pay for, and what changes when the data finally talks to itself<br>Getting good design out of LLMs: Claude's house style vs. Codex 5.5 with image-gen mockups, and why Claude Design is still a prototyping tool<br>Closing round of what each of us is using right now: managed agents, Pi as a harness for steering Claude and Codex together, a PNPM supply chain attack PSA, HTML artifacts instead of Markdown, and a $30 conference swag computer turned into a reading game for Matthew's daughter</p><p>Chapters<br>00:00 Intro and new faces<br>01:30 Matthew's report from Code with Claude<br>05:30 Anthropic vs. OpenAI, in person<br>10:15 The AI consulting gold rush<br>14:30 Change management and company size<br>30:00 Is the SaaSpocalypse real?<br>40:30 Replacing software you only use 10% of<br>45:00 Getting good design out of LLMs<br>52:00 What we're using right now: managed agents, Pi, PNPM, HTML artifacts, and a tiny computer</p><p>Guests<br>Thanh Pham, Signal Advisory</p>]]>
      </content:encoded>
      <pubDate>Tue, 12 May 2026 12:03:58 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/ce48cd1b/d3b92821.mp3" length="51568799" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>3223</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Runpoint Podcast E11: Code with Claude, the SaaSpocalypse, and AI Consulting Goes Mainstream<br>Back after a couple months off, with a bigger crew this time. Sam and Matthew are joined by Ryan Mish, one of Runpoint's operator engineers, and Thanh Pham of Signal Advisory.<br>Matthew just got back from Anthropic's Code with Claude conference and gives a side-by-side of the vibe at Anthropic vs. OpenAI (he hit both in the same week). From there we get into the stuff that's actually on our minds:</p><p>The flood of new "AI consulting firms" charging $20K to install Claude Code and call it a deployment, and what separates real work from theater<br>Whether the SaaSpocalypse is real, when it makes sense to rip out HubSpot, and where SaaS still wins (network effects, niche infrastructure, the school district that no VC will ever touch)<br>Why mid-market companies often only use 10% of the software they pay for, and what changes when the data finally talks to itself<br>Getting good design out of LLMs: Claude's house style vs. Codex 5.5 with image-gen mockups, and why Claude Design is still a prototyping tool<br>Closing round of what each of us is using right now: managed agents, Pi as a harness for steering Claude and Codex together, a PNPM supply chain attack PSA, HTML artifacts instead of Markdown, and a $30 conference swag computer turned into a reading game for Matthew's daughter</p><p>Chapters<br>00:00 Intro and new faces<br>01:30 Matthew's report from Code with Claude<br>05:30 Anthropic vs. OpenAI, in person<br>10:15 The AI consulting gold rush<br>14:30 Change management and company size<br>30:00 Is the SaaSpocalypse real?<br>40:30 Replacing software you only use 10% of<br>45:00 Getting good design out of LLMs<br>52:00 What we're using right now: managed agents, Pi, PNPM, HTML artifacts, and a tiny computer</p><p>Guests<br>Thanh Pham, Signal Advisory</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" href="https://runpoint.ai/" img="https://img.transistorcdn.com/iVKFh0X7FN21u2KB9aYTGg6-2pIWdPP09kYe8o67_Cg/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mM2M0/ZjU3MjNjZmQxOTFk/OTI3MWQ3NWMxMDk4/MWZjMS5wbmc.jpg">Sam Gaddis</podcast:person>
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      <title>2025 AI Recap &amp; 2026 Predictions: Winners, Losers, and What's Actually Working</title>
      <itunes:episode>11</itunes:episode>
      <podcast:episode>11</podcast:episode>
      <itunes:title>2025 AI Recap &amp; 2026 Predictions: Winners, Losers, and What's Actually Working</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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        <![CDATA[<p>Happy New Year! In this episode, Matthew and Sam break down what actually happened in AI during 2025 and make predictions for what's coming in 2026.</p><p>We cover the biggest winners and losers, the apps and tools that changed how we work, who to follow for smart AI takes, what surprised us most, and where we think things are headed.</p><p>Key topics:<br>• Why companies that stayed curious won 2025<br>• OpenAI's fall from dominance to a three-horse race<br>• Claude Code and why it changed everything<br>• The tools we actually use daily (Whisper Flow, Granola, Cursor)<br>• Why vibe coded apps are passing enterprise code reviews<br>• Google's image generation breakthrough<br>• Our custom CRM build and the future of back office AI<br>• Why product managers are the winners of 2026<br>• The coming downfall of SaaS and low-skill trades</p><p>Plus: We launch our new Run Point Magazine and Sam accidentally emails hundreds of people.</p><p>🔗 Get the Run Point Magazine: [link]<br>🔗 Subscribe to our newsletter: [link]</p><p>---</p><p>## Chapters</p><p>0:00 - Intro &amp; Happy New Year<br>0:39 - Biggest Winner of 2025: Curious Companies<br>2:16 - Claude Code Changed Everything<br>4:04 - Biggest Loser of 2025: AI Resisters<br>5:25 - Why OpenAI Lost Ground in 2025<br>7:07 - Best App of 2025: Claude Code &amp; Whisper Flow<br>9:17 - Granola, Transcripts &amp; the Transcript-to-Action Pattern<br>10:29 - Why Cursor Won the IDE Wars<br>11:33 - Best Thinkers to Follow: Tyler Cowen &amp; Twitter Curation<br>14:40 - The Run Point Magazine Launch (and Email Disaster)<br>17:17 - Biggest Surprise: Enterprise-Grade Vibe Coded Apps<br>20:35 - Google's Image Generation Breakthrough<br>22:53 - Best Thing We Built: The AI-Powered CRM<br>27:08 - Worst Things We Built: Complex RAG Systems<br>28:52 - 2026 Predictions: Product Managers Win Big<br>30:37 - 2026 Loser Prediction: Half of SaaS Dies<br>32:28 - Why Low-Skill Home Services Are in Trouble<br>35:04 - AGI Is Basically Here (Contrarian Take)<br>38:10 - Why "Vibe Coding" Will Get Rebranded<br>38:38 - 2026 Resolutions: Back Office AI &amp; Continuous Learning<br>41:01 - Wrap Up</p>]]>
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      <content:encoded>
        <![CDATA[<p>Happy New Year! In this episode, Matthew and Sam break down what actually happened in AI during 2025 and make predictions for what's coming in 2026.</p><p>We cover the biggest winners and losers, the apps and tools that changed how we work, who to follow for smart AI takes, what surprised us most, and where we think things are headed.</p><p>Key topics:<br>• Why companies that stayed curious won 2025<br>• OpenAI's fall from dominance to a three-horse race<br>• Claude Code and why it changed everything<br>• The tools we actually use daily (Whisper Flow, Granola, Cursor)<br>• Why vibe coded apps are passing enterprise code reviews<br>• Google's image generation breakthrough<br>• Our custom CRM build and the future of back office AI<br>• Why product managers are the winners of 2026<br>• The coming downfall of SaaS and low-skill trades</p><p>Plus: We launch our new Run Point Magazine and Sam accidentally emails hundreds of people.</p><p>🔗 Get the Run Point Magazine: [link]<br>🔗 Subscribe to our newsletter: [link]</p><p>---</p><p>## Chapters</p><p>0:00 - Intro &amp; Happy New Year<br>0:39 - Biggest Winner of 2025: Curious Companies<br>2:16 - Claude Code Changed Everything<br>4:04 - Biggest Loser of 2025: AI Resisters<br>5:25 - Why OpenAI Lost Ground in 2025<br>7:07 - Best App of 2025: Claude Code &amp; Whisper Flow<br>9:17 - Granola, Transcripts &amp; the Transcript-to-Action Pattern<br>10:29 - Why Cursor Won the IDE Wars<br>11:33 - Best Thinkers to Follow: Tyler Cowen &amp; Twitter Curation<br>14:40 - The Run Point Magazine Launch (and Email Disaster)<br>17:17 - Biggest Surprise: Enterprise-Grade Vibe Coded Apps<br>20:35 - Google's Image Generation Breakthrough<br>22:53 - Best Thing We Built: The AI-Powered CRM<br>27:08 - Worst Things We Built: Complex RAG Systems<br>28:52 - 2026 Predictions: Product Managers Win Big<br>30:37 - 2026 Loser Prediction: Half of SaaS Dies<br>32:28 - Why Low-Skill Home Services Are in Trouble<br>35:04 - AGI Is Basically Here (Contrarian Take)<br>38:10 - Why "Vibe Coding" Will Get Rebranded<br>38:38 - 2026 Resolutions: Back Office AI &amp; Continuous Learning<br>41:01 - Wrap Up</p>]]>
      </content:encoded>
      <pubDate>Fri, 02 Jan 2026 11:41:31 -0600</pubDate>
      <author>Runpoint Partners</author>
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      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2469</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Happy New Year! In this episode, Matthew and Sam break down what actually happened in AI during 2025 and make predictions for what's coming in 2026.</p><p>We cover the biggest winners and losers, the apps and tools that changed how we work, who to follow for smart AI takes, what surprised us most, and where we think things are headed.</p><p>Key topics:<br>• Why companies that stayed curious won 2025<br>• OpenAI's fall from dominance to a three-horse race<br>• Claude Code and why it changed everything<br>• The tools we actually use daily (Whisper Flow, Granola, Cursor)<br>• Why vibe coded apps are passing enterprise code reviews<br>• Google's image generation breakthrough<br>• Our custom CRM build and the future of back office AI<br>• Why product managers are the winners of 2026<br>• The coming downfall of SaaS and low-skill trades</p><p>Plus: We launch our new Run Point Magazine and Sam accidentally emails hundreds of people.</p><p>🔗 Get the Run Point Magazine: [link]<br>🔗 Subscribe to our newsletter: [link]</p><p>---</p><p>## Chapters</p><p>0:00 - Intro &amp; Happy New Year<br>0:39 - Biggest Winner of 2025: Curious Companies<br>2:16 - Claude Code Changed Everything<br>4:04 - Biggest Loser of 2025: AI Resisters<br>5:25 - Why OpenAI Lost Ground in 2025<br>7:07 - Best App of 2025: Claude Code &amp; Whisper Flow<br>9:17 - Granola, Transcripts &amp; the Transcript-to-Action Pattern<br>10:29 - Why Cursor Won the IDE Wars<br>11:33 - Best Thinkers to Follow: Tyler Cowen &amp; Twitter Curation<br>14:40 - The Run Point Magazine Launch (and Email Disaster)<br>17:17 - Biggest Surprise: Enterprise-Grade Vibe Coded Apps<br>20:35 - Google's Image Generation Breakthrough<br>22:53 - Best Thing We Built: The AI-Powered CRM<br>27:08 - Worst Things We Built: Complex RAG Systems<br>28:52 - 2026 Predictions: Product Managers Win Big<br>30:37 - 2026 Loser Prediction: Half of SaaS Dies<br>32:28 - Why Low-Skill Home Services Are in Trouble<br>35:04 - AGI Is Basically Here (Contrarian Take)<br>38:10 - Why "Vibe Coding" Will Get Rebranded<br>38:38 - 2026 Resolutions: Back Office AI &amp; Continuous Learning<br>41:01 - Wrap Up</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/20bf2368/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>Episode 10 | Unlock AI Savings: R&amp;D Tax Credits for Builders</title>
      <itunes:episode>10</itunes:episode>
      <podcast:episode>10</podcast:episode>
      <itunes:title>Episode 10 | Unlock AI Savings: R&amp;D Tax Credits for Builders</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">46f67300-ff9e-4047-bed0-5097e8f15215</guid>
      <link>https://share.transistor.fm/s/21bf5478</link>
      <description>
        <![CDATA[<p>Learn how to save on your AI initiatives. On the Runpoint podcast, hosts Matthew Hall and Sam Gaddis welcome Ari Salafia, CEO and founder of TaxTaker. We explore how <strong>operator-engineers</strong> can claim R&amp;D tax credits to <strong>ship working AI systems</strong> and significantly reduce development costs.</p><p><strong>Chapters:<br></strong>00:00 Welcome Ari Salafia of TaxTaker<br>01:00 Understanding R&amp;D Tax Credits: TaxTaker's Mission<br>02:30 Why Businesses Should Care About R&amp;D Tax Credits Now<br>04:30 What You Stand to Gain: Key Expense Buckets<br>08:50 The Difference: Dollar-for-Dollar vs. Percentage<br>10:00 Qualified Research Expenses (QREs) Explained<br>11:00 Project Qualification: The Four-Part Test<br>14:00 Internal Use Software: Additional Requirements<br>15:45 Defining "Innovative" for Tax Credits<br>16:30 Case Study: Custom CRM Development<br>19:15 Custom Configuration vs. New Development<br>20:00 Documenting Projects for R&amp;D Credits<br>21:50 Structuring Contracts with AI Consultants (like Runpoint)<br>25:00 Case Study: AI for Business Intelligence Tools<br>27:10 Case Study: AI for Resource Allocation<br>28:15 Case Study: AI-Powered New Service Offerings<br>30:45 Advice for Employees Seeking Project Approval<br>35:40 Addressing Global Talent in R&amp;D Claims<br>38:00 Connect with TaxTaker</p><p><strong>Key Takeaways:</strong></p><ul><li><strong>Measurable Impact:</strong> Claim up to 10% of your AI development spend back in R&amp;D tax credits.</li><li><strong>Pilots to Production:</strong> Understand how to qualify your projects, from custom builds to new AI service offerings.</li><li><strong>No BS:</strong> Learn direct strategies for contract structuring (IP retention, financial risk, US-based work) to maximize your credit.</li><li><strong>Value Creation:</strong> For early-stage companies, credits can offset payroll taxes; for profitable companies, income tax.</li><li><strong>Forward-Deploy:</strong> Empower internal champions to make a strong business case for AI initiatives by highlighting potential savings.</li></ul><p>Connect with <strong>Runpoint</strong>: We partner with executives but sit with end users, moving clients from pilots to production with measurable impact.</p><p><strong>See a 2-week pilot plan</strong> for your next AI project: <a href="https://runpoint.ai/">https://runpoint.ai/</a></p><p><strong>Learn more about R&amp;D tax credits and TaxTaker:</strong> <a href="https://www.taxtaker.com/">https://www.taxtaker.com/</a></p><p><strong>Tags:</strong><br>#AIOps #AIinProduction #RandDTaxCredits #TaxTaker #Runpoint #AISavings #BusinessFinance #Innovation #TechTax #AIImplementation #OperatorEngineers #AIStrategy</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Learn how to save on your AI initiatives. On the Runpoint podcast, hosts Matthew Hall and Sam Gaddis welcome Ari Salafia, CEO and founder of TaxTaker. We explore how <strong>operator-engineers</strong> can claim R&amp;D tax credits to <strong>ship working AI systems</strong> and significantly reduce development costs.</p><p><strong>Chapters:<br></strong>00:00 Welcome Ari Salafia of TaxTaker<br>01:00 Understanding R&amp;D Tax Credits: TaxTaker's Mission<br>02:30 Why Businesses Should Care About R&amp;D Tax Credits Now<br>04:30 What You Stand to Gain: Key Expense Buckets<br>08:50 The Difference: Dollar-for-Dollar vs. Percentage<br>10:00 Qualified Research Expenses (QREs) Explained<br>11:00 Project Qualification: The Four-Part Test<br>14:00 Internal Use Software: Additional Requirements<br>15:45 Defining "Innovative" for Tax Credits<br>16:30 Case Study: Custom CRM Development<br>19:15 Custom Configuration vs. New Development<br>20:00 Documenting Projects for R&amp;D Credits<br>21:50 Structuring Contracts with AI Consultants (like Runpoint)<br>25:00 Case Study: AI for Business Intelligence Tools<br>27:10 Case Study: AI for Resource Allocation<br>28:15 Case Study: AI-Powered New Service Offerings<br>30:45 Advice for Employees Seeking Project Approval<br>35:40 Addressing Global Talent in R&amp;D Claims<br>38:00 Connect with TaxTaker</p><p><strong>Key Takeaways:</strong></p><ul><li><strong>Measurable Impact:</strong> Claim up to 10% of your AI development spend back in R&amp;D tax credits.</li><li><strong>Pilots to Production:</strong> Understand how to qualify your projects, from custom builds to new AI service offerings.</li><li><strong>No BS:</strong> Learn direct strategies for contract structuring (IP retention, financial risk, US-based work) to maximize your credit.</li><li><strong>Value Creation:</strong> For early-stage companies, credits can offset payroll taxes; for profitable companies, income tax.</li><li><strong>Forward-Deploy:</strong> Empower internal champions to make a strong business case for AI initiatives by highlighting potential savings.</li></ul><p>Connect with <strong>Runpoint</strong>: We partner with executives but sit with end users, moving clients from pilots to production with measurable impact.</p><p><strong>See a 2-week pilot plan</strong> for your next AI project: <a href="https://runpoint.ai/">https://runpoint.ai/</a></p><p><strong>Learn more about R&amp;D tax credits and TaxTaker:</strong> <a href="https://www.taxtaker.com/">https://www.taxtaker.com/</a></p><p><strong>Tags:</strong><br>#AIOps #AIinProduction #RandDTaxCredits #TaxTaker #Runpoint #AISavings #BusinessFinance #Innovation #TechTax #AIImplementation #OperatorEngineers #AIStrategy</p>]]>
      </content:encoded>
      <pubDate>Wed, 12 Nov 2025 08:38:18 -0600</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/21bf5478/e1e3f928.mp3" length="37567137" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2348</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Learn how to save on your AI initiatives. On the Runpoint podcast, hosts Matthew Hall and Sam Gaddis welcome Ari Salafia, CEO and founder of TaxTaker. We explore how <strong>operator-engineers</strong> can claim R&amp;D tax credits to <strong>ship working AI systems</strong> and significantly reduce development costs.</p><p><strong>Chapters:<br></strong>00:00 Welcome Ari Salafia of TaxTaker<br>01:00 Understanding R&amp;D Tax Credits: TaxTaker's Mission<br>02:30 Why Businesses Should Care About R&amp;D Tax Credits Now<br>04:30 What You Stand to Gain: Key Expense Buckets<br>08:50 The Difference: Dollar-for-Dollar vs. Percentage<br>10:00 Qualified Research Expenses (QREs) Explained<br>11:00 Project Qualification: The Four-Part Test<br>14:00 Internal Use Software: Additional Requirements<br>15:45 Defining "Innovative" for Tax Credits<br>16:30 Case Study: Custom CRM Development<br>19:15 Custom Configuration vs. New Development<br>20:00 Documenting Projects for R&amp;D Credits<br>21:50 Structuring Contracts with AI Consultants (like Runpoint)<br>25:00 Case Study: AI for Business Intelligence Tools<br>27:10 Case Study: AI for Resource Allocation<br>28:15 Case Study: AI-Powered New Service Offerings<br>30:45 Advice for Employees Seeking Project Approval<br>35:40 Addressing Global Talent in R&amp;D Claims<br>38:00 Connect with TaxTaker</p><p><strong>Key Takeaways:</strong></p><ul><li><strong>Measurable Impact:</strong> Claim up to 10% of your AI development spend back in R&amp;D tax credits.</li><li><strong>Pilots to Production:</strong> Understand how to qualify your projects, from custom builds to new AI service offerings.</li><li><strong>No BS:</strong> Learn direct strategies for contract structuring (IP retention, financial risk, US-based work) to maximize your credit.</li><li><strong>Value Creation:</strong> For early-stage companies, credits can offset payroll taxes; for profitable companies, income tax.</li><li><strong>Forward-Deploy:</strong> Empower internal champions to make a strong business case for AI initiatives by highlighting potential savings.</li></ul><p>Connect with <strong>Runpoint</strong>: We partner with executives but sit with end users, moving clients from pilots to production with measurable impact.</p><p><strong>See a 2-week pilot plan</strong> for your next AI project: <a href="https://runpoint.ai/">https://runpoint.ai/</a></p><p><strong>Learn more about R&amp;D tax credits and TaxTaker:</strong> <a href="https://www.taxtaker.com/">https://www.taxtaker.com/</a></p><p><strong>Tags:</strong><br>#AIOps #AIinProduction #RandDTaxCredits #TaxTaker #Runpoint #AISavings #BusinessFinance #Innovation #TechTax #AIImplementation #OperatorEngineers #AIStrategy</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/21bf5478/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>Episode 9 | The New AI Reality: ROI, Browser Wars &amp; Vanishing Software Value</title>
      <itunes:episode>9</itunes:episode>
      <podcast:episode>9</podcast:episode>
      <itunes:title>Episode 9 | The New AI Reality: ROI, Browser Wars &amp; Vanishing Software Value</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">953b5a96-c843-489d-8ebf-66d6e4b8ce9b</guid>
      <link>https://share.transistor.fm/s/907f3823</link>
      <description>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down the latest in AI, challenging the "95% failure" narrative with new ROI data and dissecting ChatGPT's "Atlas" browser launch. They codify emerging best practices for AI workflow automation, advise on navigating the crowded AI coding assistant market, and celebrate AI's power to enable entirely new work. The episode culminates in a crucial discussion on the diminishing value of software in acquisitions and what truly constitutes a moat in the age of AI.</p><p><strong>Chapters:</strong><br>00:00 AI's Evolving Landscape: Successes and Failures<br>04:00 ChatGPT's New Browser: A Game Changer?<br>07:33 Best Practices for AI Workflow Automation<br>12:00 Navigating the AI Coding Assistant Market<br>16:55 New Opportunities: AI Empowering New Work<br>21:28 Valuing Software in the Age of AI</p><p><strong>Key Takeaways:</strong></p><ul><li>AI ROI is proving positive for most firms, with a new study challenging older "failure" statistics.</li><li>ChatGPT's new "Atlas" browser shows potential but needs deeper context integration to become a true game-changer.</li><li>Effective AI automation prioritizes breaking workflows into atomic steps, automating deterministic parts, and using single agents for judgment with human oversight.</li><li>Distribution, data, and brand are the new moats; the value of software itself is rapidly diminishing in the age of AI.</li><li>AI empowers "net new" work, allowing individuals to tackle tasks and projects they previously wouldn't have attempted.<p></p></li></ul><p><strong>Tags:</strong><br>#AI #ChatGPT #Automation #EnterpriseAI #AICoding #SoftwareValuation #Podcast #RunpointPodcast</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down the latest in AI, challenging the "95% failure" narrative with new ROI data and dissecting ChatGPT's "Atlas" browser launch. They codify emerging best practices for AI workflow automation, advise on navigating the crowded AI coding assistant market, and celebrate AI's power to enable entirely new work. The episode culminates in a crucial discussion on the diminishing value of software in acquisitions and what truly constitutes a moat in the age of AI.</p><p><strong>Chapters:</strong><br>00:00 AI's Evolving Landscape: Successes and Failures<br>04:00 ChatGPT's New Browser: A Game Changer?<br>07:33 Best Practices for AI Workflow Automation<br>12:00 Navigating the AI Coding Assistant Market<br>16:55 New Opportunities: AI Empowering New Work<br>21:28 Valuing Software in the Age of AI</p><p><strong>Key Takeaways:</strong></p><ul><li>AI ROI is proving positive for most firms, with a new study challenging older "failure" statistics.</li><li>ChatGPT's new "Atlas" browser shows potential but needs deeper context integration to become a true game-changer.</li><li>Effective AI automation prioritizes breaking workflows into atomic steps, automating deterministic parts, and using single agents for judgment with human oversight.</li><li>Distribution, data, and brand are the new moats; the value of software itself is rapidly diminishing in the age of AI.</li><li>AI empowers "net new" work, allowing individuals to tackle tasks and projects they previously wouldn't have attempted.<p></p></li></ul><p><strong>Tags:</strong><br>#AI #ChatGPT #Automation #EnterpriseAI #AICoding #SoftwareValuation #Podcast #RunpointPodcast</p>]]>
      </content:encoded>
      <pubDate>Tue, 04 Nov 2025 15:09:18 -0600</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/907f3823/44824a71.mp3" length="24554417" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>1534</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down the latest in AI, challenging the "95% failure" narrative with new ROI data and dissecting ChatGPT's "Atlas" browser launch. They codify emerging best practices for AI workflow automation, advise on navigating the crowded AI coding assistant market, and celebrate AI's power to enable entirely new work. The episode culminates in a crucial discussion on the diminishing value of software in acquisitions and what truly constitutes a moat in the age of AI.</p><p><strong>Chapters:</strong><br>00:00 AI's Evolving Landscape: Successes and Failures<br>04:00 ChatGPT's New Browser: A Game Changer?<br>07:33 Best Practices for AI Workflow Automation<br>12:00 Navigating the AI Coding Assistant Market<br>16:55 New Opportunities: AI Empowering New Work<br>21:28 Valuing Software in the Age of AI</p><p><strong>Key Takeaways:</strong></p><ul><li>AI ROI is proving positive for most firms, with a new study challenging older "failure" statistics.</li><li>ChatGPT's new "Atlas" browser shows potential but needs deeper context integration to become a true game-changer.</li><li>Effective AI automation prioritizes breaking workflows into atomic steps, automating deterministic parts, and using single agents for judgment with human oversight.</li><li>Distribution, data, and brand are the new moats; the value of software itself is rapidly diminishing in the age of AI.</li><li>AI empowers "net new" work, allowing individuals to tackle tasks and projects they previously wouldn't have attempted.<p></p></li></ul><p><strong>Tags:</strong><br>#AI #ChatGPT #Automation #EnterpriseAI #AICoding #SoftwareValuation #Podcast #RunpointPodcast</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/907f3823/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>10 Hard Questions • This Week in AI</title>
      <itunes:episode>8</itunes:episode>
      <podcast:episode>8</podcast:episode>
      <itunes:title>10 Hard Questions • This Week in AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">e99dd751-8cd8-4b87-9e08-f1ccfdf7bf72</guid>
      <link>https://share.transistor.fm/s/9eae99ae</link>
      <description>
        <![CDATA[<p>Two builder-operators break down the last two weeks in AI using 10 Tyler Cowen–style questions. We get into Sora 2’s cameo culture, whether “thinking” models are worth the latency, agents that actually help, model choice for client work, the energy/compute wave, and why open-weights like DeepSeek matter (or don’t) for practitioners.</p><p>What you’ll get</p><p>Practical takes from people shipping client projects</p><p>Where Claude 4.5 vs GPT shines (coding vs writing)</p><p>When to use “extended thinking/deep research” vs fast models</p><p>Real talk on agents, meeting schedulers, and workflow design</p><p>Energy, nuclear, and why AI ≈ infrastructure</p><p>Open-weights vs ecosystems: where the moat really is</p><p>Chapters<br>00:00 – Cold open &amp; intro<br>00:26 – Who’s Tyler Cowen and why this format<br>02:00 – Q1: Sora 2, IP, and the “cameo economy”<br>06:44 – What we’re doing in this episode (format explainer)<br>08:11 – Q2: GPT apps &amp; the VibeCoder value prop (workflow architect vs app builder)<br>17:03 – Q3: “30-hour agents” &amp; autonomy myths (Claude, Replit Agent)<br>22:57 – Q4: When to use thinking models vs fast models (and deep research)<br>29:04 – Q5: SB-53 AI transparency—useful or compliance theater?<br>30:24 – Q6: Picking models for clients: capability, brand, or last best output?<br>37:01 – Q7: Agents that actually help (Lindy scheduling, weekly pain points)<br>41:34 – Q8: Compute, energy, and nuclear—should builders be optimistic?<br>46:50 – Q9: DeepSeek R1 costs &amp; the real moat (ecosystems &gt; raw perf)<br>49:33 – Wrap-up &amp; feedback ask</p><p>Links &amp; mentions (non-sponsored)</p><p>Tyler Cowen / Marginal Revolution</p><p>Anthropic Claude 4.5 (coding + writing)</p><p>OpenAI GPT-5 (auto/fast tasks), Deep Research modes</p><p>Lindy meeting agent</p><p>Replit Agent 3 (autonomous build experiments)</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Two builder-operators break down the last two weeks in AI using 10 Tyler Cowen–style questions. We get into Sora 2’s cameo culture, whether “thinking” models are worth the latency, agents that actually help, model choice for client work, the energy/compute wave, and why open-weights like DeepSeek matter (or don’t) for practitioners.</p><p>What you’ll get</p><p>Practical takes from people shipping client projects</p><p>Where Claude 4.5 vs GPT shines (coding vs writing)</p><p>When to use “extended thinking/deep research” vs fast models</p><p>Real talk on agents, meeting schedulers, and workflow design</p><p>Energy, nuclear, and why AI ≈ infrastructure</p><p>Open-weights vs ecosystems: where the moat really is</p><p>Chapters<br>00:00 – Cold open &amp; intro<br>00:26 – Who’s Tyler Cowen and why this format<br>02:00 – Q1: Sora 2, IP, and the “cameo economy”<br>06:44 – What we’re doing in this episode (format explainer)<br>08:11 – Q2: GPT apps &amp; the VibeCoder value prop (workflow architect vs app builder)<br>17:03 – Q3: “30-hour agents” &amp; autonomy myths (Claude, Replit Agent)<br>22:57 – Q4: When to use thinking models vs fast models (and deep research)<br>29:04 – Q5: SB-53 AI transparency—useful or compliance theater?<br>30:24 – Q6: Picking models for clients: capability, brand, or last best output?<br>37:01 – Q7: Agents that actually help (Lindy scheduling, weekly pain points)<br>41:34 – Q8: Compute, energy, and nuclear—should builders be optimistic?<br>46:50 – Q9: DeepSeek R1 costs &amp; the real moat (ecosystems &gt; raw perf)<br>49:33 – Wrap-up &amp; feedback ask</p><p>Links &amp; mentions (non-sponsored)</p><p>Tyler Cowen / Marginal Revolution</p><p>Anthropic Claude 4.5 (coding + writing)</p><p>OpenAI GPT-5 (auto/fast tasks), Deep Research modes</p><p>Lindy meeting agent</p><p>Replit Agent 3 (autonomous build experiments)</p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Oct 2025 13:49:00 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/9eae99ae/6651b8b5.mp3" length="40813437" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2550</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Two builder-operators break down the last two weeks in AI using 10 Tyler Cowen–style questions. We get into Sora 2’s cameo culture, whether “thinking” models are worth the latency, agents that actually help, model choice for client work, the energy/compute wave, and why open-weights like DeepSeek matter (or don’t) for practitioners.</p><p>What you’ll get</p><p>Practical takes from people shipping client projects</p><p>Where Claude 4.5 vs GPT shines (coding vs writing)</p><p>When to use “extended thinking/deep research” vs fast models</p><p>Real talk on agents, meeting schedulers, and workflow design</p><p>Energy, nuclear, and why AI ≈ infrastructure</p><p>Open-weights vs ecosystems: where the moat really is</p><p>Chapters<br>00:00 – Cold open &amp; intro<br>00:26 – Who’s Tyler Cowen and why this format<br>02:00 – Q1: Sora 2, IP, and the “cameo economy”<br>06:44 – What we’re doing in this episode (format explainer)<br>08:11 – Q2: GPT apps &amp; the VibeCoder value prop (workflow architect vs app builder)<br>17:03 – Q3: “30-hour agents” &amp; autonomy myths (Claude, Replit Agent)<br>22:57 – Q4: When to use thinking models vs fast models (and deep research)<br>29:04 – Q5: SB-53 AI transparency—useful or compliance theater?<br>30:24 – Q6: Picking models for clients: capability, brand, or last best output?<br>37:01 – Q7: Agents that actually help (Lindy scheduling, weekly pain points)<br>41:34 – Q8: Compute, energy, and nuclear—should builders be optimistic?<br>46:50 – Q9: DeepSeek R1 costs &amp; the real moat (ecosystems &gt; raw perf)<br>49:33 – Wrap-up &amp; feedback ask</p><p>Links &amp; mentions (non-sponsored)</p><p>Tyler Cowen / Marginal Revolution</p><p>Anthropic Claude 4.5 (coding + writing)</p><p>OpenAI GPT-5 (auto/fast tasks), Deep Research modes</p><p>Lindy meeting agent</p><p>Replit Agent 3 (autonomous build experiments)</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The “Nano Banana” Moment, GPT-5 Reality Check &amp; How to Win with AI | Runpoint Ep. 7</title>
      <itunes:episode>7</itunes:episode>
      <podcast:episode>7</podcast:episode>
      <itunes:title>The “Nano Banana” Moment, GPT-5 Reality Check &amp; How to Win with AI | Runpoint Ep. 7</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">1e35ce18-0d3a-43db-8cf5-0d6d088c708a</guid>
      <link>https://share.transistor.fm/s/deba0a59</link>
      <description>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down Google’s new image model (“Nano Banana”) with real tests (thumbnails, interior wallpaper, character persistence), give a no-BS GPT-5 reality check vs Claude Code, and unpack MIT’s State of AI in Business 2025—including the viral “95% of AI projects fail” stat. We cut through the hype and share a practical framework to land in the winning 5%: build small/fast, keep an expert-in-the-loop, measure outcomes, and forward-deploy an “AI nerd” to sit with your operators. We also talk browser agents (Claude for Chrome), throttling/caps, OpenAI’s CLI, and two personal builds (an E*TRADE API portfolio snapshot and a fantasy-draft helper).</p><p>Chapters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g">00:00</a> Intro<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=32s">00:32</a> Google’s “Nano Banana” image model—why it feels like a Photoshop killer<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=160s">02:40</a> Real tests: thumbnails, character persistence, interior wallpapering<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=358s">05:58</a> GPT-5 hype vs reality; coding speed vs chat experience<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=652s">10:52</a> OpenAI Codecs &amp; CLI vs Claude Code (features, trade-offs)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=746s">12:26</a> Anthropic caps/throttling—what changed and why it matters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=862s">14:22</a> Browser agents (Claude for Chrome): promise vs practical limits<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1201s">20:01</a> MIT report: “95% fail” explained—what the data actually says<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1675s">27:55</a> Adoption ≠ transformation; back-office beats front-office (for now)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2061s">34:21</a> The winning playbook: build small/fast, expert-in-the-loop, “shadow AI,” forward-deploy talent<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2582s">43:02</a> What we’re excited about: E*TRADE API snapshot, fantasy draft tool, Nano Banana<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2738s">45:38</a> Wrap</p><p>Key takeaways</p><p>Build small, ship fast, iterate.</p><p>Expert-in-the-loop to fully autonomous (for ROI today).</p><p>Back-office automations quietly print value.</p><p>Measure quality &amp; cycle-time, not just topline ROI.</p><p>Tags<br><a href="https://www.youtube.com/hashtag/ai">#AI</a> <a href="https://www.youtube.com/hashtag/gpt5">#GPT5</a> <a href="https://www.youtube.com/hashtag/claude">#Claude</a> <a href="https://www.youtube.com/hashtag/googleai">#GoogleAI</a> <a href="https://www.youtube.com/hashtag/automation">#Automation</a> <a href="https://www.youtube.com/hashtag/enterpriseai">#EnterpriseAI</a> <a href="https://www.youtube.com/hashtag/runpointpodcast">#RunpointPodcast</a></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down Google’s new image model (“Nano Banana”) with real tests (thumbnails, interior wallpaper, character persistence), give a no-BS GPT-5 reality check vs Claude Code, and unpack MIT’s State of AI in Business 2025—including the viral “95% of AI projects fail” stat. We cut through the hype and share a practical framework to land in the winning 5%: build small/fast, keep an expert-in-the-loop, measure outcomes, and forward-deploy an “AI nerd” to sit with your operators. We also talk browser agents (Claude for Chrome), throttling/caps, OpenAI’s CLI, and two personal builds (an E*TRADE API portfolio snapshot and a fantasy-draft helper).</p><p>Chapters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g">00:00</a> Intro<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=32s">00:32</a> Google’s “Nano Banana” image model—why it feels like a Photoshop killer<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=160s">02:40</a> Real tests: thumbnails, character persistence, interior wallpapering<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=358s">05:58</a> GPT-5 hype vs reality; coding speed vs chat experience<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=652s">10:52</a> OpenAI Codecs &amp; CLI vs Claude Code (features, trade-offs)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=746s">12:26</a> Anthropic caps/throttling—what changed and why it matters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=862s">14:22</a> Browser agents (Claude for Chrome): promise vs practical limits<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1201s">20:01</a> MIT report: “95% fail” explained—what the data actually says<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1675s">27:55</a> Adoption ≠ transformation; back-office beats front-office (for now)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2061s">34:21</a> The winning playbook: build small/fast, expert-in-the-loop, “shadow AI,” forward-deploy talent<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2582s">43:02</a> What we’re excited about: E*TRADE API snapshot, fantasy draft tool, Nano Banana<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2738s">45:38</a> Wrap</p><p>Key takeaways</p><p>Build small, ship fast, iterate.</p><p>Expert-in-the-loop to fully autonomous (for ROI today).</p><p>Back-office automations quietly print value.</p><p>Measure quality &amp; cycle-time, not just topline ROI.</p><p>Tags<br><a href="https://www.youtube.com/hashtag/ai">#AI</a> <a href="https://www.youtube.com/hashtag/gpt5">#GPT5</a> <a href="https://www.youtube.com/hashtag/claude">#Claude</a> <a href="https://www.youtube.com/hashtag/googleai">#GoogleAI</a> <a href="https://www.youtube.com/hashtag/automation">#Automation</a> <a href="https://www.youtube.com/hashtag/enterpriseai">#EnterpriseAI</a> <a href="https://www.youtube.com/hashtag/runpointpodcast">#RunpointPodcast</a></p>]]>
      </content:encoded>
      <pubDate>Tue, 16 Sep 2025 09:38:53 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/deba0a59/7203d801.mp3" length="43897236" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2743</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Matthew Hall and Sam Gaddis break down Google’s new image model (“Nano Banana”) with real tests (thumbnails, interior wallpaper, character persistence), give a no-BS GPT-5 reality check vs Claude Code, and unpack MIT’s State of AI in Business 2025—including the viral “95% of AI projects fail” stat. We cut through the hype and share a practical framework to land in the winning 5%: build small/fast, keep an expert-in-the-loop, measure outcomes, and forward-deploy an “AI nerd” to sit with your operators. We also talk browser agents (Claude for Chrome), throttling/caps, OpenAI’s CLI, and two personal builds (an E*TRADE API portfolio snapshot and a fantasy-draft helper).</p><p>Chapters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g">00:00</a> Intro<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=32s">00:32</a> Google’s “Nano Banana” image model—why it feels like a Photoshop killer<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=160s">02:40</a> Real tests: thumbnails, character persistence, interior wallpapering<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=358s">05:58</a> GPT-5 hype vs reality; coding speed vs chat experience<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=652s">10:52</a> OpenAI Codecs &amp; CLI vs Claude Code (features, trade-offs)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=746s">12:26</a> Anthropic caps/throttling—what changed and why it matters<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=862s">14:22</a> Browser agents (Claude for Chrome): promise vs practical limits<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1201s">20:01</a> MIT report: “95% fail” explained—what the data actually says<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=1675s">27:55</a> Adoption ≠ transformation; back-office beats front-office (for now)<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2061s">34:21</a> The winning playbook: build small/fast, expert-in-the-loop, “shadow AI,” forward-deploy talent<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2582s">43:02</a> What we’re excited about: E*TRADE API snapshot, fantasy draft tool, Nano Banana<br><a href="https://www.youtube.com/watch?v=UXpTQI8zE3g&amp;t=2738s">45:38</a> Wrap</p><p>Key takeaways</p><p>Build small, ship fast, iterate.</p><p>Expert-in-the-loop to fully autonomous (for ROI today).</p><p>Back-office automations quietly print value.</p><p>Measure quality &amp; cycle-time, not just topline ROI.</p><p>Tags<br><a href="https://www.youtube.com/hashtag/ai">#AI</a> <a href="https://www.youtube.com/hashtag/gpt5">#GPT5</a> <a href="https://www.youtube.com/hashtag/claude">#Claude</a> <a href="https://www.youtube.com/hashtag/googleai">#GoogleAI</a> <a href="https://www.youtube.com/hashtag/automation">#Automation</a> <a href="https://www.youtube.com/hashtag/enterpriseai">#EnterpriseAI</a> <a href="https://www.youtube.com/hashtag/runpointpodcast">#RunpointPodcast</a></p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Episode 6 | AI Fluency for Private Equity: From Zapier’s Framework to Real-World Tools</title>
      <itunes:episode>6</itunes:episode>
      <podcast:episode>6</podcast:episode>
      <itunes:title>Episode 6 | AI Fluency for Private Equity: From Zapier’s Framework to Real-World Tools</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">e66c58bb-0cdb-4dba-aeb2-cc13df04cc03</guid>
      <link>https://share.transistor.fm/s/7fcb5021</link>
      <description>
        <![CDATA[<p>Unlock the practical side of AI adoption in private equity. 🤖💼<br>Matthew Hall and Sam Gaddis break down Zapier’s widely shared AI Fluency Framework and then rebuild it for PE—covering deal sourcing, diligence, fund ops, and the coding workflows that actually ship AI products.</p><p>What You’ll Learn<br>Why Zapier made AI fluency non-negotiable for every new hire—and what that means outside tech.</p><p>A four-level ladder (Unacceptable → Transformative) tailored to PE functions:</p><p>Deal Sourcing</p><p>Deal Evaluation &amp; Diligence</p><p>Fund Operations</p><p>Value Creation &amp; Investor Relations</p><p>Concrete tool stacks: Clay, Replit, Claude Code, GitHub Issues, custom GPTs.</p><p>The “white whale” of PE ops: a chat interface that understands every deal doc—and why we’re this close.</p><p>Sam’s two-terminal setup that turns AI agents into reliable teammates (and kills downtime).</p><p>Links &amp; Resources<br>Zapier AI Fluency Framework → https://zapier.com/blog/zapier-ai-first-hiring-leaning/</p><p>Sam’s coding-workflow video → https://www.youtube.com/watch?v=v0o50r4hz24&amp;t=259s</p><p>Full PE AI-fluency matrix &amp; examples → coming soon on runpoint.ai</p><p>Subscribe for more AI-in-business deep dives → 🔔</p><p>Chapters<br>00:00  Intro<br>01:00  Zapier’s AI Fluency Framework explained<br>10:00  Deal Sourcing—spray-and-pray vs adaptive agents<br>17:00  Diligence workflows with Replit &amp; contract analyzers<br>24:25  Fund Ops dashboards, data warehouses &amp; the ‘impossible’ chatbot<br>32:00  Sam’s multitasking Claude Code + GitHub flow<br>35:00  How you can score your own firm (and help us refine the model)</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Unlock the practical side of AI adoption in private equity. 🤖💼<br>Matthew Hall and Sam Gaddis break down Zapier’s widely shared AI Fluency Framework and then rebuild it for PE—covering deal sourcing, diligence, fund ops, and the coding workflows that actually ship AI products.</p><p>What You’ll Learn<br>Why Zapier made AI fluency non-negotiable for every new hire—and what that means outside tech.</p><p>A four-level ladder (Unacceptable → Transformative) tailored to PE functions:</p><p>Deal Sourcing</p><p>Deal Evaluation &amp; Diligence</p><p>Fund Operations</p><p>Value Creation &amp; Investor Relations</p><p>Concrete tool stacks: Clay, Replit, Claude Code, GitHub Issues, custom GPTs.</p><p>The “white whale” of PE ops: a chat interface that understands every deal doc—and why we’re this close.</p><p>Sam’s two-terminal setup that turns AI agents into reliable teammates (and kills downtime).</p><p>Links &amp; Resources<br>Zapier AI Fluency Framework → https://zapier.com/blog/zapier-ai-first-hiring-leaning/</p><p>Sam’s coding-workflow video → https://www.youtube.com/watch?v=v0o50r4hz24&amp;t=259s</p><p>Full PE AI-fluency matrix &amp; examples → coming soon on runpoint.ai</p><p>Subscribe for more AI-in-business deep dives → 🔔</p><p>Chapters<br>00:00  Intro<br>01:00  Zapier’s AI Fluency Framework explained<br>10:00  Deal Sourcing—spray-and-pray vs adaptive agents<br>17:00  Diligence workflows with Replit &amp; contract analyzers<br>24:25  Fund Ops dashboards, data warehouses &amp; the ‘impossible’ chatbot<br>32:00  Sam’s multitasking Claude Code + GitHub flow<br>35:00  How you can score your own firm (and help us refine the model)</p>]]>
      </content:encoded>
      <pubDate>Mon, 04 Aug 2025 15:52:18 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/7fcb5021/45d4f606.mp3" length="31423668" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>1964</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Unlock the practical side of AI adoption in private equity. 🤖💼<br>Matthew Hall and Sam Gaddis break down Zapier’s widely shared AI Fluency Framework and then rebuild it for PE—covering deal sourcing, diligence, fund ops, and the coding workflows that actually ship AI products.</p><p>What You’ll Learn<br>Why Zapier made AI fluency non-negotiable for every new hire—and what that means outside tech.</p><p>A four-level ladder (Unacceptable → Transformative) tailored to PE functions:</p><p>Deal Sourcing</p><p>Deal Evaluation &amp; Diligence</p><p>Fund Operations</p><p>Value Creation &amp; Investor Relations</p><p>Concrete tool stacks: Clay, Replit, Claude Code, GitHub Issues, custom GPTs.</p><p>The “white whale” of PE ops: a chat interface that understands every deal doc—and why we’re this close.</p><p>Sam’s two-terminal setup that turns AI agents into reliable teammates (and kills downtime).</p><p>Links &amp; Resources<br>Zapier AI Fluency Framework → https://zapier.com/blog/zapier-ai-first-hiring-leaning/</p><p>Sam’s coding-workflow video → https://www.youtube.com/watch?v=v0o50r4hz24&amp;t=259s</p><p>Full PE AI-fluency matrix &amp; examples → coming soon on runpoint.ai</p><p>Subscribe for more AI-in-business deep dives → 🔔</p><p>Chapters<br>00:00  Intro<br>01:00  Zapier’s AI Fluency Framework explained<br>10:00  Deal Sourcing—spray-and-pray vs adaptive agents<br>17:00  Diligence workflows with Replit &amp; contract analyzers<br>24:25  Fund Ops dashboards, data warehouses &amp; the ‘impossible’ chatbot<br>32:00  Sam’s multitasking Claude Code + GitHub flow<br>35:00  How you can score your own firm (and help us refine the model)</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/7fcb5021/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>Episode 5 | Navigating the Future of Outbound Sales with AI</title>
      <itunes:episode>5</itunes:episode>
      <podcast:episode>5</podcast:episode>
      <itunes:title>Episode 5 | Navigating the Future of Outbound Sales with AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">7628d930-1f29-46cc-945a-0c3aaf6d6d9b</guid>
      <link>https://share.transistor.fm/s/c300d993</link>
      <description>
        <![CDATA[<p>In this episode of the Run Point Podcast, hosts Matthew Hall and Sam Gaddis engage with Shane Stearns to explore the evolving landscape of outbound sales, particularly in the context of AI. They discuss the historical eras of outbound sales, the challenges of the sequencing era, and the importance of quality over quantity in sales strategies. Shane shares insights on how AI can enhance list building and research, the fragmentation of sales tools, and the critical role of personalization in effective sales outreach. The conversation culminates in a discussion about the future of AI in sales coaching and training, emphasizing the need for a human touch in understanding client needs.<br>takeaways</p><p>Chapters<br>00:00 - Introduction to AI and Go-to-Market Strategies<br>01:26 - Eras of Outbound Sales: A Historical Perspective<br>04:07 - The Sequencing Era: Overload and Complexity<br>08:45 - The Shift to Quality Lists and Personalization<br>11:32 - The Rise of Clay: A New Era in Sales Tools<br>14:20 - Fragmentation vs. All-in-One Solutions<br>18:07 - Human Interaction: The Key to Effective Sales<br>21:31 - Understanding the Value Proposition<br>24:37 - Leveraging AI in Sales Processes<br>28:47 - Building Targeted Lists with AI<br>31:24 - The Role of Personalization in Outreach<br>34:36 - AI in Market Research and Focus Groups <br>39:06 - AI's Role in Sales Coaching and Training</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>In this episode of the Run Point Podcast, hosts Matthew Hall and Sam Gaddis engage with Shane Stearns to explore the evolving landscape of outbound sales, particularly in the context of AI. They discuss the historical eras of outbound sales, the challenges of the sequencing era, and the importance of quality over quantity in sales strategies. Shane shares insights on how AI can enhance list building and research, the fragmentation of sales tools, and the critical role of personalization in effective sales outreach. The conversation culminates in a discussion about the future of AI in sales coaching and training, emphasizing the need for a human touch in understanding client needs.<br>takeaways</p><p>Chapters<br>00:00 - Introduction to AI and Go-to-Market Strategies<br>01:26 - Eras of Outbound Sales: A Historical Perspective<br>04:07 - The Sequencing Era: Overload and Complexity<br>08:45 - The Shift to Quality Lists and Personalization<br>11:32 - The Rise of Clay: A New Era in Sales Tools<br>14:20 - Fragmentation vs. All-in-One Solutions<br>18:07 - Human Interaction: The Key to Effective Sales<br>21:31 - Understanding the Value Proposition<br>24:37 - Leveraging AI in Sales Processes<br>28:47 - Building Targeted Lists with AI<br>31:24 - The Role of Personalization in Outreach<br>34:36 - AI in Market Research and Focus Groups <br>39:06 - AI's Role in Sales Coaching and Training</p>]]>
      </content:encoded>
      <pubDate>Wed, 09 Jul 2025 12:16:36 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/c300d993/c96ba0bb.mp3" length="43387635" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2711</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>In this episode of the Run Point Podcast, hosts Matthew Hall and Sam Gaddis engage with Shane Stearns to explore the evolving landscape of outbound sales, particularly in the context of AI. They discuss the historical eras of outbound sales, the challenges of the sequencing era, and the importance of quality over quantity in sales strategies. Shane shares insights on how AI can enhance list building and research, the fragmentation of sales tools, and the critical role of personalization in effective sales outreach. The conversation culminates in a discussion about the future of AI in sales coaching and training, emphasizing the need for a human touch in understanding client needs.<br>takeaways</p><p>Chapters<br>00:00 - Introduction to AI and Go-to-Market Strategies<br>01:26 - Eras of Outbound Sales: A Historical Perspective<br>04:07 - The Sequencing Era: Overload and Complexity<br>08:45 - The Shift to Quality Lists and Personalization<br>11:32 - The Rise of Clay: A New Era in Sales Tools<br>14:20 - Fragmentation vs. All-in-One Solutions<br>18:07 - Human Interaction: The Key to Effective Sales<br>21:31 - Understanding the Value Proposition<br>24:37 - Leveraging AI in Sales Processes<br>28:47 - Building Targeted Lists with AI<br>31:24 - The Role of Personalization in Outreach<br>34:36 - AI in Market Research and Focus Groups <br>39:06 - AI's Role in Sales Coaching and Training</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>From Diapers to Deal Flow: How We Actually Use AI All Day</title>
      <itunes:episode>4</itunes:episode>
      <podcast:episode>4</podcast:episode>
      <itunes:title>From Diapers to Deal Flow: How We Actually Use AI All Day</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">c8d9e4c3-bb12-41d4-9250-18791e876293</guid>
      <link>https://share.transistor.fm/s/0ea22b17</link>
      <description>
        <![CDATA[<p>AI isn’t coming—it’s already in your pocket and on your P&amp;L. In this RunPoint Podcast episode, Matthew Hall and Sam Gaddis break down the real-world ways they’re using generative AI to:</p><ul><li><strong>Out-think the spreadsheet</strong> – build cash-flow models, plan investments, and pressure-test big bets in minutes.</li><li><strong>Parent with data</strong> – get actionable, guilt-free advice on sleep schedules, tough conversations, and everything in-between.</li><li><strong>Slash overhead</strong> – automate the grunt work across ops, finance, and customer success, freeing headcount for higher-margin jobs.</li><li><strong>Spot the next 10-bagger</strong> – why private-equity buyers are paying premiums for AI-enabled companies and how to ride that wave.</li></ul><p>They call out the hype, quantify the upside, and share the playbooks they’re actually running inside PE-backed businesses. If you want concrete tactics (not sci-fi headlines) on turning AI into personal leverage and fatter EBIT, this one’s for you.</p><p><strong>Timestamps</strong><br> 0:00 – Intro: AI hits daily life<br> 10:53 – Pro-level AI stacks and workflows<br> 21:19 – Macro view: margins, multiples, and the next decade</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>AI isn’t coming—it’s already in your pocket and on your P&amp;L. In this RunPoint Podcast episode, Matthew Hall and Sam Gaddis break down the real-world ways they’re using generative AI to:</p><ul><li><strong>Out-think the spreadsheet</strong> – build cash-flow models, plan investments, and pressure-test big bets in minutes.</li><li><strong>Parent with data</strong> – get actionable, guilt-free advice on sleep schedules, tough conversations, and everything in-between.</li><li><strong>Slash overhead</strong> – automate the grunt work across ops, finance, and customer success, freeing headcount for higher-margin jobs.</li><li><strong>Spot the next 10-bagger</strong> – why private-equity buyers are paying premiums for AI-enabled companies and how to ride that wave.</li></ul><p>They call out the hype, quantify the upside, and share the playbooks they’re actually running inside PE-backed businesses. If you want concrete tactics (not sci-fi headlines) on turning AI into personal leverage and fatter EBIT, this one’s for you.</p><p><strong>Timestamps</strong><br> 0:00 – Intro: AI hits daily life<br> 10:53 – Pro-level AI stacks and workflows<br> 21:19 – Macro view: margins, multiples, and the next decade</p>]]>
      </content:encoded>
      <pubDate>Fri, 20 Jun 2025 18:41:05 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/0ea22b17/bd7a7514.mp3" length="26150996" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>1634</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>AI isn’t coming—it’s already in your pocket and on your P&amp;L. In this RunPoint Podcast episode, Matthew Hall and Sam Gaddis break down the real-world ways they’re using generative AI to:</p><ul><li><strong>Out-think the spreadsheet</strong> – build cash-flow models, plan investments, and pressure-test big bets in minutes.</li><li><strong>Parent with data</strong> – get actionable, guilt-free advice on sleep schedules, tough conversations, and everything in-between.</li><li><strong>Slash overhead</strong> – automate the grunt work across ops, finance, and customer success, freeing headcount for higher-margin jobs.</li><li><strong>Spot the next 10-bagger</strong> – why private-equity buyers are paying premiums for AI-enabled companies and how to ride that wave.</li></ul><p>They call out the hype, quantify the upside, and share the playbooks they’re actually running inside PE-backed businesses. If you want concrete tactics (not sci-fi headlines) on turning AI into personal leverage and fatter EBIT, this one’s for you.</p><p><strong>Timestamps</strong><br> 0:00 – Intro: AI hits daily life<br> 10:53 – Pro-level AI stacks and workflows<br> 21:19 – Macro view: margins, multiples, and the next decade</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Episode 3 - Google I.O., newsletter automation, voice memos, AI tools, private equity, AI quality, sycophancy, technology trends</title>
      <itunes:episode>3</itunes:episode>
      <podcast:episode>3</podcast:episode>
      <itunes:title>Episode 3 - Google I.O., newsletter automation, voice memos, AI tools, private equity, AI quality, sycophancy, technology trends</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <description>
        <![CDATA[<p><strong>keywords</strong></p><p>AI, ChatGPT, Google I.O., newsletter automation, voice memos, AI tools, private equity, AI quality, sycophancy, technology trends</p><p><br><strong>summary</strong></p><p>In this episode of the Run Point podcast, hosts Sam Gaddis and Matthew Hall discuss practical AI tools that can be utilized immediately, including voice memos and ChatGPT projects. They also explore the creation of a personalized newsletter using AI, the latest innovations from Google I.O., and the ongoing concerns regarding the quality of AI-generated content and its tendency to be sycophantic. The conversation emphasizes the importance of understanding AI's capabilities and the potential for it to enhance productivity and creativity.</p><p><br><strong>takeaways</strong></p><ul><li>Using voice memos can enhance AI interactions.</li><li>ChatGPT projects help organize information effectively.</li><li>AI can automate newsletter creation for specific industries.</li><li>Google's advancements in AI are significant and impactful.</li><li>AI-generated content quality is a growing concern.</li><li>Sycophantic AI responses can be adjusted with prompts.</li><li>AI tools can serve as infinite force multipliers.</li><li>Understanding AI's capabilities is crucial for effective use.</li><li>The future of AI will involve more personalized applications.</li><li>AI's role in content creation is evolving rapidly.</li></ul><p><br></p><p><br></p><p><strong>Chapters</strong></p><p>00:00<br>Introduction to the Run Point Podcast</p><p>01:32<br>Practical AI Applications for Today</p><p>03:35<br>Voice Memos and AI</p><p>09:00<br>Innovative Newsletter Creation with AI</p><p>16:20<br>Google I.O. Highlights and AI Innovations</p><p>19:40<br>Exploring AI Utility and Frustrations</p><p>20:21<br>Google's AI Advancements and Market Position</p><p>22:08<br>The Future of Google's Ad Revenue</p><p>25:51<br>The Concept of AI Slop and Content Quality</p><p>28:05<br>Addressing AI Sycophancy and User Experience</p><p>30:51<br>The Need for Better AI Branding and Understanding</p><p>34:16<br>AI as a Force Multiplier in Everyday Life</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>keywords</strong></p><p>AI, ChatGPT, Google I.O., newsletter automation, voice memos, AI tools, private equity, AI quality, sycophancy, technology trends</p><p><br><strong>summary</strong></p><p>In this episode of the Run Point podcast, hosts Sam Gaddis and Matthew Hall discuss practical AI tools that can be utilized immediately, including voice memos and ChatGPT projects. They also explore the creation of a personalized newsletter using AI, the latest innovations from Google I.O., and the ongoing concerns regarding the quality of AI-generated content and its tendency to be sycophantic. The conversation emphasizes the importance of understanding AI's capabilities and the potential for it to enhance productivity and creativity.</p><p><br><strong>takeaways</strong></p><ul><li>Using voice memos can enhance AI interactions.</li><li>ChatGPT projects help organize information effectively.</li><li>AI can automate newsletter creation for specific industries.</li><li>Google's advancements in AI are significant and impactful.</li><li>AI-generated content quality is a growing concern.</li><li>Sycophantic AI responses can be adjusted with prompts.</li><li>AI tools can serve as infinite force multipliers.</li><li>Understanding AI's capabilities is crucial for effective use.</li><li>The future of AI will involve more personalized applications.</li><li>AI's role in content creation is evolving rapidly.</li></ul><p><br></p><p><br></p><p><strong>Chapters</strong></p><p>00:00<br>Introduction to the Run Point Podcast</p><p>01:32<br>Practical AI Applications for Today</p><p>03:35<br>Voice Memos and AI</p><p>09:00<br>Innovative Newsletter Creation with AI</p><p>16:20<br>Google I.O. Highlights and AI Innovations</p><p>19:40<br>Exploring AI Utility and Frustrations</p><p>20:21<br>Google's AI Advancements and Market Position</p><p>22:08<br>The Future of Google's Ad Revenue</p><p>25:51<br>The Concept of AI Slop and Content Quality</p><p>28:05<br>Addressing AI Sycophancy and User Experience</p><p>30:51<br>The Need for Better AI Branding and Understanding</p><p>34:16<br>AI as a Force Multiplier in Everyday Life</p>]]>
      </content:encoded>
      <pubDate>Fri, 23 May 2025 14:12:33 -0500</pubDate>
      <author>Runpoint Partners</author>
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      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/oDNPGPgkK40A1ywb0e5rvJWNTFz4aPFbH10G5uzpE34/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8zZTIx/MDdhNGFlNjdjMGUw/NTkxNDlmOWFjMzhm/ZjYyNS5wbmc.jpg"/>
      <itunes:duration>2500</itunes:duration>
      <itunes:summary>
        <![CDATA[<p><strong>keywords</strong></p><p>AI, ChatGPT, Google I.O., newsletter automation, voice memos, AI tools, private equity, AI quality, sycophancy, technology trends</p><p><br><strong>summary</strong></p><p>In this episode of the Run Point podcast, hosts Sam Gaddis and Matthew Hall discuss practical AI tools that can be utilized immediately, including voice memos and ChatGPT projects. They also explore the creation of a personalized newsletter using AI, the latest innovations from Google I.O., and the ongoing concerns regarding the quality of AI-generated content and its tendency to be sycophantic. The conversation emphasizes the importance of understanding AI's capabilities and the potential for it to enhance productivity and creativity.</p><p><br><strong>takeaways</strong></p><ul><li>Using voice memos can enhance AI interactions.</li><li>ChatGPT projects help organize information effectively.</li><li>AI can automate newsletter creation for specific industries.</li><li>Google's advancements in AI are significant and impactful.</li><li>AI-generated content quality is a growing concern.</li><li>Sycophantic AI responses can be adjusted with prompts.</li><li>AI tools can serve as infinite force multipliers.</li><li>Understanding AI's capabilities is crucial for effective use.</li><li>The future of AI will involve more personalized applications.</li><li>AI's role in content creation is evolving rapidly.</li></ul><p><br></p><p><br></p><p><strong>Chapters</strong></p><p>00:00<br>Introduction to the Run Point Podcast</p><p>01:32<br>Practical AI Applications for Today</p><p>03:35<br>Voice Memos and AI</p><p>09:00<br>Innovative Newsletter Creation with AI</p><p>16:20<br>Google I.O. Highlights and AI Innovations</p><p>19:40<br>Exploring AI Utility and Frustrations</p><p>20:21<br>Google's AI Advancements and Market Position</p><p>22:08<br>The Future of Google's Ad Revenue</p><p>25:51<br>The Concept of AI Slop and Content Quality</p><p>28:05<br>Addressing AI Sycophancy and User Experience</p><p>30:51<br>The Need for Better AI Branding and Understanding</p><p>34:16<br>AI as a Force Multiplier in Everyday Life</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
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      <title>Episode 2 | PowerPoint Is Dead: Building the Future of Work With AI</title>
      <itunes:episode>2</itunes:episode>
      <podcast:episode>2</podcast:episode>
      <itunes:title>Episode 2 | PowerPoint Is Dead: Building the Future of Work With AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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        <![CDATA[<p><strong>keywords<br></strong>AI, tools, development, PowerPoint, automation, coding, data analysis, business insights, technology, productivity</p><p><br><strong>summary</strong></p><p>In this conversation, Matthew Hall and Sam Gaddis discuss their current projects, tools they find useful, and their opinions on the future of presentations and AI in business. They explore the effectiveness of various AI tools for automating tasks, the decline of traditional presentation software like PowerPoint, and the evolving role of AI in financial analysis and project management. The discussion also delves into their development stacks and best practices for coding and project planning.</p><p><br><strong>takeaways</strong></p><ul><li>Sam is excited about a new project involving data scraping and analysis.</li><li>Matthew is focused on developing coding tools and models.</li><li>They discuss the utility of AI tools for business applications.</li><li>PowerPoint is becoming obsolete in favor of more dynamic tools.</li><li>AI can effectively replace some traditional roles in finance.</li><li>Customization of prompts is key to getting the best results from AI.</li><li>Planning is crucial before starting any coding project.</li><li>AI can significantly reduce the time spent on tedious tasks.</li><li>Using up-to-date API documentation is essential for successful coding.</li><li>The conversation emphasizes the importance of clear communication in project specifications.</li></ul><p><br></p><p><strong>Chapters<br></strong><br></p><p>00:00 - Introduction and Exciting Projects</p><p>03:23 - Tools You Can Use Today</p><p>17:58 - Hot Takes on PowerPoint and AI</p><p>30:55 - In the Weeds: Development Stack and Challenges</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>keywords<br></strong>AI, tools, development, PowerPoint, automation, coding, data analysis, business insights, technology, productivity</p><p><br><strong>summary</strong></p><p>In this conversation, Matthew Hall and Sam Gaddis discuss their current projects, tools they find useful, and their opinions on the future of presentations and AI in business. They explore the effectiveness of various AI tools for automating tasks, the decline of traditional presentation software like PowerPoint, and the evolving role of AI in financial analysis and project management. The discussion also delves into their development stacks and best practices for coding and project planning.</p><p><br><strong>takeaways</strong></p><ul><li>Sam is excited about a new project involving data scraping and analysis.</li><li>Matthew is focused on developing coding tools and models.</li><li>They discuss the utility of AI tools for business applications.</li><li>PowerPoint is becoming obsolete in favor of more dynamic tools.</li><li>AI can effectively replace some traditional roles in finance.</li><li>Customization of prompts is key to getting the best results from AI.</li><li>Planning is crucial before starting any coding project.</li><li>AI can significantly reduce the time spent on tedious tasks.</li><li>Using up-to-date API documentation is essential for successful coding.</li><li>The conversation emphasizes the importance of clear communication in project specifications.</li></ul><p><br></p><p><strong>Chapters<br></strong><br></p><p>00:00 - Introduction and Exciting Projects</p><p>03:23 - Tools You Can Use Today</p><p>17:58 - Hot Takes on PowerPoint and AI</p><p>30:55 - In the Weeds: Development Stack and Challenges</p>]]>
      </content:encoded>
      <pubDate>Fri, 02 May 2025 17:32:28 -0500</pubDate>
      <author>Runpoint Partners</author>
      <enclosure url="https://media.transistor.fm/0b1924c9/7adb4583.mp3" length="30519099" type="audio/mpeg"/>
      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/ub1GxeLj9BXVOxFmp4xcEeeuKL0Sz6zF4O59zTtPb10/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yYmM1/OGViMzM3OTg4ZTVl/Y2IyZDU3MDc5M2Y0/ZDg2YS5wbmc.jpg"/>
      <itunes:duration>1905</itunes:duration>
      <itunes:summary>
        <![CDATA[<p><strong>keywords<br></strong>AI, tools, development, PowerPoint, automation, coding, data analysis, business insights, technology, productivity</p><p><br><strong>summary</strong></p><p>In this conversation, Matthew Hall and Sam Gaddis discuss their current projects, tools they find useful, and their opinions on the future of presentations and AI in business. They explore the effectiveness of various AI tools for automating tasks, the decline of traditional presentation software like PowerPoint, and the evolving role of AI in financial analysis and project management. The discussion also delves into their development stacks and best practices for coding and project planning.</p><p><br><strong>takeaways</strong></p><ul><li>Sam is excited about a new project involving data scraping and analysis.</li><li>Matthew is focused on developing coding tools and models.</li><li>They discuss the utility of AI tools for business applications.</li><li>PowerPoint is becoming obsolete in favor of more dynamic tools.</li><li>AI can effectively replace some traditional roles in finance.</li><li>Customization of prompts is key to getting the best results from AI.</li><li>Planning is crucial before starting any coding project.</li><li>AI can significantly reduce the time spent on tedious tasks.</li><li>Using up-to-date API documentation is essential for successful coding.</li><li>The conversation emphasizes the importance of clear communication in project specifications.</li></ul><p><br></p><p><strong>Chapters<br></strong><br></p><p>00:00 - Introduction and Exciting Projects</p><p>03:23 - Tools You Can Use Today</p><p>17:58 - Hot Takes on PowerPoint and AI</p><p>30:55 - In the Weeds: Development Stack and Challenges</p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" href="https://runpoint.ai/" img="https://img.transistorcdn.com/iVKFh0X7FN21u2KB9aYTGg6-2pIWdPP09kYe8o67_Cg/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mM2M0/ZjU3MjNjZmQxOTFk/OTI3MWQ3NWMxMDk4/MWZjMS5wbmc.jpg">Sam Gaddis</podcast:person>
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    <item>
      <title>Runpoint Podcast: Episode 1 - Lindy vs. N8n vs Custom</title>
      <itunes:episode>1</itunes:episode>
      <podcast:episode>1</podcast:episode>
      <itunes:title>Runpoint Podcast: Episode 1 - Lindy vs. N8n vs Custom</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/37a82acb</link>
      <description>
        <![CDATA[<p>In this conversation, Matthew Hall and Sam Gaddis explore various AI tools and their applications in workflow automation, lead enrichment, and document management. They discuss their experiences with Lindy, N8n, and a custom-built lead enrichment app, highlighting the pros and cons of each tool. </p><p>The conversation also delves into the SuperCIM project, which focuses on document synthesis and management for private equity clients. They conclude by discussing the future of AI in business and the potential for custom solutions to meet specific needs.</p><p>Chapters</p><p>00:00 Introduction to AI Tools and Their Applications<br>02:47 Exploring Lindy: The Agent Swarm Approach<br>05:59 N8n: A Developer-Friendly Automation Solution<br>08:57 Custom Lead Enrichment with Cursor<br>12:01 Comparing DIY Solutions to Established SaaS<br>14:58 The Future of Custom Solutions vs. SaaS<br>18:01 Building Tools for Specific Needs<br>20:15 Custom Tooling for Business Needs<br>20:57 Introducing Super Sim: A Game Changer<br>22:12 Document Management in Private Equity<br>24:00 Customization and Metrics in Super Sim<br>26:10 The Role of LLMs in Data Analysis<br>28:14 From Data to Insights: The Moneyball Approach<br>29:56 Creative Uses of Structured Data<br>32:00 Unlocking Value in Unstructured Data<br>35:42 Closing Thoughts and Future Opportunities</p><p><br>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends<br></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>In this conversation, Matthew Hall and Sam Gaddis explore various AI tools and their applications in workflow automation, lead enrichment, and document management. They discuss their experiences with Lindy, N8n, and a custom-built lead enrichment app, highlighting the pros and cons of each tool. </p><p>The conversation also delves into the SuperCIM project, which focuses on document synthesis and management for private equity clients. They conclude by discussing the future of AI in business and the potential for custom solutions to meet specific needs.</p><p>Chapters</p><p>00:00 Introduction to AI Tools and Their Applications<br>02:47 Exploring Lindy: The Agent Swarm Approach<br>05:59 N8n: A Developer-Friendly Automation Solution<br>08:57 Custom Lead Enrichment with Cursor<br>12:01 Comparing DIY Solutions to Established SaaS<br>14:58 The Future of Custom Solutions vs. SaaS<br>18:01 Building Tools for Specific Needs<br>20:15 Custom Tooling for Business Needs<br>20:57 Introducing Super Sim: A Game Changer<br>22:12 Document Management in Private Equity<br>24:00 Customization and Metrics in Super Sim<br>26:10 The Role of LLMs in Data Analysis<br>28:14 From Data to Insights: The Moneyball Approach<br>29:56 Creative Uses of Structured Data<br>32:00 Unlocking Value in Unstructured Data<br>35:42 Closing Thoughts and Future Opportunities</p><p><br>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends<br></p>]]>
      </content:encoded>
      <pubDate>Fri, 25 Apr 2025 10:24:16 -0500</pubDate>
      <author>Runpoint Partners</author>
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      <itunes:author>Runpoint Partners</itunes:author>
      <itunes:duration>2030</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>In this conversation, Matthew Hall and Sam Gaddis explore various AI tools and their applications in workflow automation, lead enrichment, and document management. They discuss their experiences with Lindy, N8n, and a custom-built lead enrichment app, highlighting the pros and cons of each tool. </p><p>The conversation also delves into the SuperCIM project, which focuses on document synthesis and management for private equity clients. They conclude by discussing the future of AI in business and the potential for custom solutions to meet specific needs.</p><p>Chapters</p><p>00:00 Introduction to AI Tools and Their Applications<br>02:47 Exploring Lindy: The Agent Swarm Approach<br>05:59 N8n: A Developer-Friendly Automation Solution<br>08:57 Custom Lead Enrichment with Cursor<br>12:01 Comparing DIY Solutions to Established SaaS<br>14:58 The Future of Custom Solutions vs. SaaS<br>18:01 Building Tools for Specific Needs<br>20:15 Custom Tooling for Business Needs<br>20:57 Introducing Super Sim: A Game Changer<br>22:12 Document Management in Private Equity<br>24:00 Customization and Metrics in Super Sim<br>26:10 The Role of LLMs in Data Analysis<br>28:14 From Data to Insights: The Moneyball Approach<br>29:56 Creative Uses of Structured Data<br>32:00 Unlocking Value in Unstructured Data<br>35:42 Closing Thoughts and Future Opportunities</p><p><br>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends<br></p>]]>
      </itunes:summary>
      <itunes:keywords>AI tools, workflow automation, Lindy, N8n, lead enrichment, SuperSIM, document management, business applications, custom solutions, technology trends</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" href="https://runpoint.ai/" img="https://img.transistorcdn.com/iVKFh0X7FN21u2KB9aYTGg6-2pIWdPP09kYe8o67_Cg/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mM2M0/ZjU3MjNjZmQxOTFk/OTI3MWQ3NWMxMDk4/MWZjMS5wbmc.jpg">Sam Gaddis</podcast:person>
      <podcast:transcript url="https://share.transistor.fm/s/37a82acb/transcript.txt" type="text/plain"/>
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