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    <title>Contextually Aware</title>
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    <description>What product managers can actually build with AI today—and where it still breaks.
</description>
    <copyright>© 2026 Luis Calderon</copyright>
    <podcast:guid>088b4bdf-6714-5c11-bd29-a83a6963dfab</podcast:guid>
    <podcast:locked>yes</podcast:locked>
    <language>en</language>
    <pubDate>Mon, 10 Aug 2026 12:43:10 -0700</pubDate>
    <lastBuildDate>Mon, 10 Aug 2026 12:44:07 -0700</lastBuildDate>
    <link>https://contextuallyaware.com</link>
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      <title>Contextually Aware</title>
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      <itunes:category text="Management"/>
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    <itunes:type>episodic</itunes:type>
    <itunes:author>Luis Calderon</itunes:author>
    <itunes:image href="https://img.transistorcdn.com/KeM9QIAshth_PXuX-BGE-QUV8CJLkZiFKDUOfuKHqpg/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hMzNm/MDlmMGIyM2FjZTNl/N2Q5MWM0N2ZhZmFl/MDY2OC5wbmc.jpg"/>
    <itunes:summary>What product managers can actually build with AI today—and where it still breaks.
</itunes:summary>
    <itunes:subtitle>What product managers can actually build with AI today—and where it still breaks.</itunes:subtitle>
    <itunes:keywords>product management, AI, tech, agentic, LLM</itunes:keywords>
    <itunes:owner>
      <itunes:name>GrowthAlchemyLab</itunes:name>
      <itunes:email>luis@growthalchemylab.com</itunes:email>
    </itunes:owner>
    <itunes:complete>No</itunes:complete>
    <itunes:explicit>No</itunes:explicit>
    <item>
      <title>I Built More Agents. The Work Got Harder.</title>
      <itunes:episode>39</itunes:episode>
      <podcast:episode>39</podcast:episode>
      <itunes:title>I Built More Agents. The Work Got Harder.</itunes:title>
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      <description>
        <![CDATA[<p><strong>Episode 39: I Built More Agents. The Work Got Harder.</strong></p>
<p>Vercel's vision made one production agent easier to ship. The second agent reveals the hidden cost: shared context, permissions, handoffs, approvals, and proof.</p>
<p><strong>Hosts:</strong> Luis and Carina · <strong>Runtime:</strong> 11.3 minutes</p>
<p><b>Chapters</b></p>
<ul>
  <li>Cold open and introduction</li>
  <li>The second agent changes the job</li>
  <li>What production runtimes solve</li>
  <li>The hidden tax at the handoff</li>
  <li>The Agent Workplane</li>
  <li>Establish, Operate, Compound</li>
  <li>The small first test</li>
  <li>What comes next</li>
  <li>Sign-off</li>
</ul>
<p><a href="https://growthalchemylab.com/blog/i-built-more-agents-the-work-got-harder">Read the full article →</a></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>Episode 39: I Built More Agents. The Work Got Harder.</strong></p>
<p>Vercel's vision made one production agent easier to ship. The second agent reveals the hidden cost: shared context, permissions, handoffs, approvals, and proof.</p>
<p><strong>Hosts:</strong> Luis and Carina · <strong>Runtime:</strong> 11.3 minutes</p>
<p><b>Chapters</b></p>
<ul>
  <li>Cold open and introduction</li>
  <li>The second agent changes the job</li>
  <li>What production runtimes solve</li>
  <li>The hidden tax at the handoff</li>
  <li>The Agent Workplane</li>
  <li>Establish, Operate, Compound</li>
  <li>The small first test</li>
  <li>What comes next</li>
  <li>Sign-off</li>
</ul>
<p><a href="https://growthalchemylab.com/blog/i-built-more-agents-the-work-got-harder">Read the full article →</a></p>]]>
      </content:encoded>
      <pubDate>Mon, 10 Aug 2026 12:43:10 -0700</pubDate>
      <author>Luis Calderon and Carina</author>
      <enclosure url="https://media.transistor.fm/c3d36fd0/d25b97ff.mp3" length="10925311" type="audio/mpeg"/>
      <itunes:author>Luis Calderon and Carina</itunes:author>
      <itunes:duration>680</itunes:duration>
      <itunes:summary>Vercel's vision made one production agent easier to ship. The second agent reveals the hidden cost: shared context, permissions, handoffs, approvals, and proof.</itunes:summary>
      <itunes:subtitle>Vercel's vision made one production agent easier to ship. The second agent reveals the hidden cost: shared context, permissions, handoffs, approvals, and proof.</itunes:subtitle>
      <itunes:keywords>agent coordination, agent workplane, multi-agent systems</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/c3d36fd0/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>On the internet, nobody knows you're an agent</title>
      <itunes:episode>38</itunes:episode>
      <podcast:episode>38</podcast:episode>
      <itunes:title>On the internet, nobody knows you're an agent</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">024784b7-fd5e-4027-b234-c9c0ef685840</guid>
      <link>https://share.transistor.fm/s/4e1b418f</link>
      <description>
        <![CDATA[Luis and Maya dig into why the web treats every AI agent like a burglar, and what Block's new Buzz platform does about it.

Bots are now about 57% of web traffic, so the default answer to an agent is "blocked" — which punishes the ordinary case of asking your assistant to go check a price. Buzz gives every participant, human or agent, their own cryptographic keys, so work is signed by whoever actually did it. The bigger point: every serious payments rail, from Visa to Mastercard to Google, has independently landed on the same precondition. Nobody hands a wallet to anonymous software. Identity comes first, or nothing comes at all.

Chapters
00:00 Meet your host
00:20 I was wrong on a client call
00:55 What Buzz actually shipped
02:00 Nobody knows you're an agent
02:40 Identity is the toll gate
03:30 Three moves for Monday
04:35 The skeptic ledger
05:15 Where to read the rest

Full written breakdown, with every source and the complete skeptic ledger:
https://growthalchemylab.com/blog/on-the-internet-nobody-knows-youre-an-agent

More episodes: https://contextuallyaware.com]]>
      </description>
      <content:encoded>
        <![CDATA[Luis and Maya dig into why the web treats every AI agent like a burglar, and what Block's new Buzz platform does about it.

Bots are now about 57% of web traffic, so the default answer to an agent is "blocked" — which punishes the ordinary case of asking your assistant to go check a price. Buzz gives every participant, human or agent, their own cryptographic keys, so work is signed by whoever actually did it. The bigger point: every serious payments rail, from Visa to Mastercard to Google, has independently landed on the same precondition. Nobody hands a wallet to anonymous software. Identity comes first, or nothing comes at all.

Chapters
00:00 Meet your host
00:20 I was wrong on a client call
00:55 What Buzz actually shipped
02:00 Nobody knows you're an agent
02:40 Identity is the toll gate
03:30 Three moves for Monday
04:35 The skeptic ledger
05:15 Where to read the rest

Full written breakdown, with every source and the complete skeptic ledger:
https://growthalchemylab.com/blog/on-the-internet-nobody-knows-youre-an-agent

More episodes: https://contextuallyaware.com]]>
      </content:encoded>
      <pubDate>Mon, 10 Aug 2026 10:32:02 -0700</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/4e1b418f/9239e7be.mp3" length="5593650" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/bOz4Ud46f2fwewl7k9rXIPLdoyImLWGWhORtlI6Nijk/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yOWY3/NmE0MmE0NTE3MDU4/NzQwOGI2OTMzZDEz/YzQxMy5qcGc.jpg"/>
      <itunes:duration>347</itunes:duration>
      <itunes:summary>Block gave AI agents their own cryptographic ID cards. Why the web blocks every agent by default, and why identity is the toll gate standing in front of agent payments.</itunes:summary>
      <itunes:subtitle>Block gave AI agents their own cryptographic ID cards. Why the web blocks every agent by default, and why identity is the toll gate standing in front of agent payments.</itunes:subtitle>
      <itunes:keywords>product management, AI, tech, agentic, LLM</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The bottom has fallen out of software development</title>
      <itunes:episode>35</itunes:episode>
      <podcast:episode>35</podcast:episode>
      <itunes:title>The bottom has fallen out of software development</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/9ba2af70</link>
      <description>
        <![CDATA[]]>
      </description>
      <content:encoded>
        <![CDATA[]]>
      </content:encoded>
      <pubDate>Fri, 31 Jul 2026 01:18:41 -0700</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/9ba2af70/824f9969.mp3" length="7660651" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/J9RtcnnPYIIYEkwc0A2CcRqlWPN1GzKHboY7gKzkT1E/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yMzZj/YmMwNmQ0Njk1MDU4/M2EwNWFmOGZmNDM2/ZTEyZS5wbmc.jpg"/>
      <itunes:duration>477</itunes:duration>
      <itunes:summary>
        <![CDATA[]]>
      </itunes:summary>
      <itunes:keywords>product management, AI, tech, agentic, LLM</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>I maxed out my human context window</title>
      <itunes:episode>37</itunes:episode>
      <podcast:episode>37</podcast:episode>
      <itunes:title>I maxed out my human context window</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">47932f9a-0620-423c-9b18-8534d8bb77c9</guid>
      <link>https://share.transistor.fm/s/bfb4d80f</link>
      <description>
        <![CDATA[<p><strong>Episode 37: I maxed out my context window</strong></p><p>Luis and Maya unpack the hidden bottleneck in agent-heavy work: the human approval queue. The fix is less clever tooling, fewer harnesses, one queue, and a daily count of real decisions.</p><p>Chapters</p><ul><li><strong>00:00</strong> — Meet your host</li><li><strong>00:42</strong> — The setup</li><li><strong>01:24</strong> — What the article says</li><li><strong>02:06</strong> — The killer line</li><li><strong>02:48</strong> — The new way to think</li><li><strong>03:30</strong> — Concrete moves</li><li><strong>04:12</strong> — One thing to remember</li><li><strong>04:54</strong> — Where to find us</li><li><strong>05:36</strong> — Sign-off</li></ul><p><a href="https://growthalchemylab.com/blog/i-became-the-context-window">Read the full article →</a></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>Episode 37: I maxed out my context window</strong></p><p>Luis and Maya unpack the hidden bottleneck in agent-heavy work: the human approval queue. The fix is less clever tooling, fewer harnesses, one queue, and a daily count of real decisions.</p><p>Chapters</p><ul><li><strong>00:00</strong> — Meet your host</li><li><strong>00:42</strong> — The setup</li><li><strong>01:24</strong> — What the article says</li><li><strong>02:06</strong> — The killer line</li><li><strong>02:48</strong> — The new way to think</li><li><strong>03:30</strong> — Concrete moves</li><li><strong>04:12</strong> — One thing to remember</li><li><strong>04:54</strong> — Where to find us</li><li><strong>05:36</strong> — Sign-off</li></ul><p><a href="https://growthalchemylab.com/blog/i-became-the-context-window">Read the full article →</a></p>]]>
      </content:encoded>
      <pubDate>Fri, 31 Jul 2026 01:17:34 -0700</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/bfb4d80f/c5e3b620.mp3" length="6101453" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:duration>379</itunes:duration>
      <itunes:summary>Luis and Maya unpack the hidden bottleneck in agent-heavy work: the human approval queue. The fix is less clever tooling, fewer harnesses, one queue, and a daily count of real decisions.</itunes:summary>
      <itunes:subtitle>Luis and Maya unpack the hidden bottleneck in agent-heavy work: the human approval queue. The fix is less clever tooling, fewer harnesses, one queue, and a daily count of real decisions.</itunes:subtitle>
      <itunes:keywords>product management, AI, tech, agentic, LLM</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Why Kimi K3 Paused New Subs — And What That Tells You</title>
      <itunes:episode>34</itunes:episode>
      <podcast:episode>34</podcast:episode>
      <itunes:title>Why Kimi K3 Paused New Subs — And What That Tells You</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">50fd00ea-f7c1-4191-b8b3-807b9509ab8f</guid>
      <link>https://share.transistor.fm/s/d64861e3</link>
      <description>
        <![CDATA[<p>Moonshot paused new Kimi K3 subscriptions 48 hours after launch because GPU demand pushed them to capacity. They chose reliability over growth.</p><p>The open weights drop July 27. For builders: stop treating your model choice as a permanent commitment. Wrap it behind an interface. Treat it as a config value.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/kimi-k3-the-pause-that-tells-you-everything">https://growthalchemylab.com/blog/kimi-k3-the-pause-that-tells-you-everything</a></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Moonshot paused new Kimi K3 subscriptions 48 hours after launch because GPU demand pushed them to capacity. They chose reliability over growth.</p><p>The open weights drop July 27. For builders: stop treating your model choice as a permanent commitment. Wrap it behind an interface. Treat it as a config value.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/kimi-k3-the-pause-that-tells-you-everything">https://growthalchemylab.com/blog/kimi-k3-the-pause-that-tells-you-everything</a></p>]]>
      </content:encoded>
      <pubDate>Mon, 20 Jul 2026 02:18:57 -0700</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/d64861e3/0d5c6f6e.mp3" length="7941806" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:duration>494</itunes:duration>
      <itunes:summary>Moonshot hit capacity in 48 hours. Google got punished for being slow. Open weights drop July 27. Here is what changes for builders shipping on top of these models.</itunes:summary>
      <itunes:subtitle>Moonshot hit capacity in 48 hours. Google got punished for being slow. Open weights drop July 27. Here is what changes for builders shipping on top of these models.</itunes:subtitle>
      <itunes:keywords>product management, AI, tech, agentic, LLM</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>What Happens to the S&amp;P 500 When AI Gets Cheaper Faster Than Data Centers Depreciate?</title>
      <itunes:episode>33</itunes:episode>
      <podcast:episode>33</podcast:episode>
      <itunes:title>What Happens to the S&amp;P 500 When AI Gets Cheaper Faster Than Data Centers Depreciate?</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">43620cd7-86fc-4be6-9179-27ca94516de4</guid>
      <link>https://share.transistor.fm/s/70c902c9</link>
      <description>
        <![CDATA[<p>Luis and Maya dig into the $700B hyperscaler capex bet and why falling AI model prices could leave a third of the S&amp;P 500 mispriced. The math is falsifiable — and the clock is already running.</p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis and Maya dig into the $700B hyperscaler capex bet and why falling AI model prices could leave a third of the S&amp;P 500 mispriced. The math is falsifiable — and the clock is already running.</p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 17 Jul 2026 21:00:13 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/70c902c9/cfae9857.mp3" length="5233311" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/APph-5NHLfz6_JA6cE1j0ghz2Wq2RYhc3pOEWxFad_0/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xNjRh/ODlhODhlMDYzNTJm/NTA4MzIwZjU1NjUy/NDM2Mi5qcGc.jpg"/>
      <itunes:duration>328</itunes:duration>
      <itunes:summary>Luis and Maya dig into the $700B hyperscaler capex bet and why falling AI model prices could leave a third of the S&amp;amp;P 500 mispriced. The math is falsifiable — and the clock is already running.</itunes:summary>
      <itunes:subtitle>Luis and Maya dig into the $700B hyperscaler capex bet and why falling AI model prices could leave a third of the S&amp;amp;P 500 mispriced. The math is falsifiable — and the clock is already running.</itunes:subtitle>
      <itunes:keywords>AI-economics,S&amp;P-500,capex-risk</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>OpenAI Model Guide: Stop Staring at the Picker</title>
      <itunes:episode>32</itunes:episode>
      <podcast:episode>32</podcast:episode>
      <itunes:title>OpenAI Model Guide: Stop Staring at the Picker</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">b45a85bd-602f-463b-a540-f325d8180886</guid>
      <link>https://share.transistor.fm/s/443c9781</link>
      <description>
        <![CDATA[<p>Luis and Maya cut through OpenAI's Sol/Terra/Luna model catalog with one operator rule: pick a default, escalate effort before model, and stop treating the picker like a menu.</p>
<p>Read the full article: <a href="https://growthalchemylab.com/blog/openai-model-guide-confused-choices">https://growthalchemylab.com/blog/openai-model-guide-confused-choices</a></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis and Maya cut through OpenAI's Sol/Terra/Luna model catalog with one operator rule: pick a default, escalate effort before model, and stop treating the picker like a menu.</p>
<p>Read the full article: <a href="https://growthalchemylab.com/blog/openai-model-guide-confused-choices">https://growthalchemylab.com/blog/openai-model-guide-confused-choices</a></p>]]>
      </content:encoded>
      <pubDate>Mon, 13 Jul 2026 15:02:21 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/443c9781/fa025caa.mp3" length="8654213" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/bB-Q6tdCZTpgTTWpZlQmmVqFlfxXrxiiApKtrVIdURg/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lODA4/YzcwNWU4MmUyMDRk/YTBmOWQwMzFkMDll/MGIxMC5qcGc.jpg"/>
      <itunes:duration>360</itunes:duration>
      <itunes:summary>Luis and Maya cut through OpenAI's Sol/Terra/Luna model catalog with one operator rule: pick a default, escalate effort before model, and stop treating the picker like a menu.</itunes:summary>
      <itunes:subtitle>Luis and Maya cut through OpenAI's Sol/Terra/Luna model catalog with one operator rule: pick a default, escalate effort before model, and stop treating the picker like a menu.</itunes:subtitle>
      <itunes:keywords>openai-models,ai-tooling,product-ops</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Has AGI Arrived? Send in the Misfits.</title>
      <itunes:episode>31</itunes:episode>
      <podcast:episode>31</podcast:episode>
      <itunes:title>Has AGI Arrived? Send in the Misfits.</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">bd8f5ef0-fb58-44c3-84ba-4dc6a960dd5b</guid>
      <link>https://share.transistor.fm/s/d524473f</link>
      <description>
        <![CDATA[<p>An $8 multi-agent website build beat a $105 solo build on accessibility — and it proves hallucination isn't solved, it's routed. Luis and Maya break down the org-chart model for trustworthy AI.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/has-agi-arrived-send-in-the-misfits">https://growthalchemylab.com/blog/has-agi-arrived-send-in-the-misfits</a></p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>An $8 multi-agent website build beat a $105 solo build on accessibility — and it proves hallucination isn't solved, it's routed. Luis and Maya break down the org-chart model for trustworthy AI.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/has-agi-arrived-send-in-the-misfits">https://growthalchemylab.com/blog/has-agi-arrived-send-in-the-misfits</a></p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Sun, 12 Jul 2026 14:25:15 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/d524473f/03b45aea.mp3" length="9067779" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/BBxFId4guh4DEXNkvMRFDB8NFj1ZXo_1jZTTkZ0SbXo/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xZTI2/OWMxN2VlMmVkZTA3/N2E0NTYwZWNjNGJj/NjcwMi5qcGc.jpg"/>
      <itunes:duration>376</itunes:duration>
      <itunes:summary>An $8 multi-agent website build beat a $105 solo build on accessibility — and it proves hallucination isn't solved, it's routed. Luis and Maya break down the org-chart model for trustworthy AI.</itunes:summary>
      <itunes:subtitle>An $8 multi-agent website build beat a $105 solo build on accessibility — and it proves hallucination isn't solved, it's routed. Luis and Maya break down the org-chart model for trustworthy AI.</itunes:subtitle>
      <itunes:keywords>multi-agent-systems,AI-hallucination,product-workflow</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Your Code Is Trash Anyway</title>
      <itunes:episode>27</itunes:episode>
      <podcast:episode>27</podcast:episode>
      <itunes:title>Your Code Is Trash Anyway</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">aee4ad21-12b9-4151-b2ff-8b848f76870d</guid>
      <link>https://share.transistor.fm/s/847399d9</link>
      <description>
        <![CDATA[<p>The production curve for generating code is steeper than understanding it. Teams that win store decisions, not commits—and specs are the moat.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>The production curve for generating code is steeper than understanding it. Teams that win store decisions, not commits—and specs are the moat.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 16:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/847399d9/b6f6bce8.mp3" length="7149234" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/d310R4BGKHFYTS7jgTIwZ0YWH4E1z0WBApefjbe_d5I/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hMGMw/MmYwOGVlMzIzNTE1/N2YzZThhY2I0OTQ5/ZTFlYi5qcGc.jpg"/>
      <itunes:duration>447</itunes:duration>
      <itunes:summary>The production curve for generating code is steeper than understanding it. Teams that win store decisions, not commits—and specs are the moat.</itunes:summary>
      <itunes:subtitle>The production curve for generating code is steeper than understanding it. Teams that win store decisions, not commits—and specs are the moat.</itunes:subtitle>
      <itunes:keywords>AI code generation,technical debt,specification-first,product management,software architecture</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Your Agents Have Amnesia — Stop Using Markdown!</title>
      <itunes:episode>26</itunes:episode>
      <podcast:episode>26</podcast:episode>
      <itunes:title>Your Agents Have Amnesia — Stop Using Markdown!</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">af22daba-2ab5-4108-a408-3b0b2c32c31e</guid>
      <link>https://share.transistor.fm/s/880f2597</link>
      <description>
        <![CDATA[<p>Why stuffing context into markdown files breaks production AI agents, and the six-layer memory architecture that actually works at scale.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Why stuffing context into markdown files breaks production AI agents, and the six-layer memory architecture that actually works at scale.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 14:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/880f2597/2c99ed73.mp3" length="5974351" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/kIiwfXRt0X9ctkVnbPezglVKFUSSBpvgKGJjkQufsrk/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hOGMz/ZWZkOWRiMDg2OTQz/ZjQ3M2U4NzJmOGZl/MmY5ZC5qcGc.jpg"/>
      <itunes:duration>374</itunes:duration>
      <itunes:summary>Why stuffing context into markdown files breaks production AI agents, and the six-layer memory architecture that actually works at scale.</itunes:summary>
      <itunes:subtitle>Why stuffing context into markdown files breaks production AI agents, and the six-layer memory architecture that actually works at scale.</itunes:subtitle>
      <itunes:keywords>AI agents,memory systems,architecture,production systems,SQLite,system design</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Why Agent Memory Needs an OS, Not a Vector Store</title>
      <itunes:episode>25</itunes:episode>
      <podcast:episode>25</podcast:episode>
      <itunes:title>Why Agent Memory Needs an OS, Not a Vector Store</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">cde19232-560a-4d46-940b-f6fbe97177bd</guid>
      <link>https://share.transistor.fm/s/bcecf713</link>
      <description>
        <![CDATA[<p>Production agents hit a wall around day 30: context drift, not retrieval, is the killer. Vector stores can't manage state across multi-agent workflows. The fix is treating memory like an operating system.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Production agents hit a wall around day 30: context drift, not retrieval, is the killer. Vector stores can't manage state across multi-agent workflows. The fix is treating memory like an operating system.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 12:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/bcecf713/19f766ee.mp3" length="5651687" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/6-PFooSJ8BagxHivKyQ5g3CEScGJeG32GfBJftULI0Q/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9jZjVh/OTRiZWU0YWMxOGE1/Mzg5OTA3MThkZTk5/ZjMyYi5qcGc.jpg"/>
      <itunes:duration>354</itunes:duration>
      <itunes:summary>Production agents hit a wall around day 30: context drift, not retrieval, is the killer. Vector stores can't manage state across multi-agent workflows. The fix is treating memory like an operating system.</itunes:summary>
      <itunes:subtitle>Production agents hit a wall around day 30: context drift, not retrieval, is the killer. Vector stores can't manage state across multi-agent workflows. The fix is treating memory like an operating system.</itunes:subtitle>
      <itunes:keywords>agent-memory,production-ai,state-management,vector-stores,agentic-workflows</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>When Not to Deploy an Agent</title>
      <itunes:episode>24</itunes:episode>
      <podcast:episode>24</podcast:episode>
      <itunes:title>When Not to Deploy an Agent</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">9868f625-bd82-494a-bd96-916f0b48c491</guid>
      <link>https://share.transistor.fm/s/e9c9e9a0</link>
      <description>
        <![CDATA[<p>Luis explores five conditions that should trigger a pause before deploying an AI agent—and why a queue, form, or policy often solves the problem faster than autonomy.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis explores five conditions that should trigger a pause before deploying an AI agent—and why a queue, form, or policy often solves the problem faster than autonomy.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 10:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/e9c9e9a0/1d99380e.mp3" length="4981280" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/vouZCXHOp41r5w6-8-Fyc5tBa7C0JJr5Iy2RtFubI7Y/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hMDgy/MTZkMjM4NTBkYjlh/NDIyNTI4M2M1Zjc3/NTliNC5qcGc.jpg"/>
      <itunes:duration>312</itunes:duration>
      <itunes:summary>Luis explores five conditions that should trigger a pause before deploying an AI agent—and why a queue, form, or policy often solves the problem faster than autonomy.</itunes:summary>
      <itunes:subtitle>Luis explores five conditions that should trigger a pause before deploying an AI agent—and why a queue, form, or policy often solves the problem faster than autonomy.</itunes:subtitle>
      <itunes:keywords>AI agents,product strategy,workflow automation,technical debt</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>What Broke When We Scaled to 17 Agents</title>
      <itunes:episode>23</itunes:episode>
      <podcast:episode>23</podcast:episode>
      <itunes:title>What Broke When We Scaled to 17 Agents</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">856a042b-5055-4882-bc84-b203da84b948</guid>
      <link>https://share.transistor.fm/s/6d3372f0</link>
      <description>
        <![CDATA[<p>Luis walks through five coordination failures that emerge when agent systems scale past single digits—memory contention, context bloat, skill drift, context corruption, and operator blindness. The fix: a memory OS layer that governs writes, gates context, standardizes skills, checkpoints state, and </p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis walks through five coordination failures that emerge when agent systems scale past single digits—memory contention, context bloat, skill drift, context corruption, and operator blindness. The fix: a memory OS layer that governs writes, gates context, standardizes skills, checkpoints state, and </p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 08:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/6d3372f0/a80a39b6.mp3" length="7119977" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/Elw0t-XaKvHCKb9DwrZzz6-XAXwG5fqwuMEfkqECN6w/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS84MGRl/OWViY2M2YzU1ODFm/NmRjZjM5YmI5ODE1/NWY1Yy5qcGc.jpg"/>
      <itunes:duration>445</itunes:duration>
      <itunes:summary>Luis walks through five coordination failures that emerge when agent systems scale past single digits—memory contention, context bloat, skill drift, context corruption, and operator blindness. The fix: a memory OS layer that governs writes, gates context, standardizes skills, checkpoints state, and </itunes:summary>
      <itunes:subtitle>Luis walks through five coordination failures that emerge when agent systems scale past single digits—memory contention, context bloat, skill drift, context corruption, and operator blindness. The fix: a memory OS layer that governs writes, gates context,</itunes:subtitle>
      <itunes:keywords>agent-systems,distributed-systems,coordination,scaling,observability</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The Trillion-Dollar Fork: Who Owns the Harness?</title>
      <itunes:episode>22</itunes:episode>
      <podcast:episode>22</podcast:episode>
      <itunes:title>The Trillion-Dollar Fork: Who Owns the Harness?</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">756f6885-96d1-435f-856c-c2c4090c44ca</guid>
      <link>https://share.transistor.fm/s/8e7e19b4</link>
      <description>
        <![CDATA[<p>OpenAI and Anthropic's IPO valuations hinge on owning the work layer above AI models—not just cheap tokens, but proprietary harnesses. We explore why context, memory, and workflow engineering are where real competitive advantage lives.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>OpenAI and Anthropic's IPO valuations hinge on owning the work layer above AI models—not just cheap tokens, but proprietary harnesses. We explore why context, memory, and workflow engineering are where real competitive advantage lives.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 06:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/8e7e19b4/565cf269.mp3" length="7830090" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/kLfaTmK-DJ-zaDBSSE2ws7AtnZbzqx8HKSBvkHS7U-w/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lZjgy/NDY2NGRmM2M5ZWM5/NjNjZjhlZTY2ZGZh/ZWM2YS5qcGc.jpg"/>
      <itunes:duration>490</itunes:duration>
      <itunes:summary>OpenAI and Anthropic's IPO valuations hinge on owning the work layer above AI models—not just cheap tokens, but proprietary harnesses. We explore why context, memory, and workflow engineering are where real competitive advantage lives.</itunes:summary>
      <itunes:subtitle>OpenAI and Anthropic's IPO valuations hinge on owning the work layer above AI models—not just cheap tokens, but proprietary harnesses. We explore why context, memory, and workflow engineering are where real competitive advantage lives.</itunes:subtitle>
      <itunes:keywords>ai-strategy,product-infrastructure,competitive-moat,enterprise-ai,harness-engineering</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Three things broke this week. None of them were the model.</title>
      <itunes:episode>21</itunes:episode>
      <podcast:episode>21</podcast:episode>
      <itunes:title>Three things broke this week. None of them were the model.</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">4e7d3f89-0ab2-44fc-bf51-f07726e5e568</guid>
      <link>https://share.transistor.fm/s/5cbbb531</link>
      <description>
        <![CDATA[<p>Palantir's CEO ranted about AI pricing, a ransomware agent proved harness engineering matters more than the model, and Mem0 benchmarked the memory layer nobody is paying attention to. The real fight isn't about weights—it's about what sits underneath.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Palantir's CEO ranted about AI pricing, a ransomware agent proved harness engineering matters more than the model, and Mem0 benchmarked the memory layer nobody is paying attention to. The real fight isn't about weights—it's about what sits underneath.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 04:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/5cbbb531/da661cec.mp3" length="7199807" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/CNJteT-GCKnwGwb-1yS6xfNoUopQSYlSknXZmRN_CTA/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS85ZWQ5/YjlmYmE3MWE3MjJh/ZGUwN2JhOGJkZDM4/ZmUzOC5qcGc.jpg"/>
      <itunes:duration>450</itunes:duration>
      <itunes:summary>Palantir's CEO ranted about AI pricing, a ransomware agent proved harness engineering matters more than the model, and Mem0 benchmarked the memory layer nobody is paying attention to. The real fight isn't about weights—it's about what sits underneath.</itunes:summary>
      <itunes:subtitle>Palantir's CEO ranted about AI pricing, a ransomware agent proved harness engineering matters more than the model, and Mem0 benchmarked the memory layer nobody is paying attention to. The real fight isn't about weights—it's about what sits underneath.</itunes:subtitle>
      <itunes:keywords>AI agents,infrastructure,memory architecture,security,product strategy</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The deployment PM is dead</title>
      <itunes:episode>20</itunes:episode>
      <podcast:episode>20</podcast:episode>
      <itunes:title>The deployment PM is dead</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">2f6d3346-6507-48e3-9f6c-4c31eada08c3</guid>
      <link>https://share.transistor.fm/s/5437553c</link>
      <description>
        <![CDATA[<p>The job description we wrote for PMs in 2019 doesn't match the work in 2026. Luis breaks down what's actually required to survive the AI era.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>The job description we wrote for PMs in 2019 doesn't match the work in 2026. Luis breaks down what's actually required to survive the AI era.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 02:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/5437553c/9b04cfea.mp3" length="5301019" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/Xf8pCNrsyDrjTCYa-ECj0bTUvCY5lEzRH-_TSdwHNJk/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8wOTE3/ZGZlMjIwM2QwZjZi/MzJkYzJiN2FiMTJl/ZDhkMy5qcGc.jpg"/>
      <itunes:duration>332</itunes:duration>
      <itunes:summary>The job description we wrote for PMs in 2019 doesn't match the work in 2026. Luis breaks down what's actually required to survive the AI era.</itunes:summary>
      <itunes:subtitle>The job description we wrote for PMs in 2019 doesn't match the work in 2026. Luis breaks down what's actually required to survive the AI era.</itunes:subtitle>
      <itunes:keywords>product-management,AI,agent-design,deployment,career-evolution</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The Audit Trail Is the Product</title>
      <itunes:episode>19</itunes:episode>
      <podcast:episode>19</podcast:episode>
      <itunes:title>The Audit Trail Is the Product</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">4d50624c-40f6-440c-8b81-d057c130b087</guid>
      <link>https://share.transistor.fm/s/f648e050</link>
      <description>
        <![CDATA[<p>Why the audit trail—not the agent's output—is what actually matters in production. Design it as a user interface, and autonomy becomes defensible.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Why the audit trail—not the agent's output—is what actually matters in production. Design it as a user interface, and autonomy becomes defensible.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Fri, 10 Jul 2026 00:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/f648e050/5125163c.mp3" length="4572098" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/XSjcoSDZR3pLyJPFrLk5N4sGkxGzGxfsjtIXRxLKqqQ/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lM2Q0/ODA5YzMwMTdkYWI2/ZTQzYzQ0ZmE0ODUx/NjFiYy5qcGc.jpg"/>
      <itunes:duration>286</itunes:duration>
      <itunes:summary>Why the audit trail—not the agent's output—is what actually matters in production. Design it as a user interface, and autonomy becomes defensible.</itunes:summary>
      <itunes:subtitle>Why the audit trail—not the agent's output—is what actually matters in production. Design it as a user interface, and autonomy becomes defensible.</itunes:subtitle>
      <itunes:keywords>AI agents,product design,operational trust,audit logging</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The AI Strategy Slide Deck Is Dead</title>
      <itunes:episode>18</itunes:episode>
      <podcast:episode>18</podcast:episode>
      <itunes:title>The AI Strategy Slide Deck Is Dead</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">46b36a46-8043-4db0-80e7-c99f69f2ccde</guid>
      <link>https://share.transistor.fm/s/057e9191</link>
      <description>
        <![CDATA[<p>Luis argues that static AI strategy decks are obsolete. The future is live orchestration graphs where agents execute workflows in real time while humans design the feedback loop.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis argues that static AI strategy decks are obsolete. The future is live orchestration graphs where agents execute workflows in real time while humans design the feedback loop.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 22:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/057e9191/7f9631d1.mp3" length="4406168" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/xn4xqkLsCbdGsV5OYmfLXQv6Zt2wifJedOvvmp03d3Y/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80NDRl/OTk3NDEwMTNlYjZm/MGI3MGUzYjQwMGM1/MTFlYy5qcGc.jpg"/>
      <itunes:duration>276</itunes:duration>
      <itunes:summary>Luis argues that static AI strategy decks are obsolete. The future is live orchestration graphs where agents execute workflows in real time while humans design the feedback loop.</itunes:summary>
      <itunes:subtitle>Luis argues that static AI strategy decks are obsolete. The future is live orchestration graphs where agents execute workflows in real time while humans design the feedback loop.</itunes:subtitle>
      <itunes:keywords>AI strategy,product management,agentic AI,operating models</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The agentic GitHub stack is forming</title>
      <itunes:episode>17</itunes:episode>
      <podcast:episode>17</podcast:episode>
      <itunes:title>The agentic GitHub stack is forming</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">12d0bff2-6112-45a5-a512-bd90b472443d</guid>
      <link>https://share.transistor.fm/s/f4630d25</link>
      <description>
        <![CDATA[<p>Five product layers are crystallizing in open-source AI agent repos right now. Learn which ones matter and how to borrow the patterns before they harden into expensive platform defaults.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Five product layers are crystallizing in open-source AI agent repos right now. Learn which ones matter and how to borrow the patterns before they harden into expensive platform defaults.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 20:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/f4630d25/1ab9ef9c.mp3" length="4616402" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/yjONyzDJByzDRKS0zpjmF2Q_U3m4PwM4ekHem2Qhe3M/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xMDMz/YzNhOWM2ODJkODhl/NTZkMjQxYTliNWUx/NjRjMy5qcGc.jpg"/>
      <itunes:duration>289</itunes:duration>
      <itunes:summary>Five product layers are crystallizing in open-source AI agent repos right now. Learn which ones matter and how to borrow the patterns before they harden into expensive platform defaults.</itunes:summary>
      <itunes:subtitle>Five product layers are crystallizing in open-source AI agent repos right now. Learn which ones matter and how to borrow the patterns before they harden into expensive platform defaults.</itunes:subtitle>
      <itunes:keywords>AI agents,GitHub,product architecture,agentic workflow,open source</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The agent memory wall</title>
      <itunes:episode>16</itunes:episode>
      <podcast:episode>16</podcast:episode>
      <itunes:title>The agent memory wall</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">a842e8ad-cbad-45ec-a7d3-2deb0888064d</guid>
      <link>https://share.transistor.fm/s/58cc1ea0</link>
      <description>
        <![CDATA[<p>Every AI agent in production hits the same wall: they start from zero every Monday with no memory of past decisions. Luis explores why memory and governance is the one unsolved layer of the agentic stack—and what governed memory actually requires.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Every AI agent in production hits the same wall: they start from zero every Monday with no memory of past decisions. Luis explores why memory and governance is the one unsolved layer of the agentic stack—and what governed memory actually requires.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 18:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/58cc1ea0/de25eb99.mp3" length="5867772" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/RMGsDd6UesIhDvvyoI3hcsQkCX6_TW8PIGXeY_m-ack/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lNmY1/NzA2ZmYxZTk5ODg1/NzkzYWIxYzVkYmJj/OGE5Yy5qcGc.jpg"/>
      <itunes:duration>367</itunes:duration>
      <itunes:summary>Every AI agent in production hits the same wall: they start from zero every Monday with no memory of past decisions. Luis explores why memory and governance is the one unsolved layer of the agentic stack—and what governed memory actually requires.</itunes:summary>
      <itunes:subtitle>Every AI agent in production hits the same wall: they start from zero every Monday with no memory of past decisions. Luis explores why memory and governance is the one unsolved layer of the agentic stack—and what governed memory actually requires.</itunes:subtitle>
      <itunes:keywords>AI agents,memory systems,production challenges,governance,agent architecture</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Stop Wasting Time Writing Better Prompts</title>
      <itunes:episode>15</itunes:episode>
      <podcast:episode>15</podcast:episode>
      <itunes:title>Stop Wasting Time Writing Better Prompts</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">c65ec561-0730-45f8-8502-4be092eab4f1</guid>
      <link>https://share.transistor.fm/s/3966d40e</link>
      <description>
        <![CDATA[<p>Prompt engineering is dead. The winning move is prompt systems—evolutionary optimization, self-refinement loops, harness engineering, and spec-driven contracts. Here's how to build them.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Prompt engineering is dead. The winning move is prompt systems—evolutionary optimization, self-refinement loops, harness engineering, and spec-driven contracts. Here's how to build them.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 16:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/3966d40e/97a67450.mp3" length="7126665" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/Dkvw9J5sH9Y1lVz_cvarJQ-MyfrrtcSEg9e5YIymgb4/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83ZGFi/NzRkMDFhYzMwZTRh/NzA1NjFjOTAxOWE3/OGYxNS5qcGc.jpg"/>
      <itunes:duration>446</itunes:duration>
      <itunes:summary>Prompt engineering is dead. The winning move is prompt systems—evolutionary optimization, self-refinement loops, harness engineering, and spec-driven contracts. Here's how to build them.</itunes:summary>
      <itunes:subtitle>Prompt engineering is dead. The winning move is prompt systems—evolutionary optimization, self-refinement loops, harness engineering, and spec-driven contracts. Here's how to build them.</itunes:subtitle>
      <itunes:keywords>AI systems,prompt engineering,product development,LLM architecture,optimization</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The NOC Console for Agent Teams</title>
      <itunes:episode>14</itunes:episode>
      <podcast:episode>14</podcast:episode>
      <itunes:title>The NOC Console for Agent Teams</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">166e09c8-0f68-43d9-85db-048aed705e50</guid>
      <link>https://share.transistor.fm/s/600c901d</link>
      <description>
        <![CDATA[<p>When you're running multiple agents in production, you need more than a dashboard—you need a real operator console. Luis breaks down what that looks like and why it matters.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>When you're running multiple agents in production, you need more than a dashboard—you need a real operator console. Luis breaks down what that looks like and why it matters.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 14:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/600c901d/0b50dea2.mp3" length="5333620" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/9B2PNTTGedh3TcFBYMvjAL6_Wq9NlvGTqUJ-_j5U5xw/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS81NmIz/MmEwMGVlOWRmNGMw/ZTNmYzEwZmNjZTNh/YmZjOS5qcGc.jpg"/>
      <itunes:duration>334</itunes:duration>
      <itunes:summary>When you're running multiple agents in production, you need more than a dashboard—you need a real operator console. Luis breaks down what that looks like and why it matters.</itunes:summary>
      <itunes:subtitle>When you're running multiple agents in production, you need more than a dashboard—you need a real operator console. Luis breaks down what that looks like and why it matters.</itunes:subtitle>
      <itunes:keywords>agent-infrastructure,operational-visibility,production-systems,memroos,control-planes</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Most PMs Won't Become Agent Orchestrators. They'll Become Obsolete.</title>
      <itunes:episode>13</itunes:episode>
      <podcast:episode>13</podcast:episode>
      <itunes:title>Most PMs Won't Become Agent Orchestrators. They'll Become Obsolete.</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">a73fa1e6-666b-4694-9a33-045e8e2e82e3</guid>
      <link>https://share.transistor.fm/s/c0fd1db6</link>
      <description>
        <![CDATA[<p>Luis argues the comfortable narrative about PMs evolving into agent orchestrators is false. The real trend: agentic AI will automate the PM role itself, leaving only domain experts and compliance checkpoints.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis argues the comfortable narrative about PMs evolving into agent orchestrators is false. The real trend: agentic AI will automate the PM role itself, leaving only domain experts and compliance checkpoints.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 12:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/c0fd1db6/f55cb24f.mp3" length="7176820" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/RjNvOlTlarhmvnO3Y8Yx8aVoS_Cka3Hf_iSFGNxQgQo/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNzc3/ZDMxNjBjMDdkNmM0/NWRjMTIyOTBlZGZh/NGM5Yi5qcGc.jpg"/>
      <itunes:duration>449</itunes:duration>
      <itunes:summary>Luis argues the comfortable narrative about PMs evolving into agent orchestrators is false. The real trend: agentic AI will automate the PM role itself, leaving only domain experts and compliance checkpoints.</itunes:summary>
      <itunes:subtitle>Luis argues the comfortable narrative about PMs evolving into agent orchestrators is false. The real trend: agentic AI will automate the PM role itself, leaving only domain experts and compliance checkpoints.</itunes:subtitle>
      <itunes:keywords>product management,agentic AI,career strategy,AI automation,future of work</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The Harness Eats the Prompt (Every Time)</title>
      <itunes:episode>12</itunes:episode>
      <podcast:episode>12</podcast:episode>
      <itunes:title>The Harness Eats the Prompt (Every Time)</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">983e75ae-64af-4442-bc4a-0b45fc932dd3</guid>
      <link>https://share.transistor.fm/s/df3d0f5c</link>
      <description>
        <![CDATA[<p>A new paper proves what product builders have suspected: your system prompt is the least valuable part of your AI harness. The real wins come from tool architecture, middleware, and memory structure.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>A new paper proves what product builders have suspected: your system prompt is the least valuable part of your AI harness. The real wins come from tool architecture, middleware, and memory structure.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 10:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/df3d0f5c/efab3b12.mp3" length="6288238" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/ufcWgLGkgVXaz25psgSyvR4sjxKQlEPtq3gqtGNmvUQ/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yMTc2/ODkyZjVlOWM4MzBm/OTljODljZWE3NTRh/NWUzMy5qcGc.jpg"/>
      <itunes:duration>393</itunes:duration>
      <itunes:summary>A new paper proves what product builders have suspected: your system prompt is the least valuable part of your AI harness. The real wins come from tool architecture, middleware, and memory structure.</itunes:summary>
      <itunes:subtitle>A new paper proves what product builders have suspected: your system prompt is the least valuable part of your AI harness. The real wins come from tool architecture, middleware, and memory structure.</itunes:subtitle>
      <itunes:keywords>prompt-engineering,ai-product,harness-engineering,system-design,agentic-systems</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Google I/O 2026 was about distribution</title>
      <itunes:episode>11</itunes:episode>
      <podcast:episode>11</podcast:episode>
      <itunes:title>Google I/O 2026 was about distribution</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">71bb07e3-a71b-4504-bec8-809973764cac</guid>
      <link>https://share.transistor.fm/s/2fbfc38a</link>
      <description>
        <![CDATA[<p>Google didn't release a smarter model at I/O 2026—it turned 12+ products into agent runtimes. The real story is distribution dominance, not AI capability.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Google didn't release a smarter model at I/O 2026—it turned 12+ products into agent runtimes. The real story is distribution dominance, not AI capability.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 08:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/2fbfc38a/bfdb7ba2.mp3" length="5768715" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/G6ZX09LQfQw9ZMSFwGiRbZji2UTbGNthXo0zFB-Cl5o/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mZmMy/ZmRmOTlhYTM0OTk3/OGFiYzVhOWNiOTE3/YTFiNS5qcGc.jpg"/>
      <itunes:duration>361</itunes:duration>
      <itunes:summary>Google didn't release a smarter model at I/O 2026—it turned 12+ products into agent runtimes. The real story is distribution dominance, not AI capability.</itunes:summary>
      <itunes:subtitle>Google didn't release a smarter model at I/O 2026—it turned 12+ products into agent runtimes. The real story is distribution dominance, not AI capability.</itunes:subtitle>
      <itunes:keywords>AI agents,Google,product strategy,distribution,AI infrastructure</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Eval design before agent design</title>
      <itunes:episode>10</itunes:episode>
      <podcast:episode>10</podcast:episode>
      <itunes:title>Eval design before agent design</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">0c790691-a8c6-4246-a3f5-f86254d35362</guid>
      <link>https://share.transistor.fm/s/f9c2f802</link>
      <description>
        <![CDATA[<p>The cheapest agent improvement happens before you build it. Write your eval first—it's the product spec that prevents plausible-but-untrustworthy outputs.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>The cheapest agent improvement happens before you build it. Write your eval first—it's the product spec that prevents plausible-but-untrustworthy outputs.</p>
<p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 06:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/f9c2f802/f33ad0db.mp3" length="4919004" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/VQbnS90OLCx4nuwUQuZR1xXT-BdZ-HxDXhkRNVDwoRM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83NzU3/Y2E4NDM1NTJiYTQ2/ZmVlNTAxZWVkOGQ0/MTU5OS5qcGc.jpg"/>
      <itunes:duration>308</itunes:duration>
      <itunes:summary>The cheapest agent improvement happens before you build it. Write your eval first—it's the product spec that prevents plausible-but-untrustworthy outputs.</itunes:summary>
      <itunes:subtitle>The cheapest agent improvement happens before you build it. Write your eval first—it's the product spec that prevents plausible-but-untrustworthy outputs.</itunes:subtitle>
      <itunes:keywords>agent-design,eval-design,product-specs,ai-systems,prompt-engineering</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Build, Buy, Borrow, Hire, or Wait? The AI Investment Framework</title>
      <itunes:episode>9</itunes:episode>
      <podcast:episode>9</podcast:episode>
      <itunes:title>Build, Buy, Borrow, Hire, or Wait? The AI Investment Framework</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">ebc25238-fe47-4dc6-9a02-ffce86749f86</guid>
      <link>https://share.transistor.fm/s/1ced3f56</link>
      <description>
        <![CDATA[<p>Your board is split on AI strategy. Luis breaks down the five investment motions—build, buy, borrow, hire, wait—and gives you the framework to pick the right one for each workflow.</p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Your board is split on AI strategy. Luis breaks down the five investment motions—build, buy, borrow, hire, wait—and gives you the framework to pick the right one for each workflow.</p><p><em>This episode is in DRAFT and has not been published yet.</em></p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 04:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/1ced3f56/a815c9ae.mp3" length="6119383" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/aKTDyh4ZKxnlSaRpZH96H8z_HnsrsRRHqorNzxZTjg8/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83ZjI1/ZTI2YjhiZGVmZWFm/ZDYwZTljMzZjMzU1/NGNlNS5qcGc.jpg"/>
      <itunes:duration>383</itunes:duration>
      <itunes:summary>Your board is split on AI strategy. Luis breaks down the five investment motions—build, buy, borrow, hire, wait—and gives you the framework to pick the right one for each workflow.</itunes:summary>
      <itunes:subtitle>Your board is split on AI strategy. Luis breaks down the five investment motions—build, buy, borrow, hire, wait—and gives you the framework to pick the right one for each workflow.</itunes:subtitle>
      <itunes:keywords>AI strategy,capital allocation,build vs buy,enterprise AI,decision-making</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Software is Dead. Long Live Services.</title>
      <itunes:episode>8</itunes:episode>
      <podcast:episode>8</podcast:episode>
      <itunes:title>Software is Dead. Long Live Services.</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">4dede541-e38a-4604-a113-bdfe2dbc5490</guid>
      <link>https://share.transistor.fm/s/33368dff</link>
      <description>
        <![CDATA[<p>Three startups shipped on schedule and hit milestones—then quietly vanished. The real moat isn't code; it's the relationship you build with customers.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/software-is-dead-long-live-services">https://growthalchemylab.com/blog/software-is-dead-long-live-services</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Three startups shipped on schedule and hit milestones—then quietly vanished. The real moat isn't code; it's the relationship you build with customers.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/software-is-dead-long-live-services">https://growthalchemylab.com/blog/software-is-dead-long-live-services</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 02:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/33368dff/c7f6c2b6.mp3" length="4996012" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/iWTQEvq0hqnWqUBc557EgpgJLQsg-qlpwmv-CAvBaA4/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mZjQ3/OWI3OWU5NjU5MWEz/NGE5MmEyYmE1NDQ5/NjIyOC5qcGc.jpg"/>
      <itunes:duration>310</itunes:duration>
      <itunes:summary>Three startups shipped on schedule and hit milestones—then quietly vanished. The real moat isn't code; it's the relationship you build with customers.</itunes:summary>
      <itunes:subtitle>Three startups shipped on schedule and hit milestones—then quietly vanished. The real moat isn't code; it's the relationship you build with customers.</itunes:subtitle>
      <itunes:keywords>product-strategy,startup-survival,customer-centricity,moats,services-vs-software</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The Silent Killer in AI Agent Workflows: Context Drift</title>
      <itunes:episode>7</itunes:episode>
      <podcast:episode>7</podcast:episode>
      <itunes:title>The Silent Killer in AI Agent Workflows: Context Drift</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">09352a4e-24ef-406c-9793-d31832390344</guid>
      <link>https://share.transistor.fm/s/0d3260b1</link>
      <description>
        <![CDATA[<p>Most agent failures aren't bugs—they're silent context drift happening after step five. Luis Calderon reveals why vector memory fails, and what actually fixes it.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/the-memory-failure-i-keep-seeing-in-agent-stacks">https://growthalchemylab.com/blog/the-memory-failure-i-keep-seeing-in-agent-stacks</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Most agent failures aren't bugs—they're silent context drift happening after step five. Luis Calderon reveals why vector memory fails, and what actually fixes it.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/the-memory-failure-i-keep-seeing-in-agent-stacks">https://growthalchemylab.com/blog/the-memory-failure-i-keep-seeing-in-agent-stacks</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </content:encoded>
      <pubDate>Thu, 09 Jul 2026 00:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/0d3260b1/1249c55d.mp3" length="4901857" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/pAmI783z0E2j9lq65mbzbQv5D5Vw4n-aAJUeUXzDPjs/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS81ZjJj/OWViNjAxY2IwZTZj/NmE1NzRlNjU2MmY3/NzNiYy5qcGc.jpg"/>
      <itunes:duration>304</itunes:duration>
      <itunes:summary>Most agent failures aren't bugs—they're silent context drift happening after step five. Luis Calderon reveals why vector memory fails, and what actually fixes it.</itunes:summary>
      <itunes:subtitle>Most agent failures aren't bugs—they're silent context drift happening after step five. Luis Calderon reveals why vector memory fails, and what actually fixes it.</itunes:subtitle>
      <itunes:keywords>AI agents,context drift,production AI,memory management,multi-step workflows</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The Five Breaks: Where Multi-Agent Systems Actually Fail</title>
      <itunes:episode>6</itunes:episode>
      <podcast:episode>6</podcast:episode>
      <itunes:title>The Five Breaks: Where Multi-Agent Systems Actually Fail</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">539fd412-b67e-4780-bd7b-08014cf93879</guid>
      <link>https://share.transistor.fm/s/92139d79</link>
      <description>
        <![CDATA[<p>Luis Calderon maps the four failure modes that kill multi-agent systems before launch—and the fifth that breaks them in production. Most teams only fix the first three.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/the-four-places-multi-agent-systems-break">https://growthalchemylab.com/blog/the-four-places-multi-agent-systems-break</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Luis Calderon maps the four failure modes that kill multi-agent systems before launch—and the fifth that breaks them in production. Most teams only fix the first three.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/the-four-places-multi-agent-systems-break">https://growthalchemylab.com/blog/the-four-places-multi-agent-systems-break</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </content:encoded>
      <pubDate>Wed, 08 Jul 2026 22:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/92139d79/773e2a86.mp3" length="6011860" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/9JkaOmQle6QVUMOus2yt9IVE4Fi_ZBiOW2yPu1nsXko/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9iMGFi/ZmVlMmE5ODkyODIz/NTgyYWQwMzc4N2Vi/ODUyMy5qcGc.jpg"/>
      <itunes:duration>374</itunes:duration>
      <itunes:summary>Luis Calderon maps the four failure modes that kill multi-agent systems before launch—and the fifth that breaks them in production. Most teams only fix the first three.</itunes:summary>
      <itunes:subtitle>Luis Calderon maps the four failure modes that kill multi-agent systems before launch—and the fifth that breaks them in production. Most teams only fix the first three.</itunes:subtitle>
      <itunes:keywords>multi-agent-systems,AI-reliability,system-design,failure-modes,observability</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>The 2 AM Write That Changed Everything: Building Approval Gates for Autonomous Agents</title>
      <itunes:episode>5</itunes:episode>
      <podcast:episode>5</podcast:episode>
      <itunes:title>The 2 AM Write That Changed Everything: Building Approval Gates for Autonomous Agents</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">9db616b6-5c1f-41de-ac5a-5631d873e95d</guid>
      <link>https://share.transistor.fm/s/4c96a163</link>
      <description>
        <![CDATA[<p>When a single blocked write action prevented disaster, one team learned that strategic approval gates—not blanket permissions—unlock true agent autonomy while keeping humans in control.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/we-blocked-one-write-action">https://growthalchemylab.com/blog/we-blocked-one-write-action</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>When a single blocked write action prevented disaster, one team learned that strategic approval gates—not blanket permissions—unlock true agent autonomy while keeping humans in control.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/we-blocked-one-write-action">https://growthalchemylab.com/blog/we-blocked-one-write-action</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </content:encoded>
      <pubDate>Wed, 08 Jul 2026 20:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/4c96a163/3d60f170.mp3" length="6795635" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/rTVMaGMcmwnsos-4jsyGQmLkFCup3kWa004uHt8kXNQ/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9hYjUx/ZWFiOTA2MDRmODU2/ZjA5YTNkNTQwZDE3/ZDJhNy5qcGc.jpg"/>
      <itunes:duration>422</itunes:duration>
      <itunes:summary>When a single blocked write action prevented disaster, one team learned that strategic approval gates—not blanket permissions—unlock true agent autonomy while keeping humans in control.</itunes:summary>
      <itunes:subtitle>When a single blocked write action prevented disaster, one team learned that strategic approval gates—not blanket permissions—unlock true agent autonomy while keeping humans in control.</itunes:subtitle>
      <itunes:keywords>autonomous-agents,AI-safety,approval-systems,workflow-automation,trust-and-control</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Why Enterprise AI Projects Take 12 Months to Ship (When the Code Takes 2 Weeks)</title>
      <itunes:episode>4</itunes:episode>
      <podcast:episode>4</podcast:episode>
      <itunes:title>Why Enterprise AI Projects Take 12 Months to Ship (When the Code Takes 2 Weeks)</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">0b6aca61-9613-4d9b-ad80-80fd6725e1d8</guid>
      <link>https://share.transistor.fm/s/15093e77</link>
      <description>
        <![CDATA[<p>Accenture built an AI agent in two weeks but took twelve months to ship it. The bottleneck wasn't technology—it was organizational. We explore the five tensions that predict whether enterprise agentic projects survive.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/enterprise-agentic-projects-doomed">https://growthalchemylab.com/blog/enterprise-agentic-projects-doomed</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Accenture built an AI agent in two weeks but took twelve months to ship it. The bottleneck wasn't technology—it was organizational. We explore the five tensions that predict whether enterprise agentic projects survive.</p><p>Read the full article: <a href="https://growthalchemylab.com/blog/enterprise-agentic-projects-doomed">https://growthalchemylab.com/blog/enterprise-agentic-projects-doomed</a></p><p>This episode is in DRAFT and has not been published yet.</p>]]>
      </content:encoded>
      <pubDate>Wed, 08 Jul 2026 18:00:00 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/15093e77/a786c033.mp3" length="5840259" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/aSv5cXIxKLOL_5lzEMWeixUF1sPzQifp60-dCUEUbk8/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80YTQz/NjJmZjYzNDU1NWE3/OGNhNTQ5ODEyMmYz/NDYxYS5qcGc.jpg"/>
      <itunes:duration>363</itunes:duration>
      <itunes:summary>Accenture built an AI agent in two weeks but took twelve months to ship it. The bottleneck wasn't technology—it was organizational. We explore the five tensions that predict whether enterprise agentic projects survive.</itunes:summary>
      <itunes:subtitle>Accenture built an AI agent in two weeks but took twelve months to ship it. The bottleneck wasn't technology—it was organizational. We explore the five tensions that predict whether enterprise agentic projects survive.</itunes:subtitle>
      <itunes:keywords>enterprise-ai,organizational-bottlenecks,ai-governance,product-leadership,ai-operations</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Your Code Is Trash Anyway—And That's the Whole Point</title>
      <itunes:episode>3</itunes:episode>
      <podcast:episode>3</podcast:episode>
      <itunes:title>Your Code Is Trash Anyway—And That's the Whole Point</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">f7e9956e-42bf-444a-a97f-a8c7a7e509a0</guid>
      <link>https://share.transistor.fm/s/ade80f97</link>
      <description>
        <![CDATA[<p><strong>Your Code Is Trash Anyway—And That's the Whole Point</strong></p><p>Short, sharp take on why specs beat prompts, models rewrite everything anyway, and product teams that store decisions—not code—are the ones who win.</p><p>Your code is going to be rewritten anyway. Models regenerate it. The next engineer rewrites it. Six months from now, nobody remembers why any decision was made. So why are you treating the code as the artifact?</p><p>This episode reframes how product teams should think about AI-generated output. The real leverage is in the <em>spec</em>, the <em>decision</em>, the <em>reasoning</em> — not the code itself. Slowest layer wins. Store the why, not the what.</p><p>Three moves you can apply this week</p><ol><li><strong>Every PR links to a decision</strong>, not a Jira card. One paragraph explaining why this code exists.</li><li><strong>Review the spec, not the code</strong>. The code is now free. The expensive thing is the human judgment behind it.</li><li><strong>Store reasoning where it's searchable</strong>. Six months from now, "read the code" is already a failure.</li></ol><p>Where to find more</p><ul><li><a href="https://growthalchemylab.com"><strong>Growth Alchemy Lab</strong></a> — short, opinionated takes on AI in product work, published every Monday.</li><li><a href="https://contextuallyaware.com"><strong>Contextually Aware</strong></a> — frameworks, code, and conversations with teams shipping AI products in the messy middle.</li></ul><p>Send this to the person on your team who's still arguing about code review nits while the spec is the bottleneck.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>Your Code Is Trash Anyway—And That's the Whole Point</strong></p><p>Short, sharp take on why specs beat prompts, models rewrite everything anyway, and product teams that store decisions—not code—are the ones who win.</p><p>Your code is going to be rewritten anyway. Models regenerate it. The next engineer rewrites it. Six months from now, nobody remembers why any decision was made. So why are you treating the code as the artifact?</p><p>This episode reframes how product teams should think about AI-generated output. The real leverage is in the <em>spec</em>, the <em>decision</em>, the <em>reasoning</em> — not the code itself. Slowest layer wins. Store the why, not the what.</p><p>Three moves you can apply this week</p><ol><li><strong>Every PR links to a decision</strong>, not a Jira card. One paragraph explaining why this code exists.</li><li><strong>Review the spec, not the code</strong>. The code is now free. The expensive thing is the human judgment behind it.</li><li><strong>Store reasoning where it's searchable</strong>. Six months from now, "read the code" is already a failure.</li></ol><p>Where to find more</p><ul><li><a href="https://growthalchemylab.com"><strong>Growth Alchemy Lab</strong></a> — short, opinionated takes on AI in product work, published every Monday.</li><li><a href="https://contextuallyaware.com"><strong>Contextually Aware</strong></a> — frameworks, code, and conversations with teams shipping AI products in the messy middle.</li></ul><p>Send this to the person on your team who's still arguing about code review nits while the spec is the bottleneck.</p>]]>
      </content:encoded>
      <pubDate>Tue, 07 Jul 2026 03:29:37 -0700</pubDate>
      <author>Contextually Aware</author>
      <enclosure url="https://media.transistor.fm/ade80f97/a8f1cd64.mp3" length="5908768" type="audio/mpeg"/>
      <itunes:author>Contextually Aware</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/8sInb4_-Ag0_FEbBkiDXkPB2QJKqUhlpEeXwS0u8meM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83YjVl/YjZiNzQyOTgzM2M2/NTczYzViNGQ5MjBh/YzIwYS5qcGc.jpg"/>
      <itunes:duration>367</itunes:duration>
      <itunes:summary>Short, sharp take on why specs beat prompts, models rewrite everything anyway, and product teams that store decisions—not code—are the ones who win.</itunes:summary>
      <itunes:subtitle>Short, sharp take on why specs beat prompts, models rewrite everything anyway, and product teams that store decisions—not code—are the ones who win.</itunes:subtitle>
      <itunes:keywords>AI,product-strategy,specs-vs-prompts,context-aware</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/ade80f97/transcript.txt" type="text/plain"/>
    </item>
    <item>
      <title>Context Engineering: What Every PM Building AI Needs to Know</title>
      <itunes:episode>2</itunes:episode>
      <podcast:episode>2</podcast:episode>
      <itunes:title>Context Engineering: What Every PM Building AI Needs to Know</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">f2a9d28d-7ff4-48c3-b6a7-88eb09fc2b1a</guid>
      <link>https://share.transistor.fm/s/07a139e1</link>
      <description>
        <![CDATA[<p>The best prompt engineer I know told me he stopped writing prompts.</p><p>He said: "Prompts are maybe 5% of what makes AI actually useful. The other 95%? It's everything the model sees before you even ask a question."</p><p>If you're building AI features and still obsessing over prompt wording, you're optimizing the wrong thing.</p><p>In this episode, I break down context engineering—what it is, where the term comes from, and how product managers can own the context window without writing code.</p><p>**What you'll learn:**</p><p>- Why "know your user" is the foundation of context engineering<br>- The 3 types of retrieval: keyword, semantic, and graph RAG<br>- Why more context actually hurts performance (context rot)<br>- How to build evals that learn from future outcomes<br>- 5 actionable homework items you can start today</p><p>**People mentioned:**</p><p>- Simon Willison (AI Engineer, Creator of Datasette)<br>- Kevin Weil (CPO at OpenAI)</p><p>**Key terms:**</p><p>- Context window<br>- RAG (Retrieval Augmented Generation)<br>- Semantic search / Vector databases<br>- Graph RAG / Knowledge graphs<br>- Context rot<br>- Evals / Data flywheel</p><p>Context engineering is where product strategy meets model behavior. The best AI products aren't using better models—they're using better context.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>The best prompt engineer I know told me he stopped writing prompts.</p><p>He said: "Prompts are maybe 5% of what makes AI actually useful. The other 95%? It's everything the model sees before you even ask a question."</p><p>If you're building AI features and still obsessing over prompt wording, you're optimizing the wrong thing.</p><p>In this episode, I break down context engineering—what it is, where the term comes from, and how product managers can own the context window without writing code.</p><p>**What you'll learn:**</p><p>- Why "know your user" is the foundation of context engineering<br>- The 3 types of retrieval: keyword, semantic, and graph RAG<br>- Why more context actually hurts performance (context rot)<br>- How to build evals that learn from future outcomes<br>- 5 actionable homework items you can start today</p><p>**People mentioned:**</p><p>- Simon Willison (AI Engineer, Creator of Datasette)<br>- Kevin Weil (CPO at OpenAI)</p><p>**Key terms:**</p><p>- Context window<br>- RAG (Retrieval Augmented Generation)<br>- Semantic search / Vector databases<br>- Graph RAG / Knowledge graphs<br>- Context rot<br>- Evals / Data flywheel</p><p>Context engineering is where product strategy meets model behavior. The best AI products aren't using better models—they're using better context.</p>]]>
      </content:encoded>
      <pubDate>Mon, 29 Dec 2025 22:16:05 -0800</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/07a139e1/cb3fa8e8.mp3" length="9169441" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/jVswS8vT_5IveMVIA9Dtt7vnvGKuNttRY1t2NlYXhS4/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8wY2Yz/YTA1ZThjNDYwN2Jm/OGJlNzRjNWU2MjU3/ZDVkMC5wbmc.jpg"/>
      <itunes:duration>571</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>The best prompt engineer I know told me he stopped writing prompts.</p><p>He said: "Prompts are maybe 5% of what makes AI actually useful. The other 95%? It's everything the model sees before you even ask a question."</p><p>If you're building AI features and still obsessing over prompt wording, you're optimizing the wrong thing.</p><p>In this episode, I break down context engineering—what it is, where the term comes from, and how product managers can own the context window without writing code.</p><p>**What you'll learn:**</p><p>- Why "know your user" is the foundation of context engineering<br>- The 3 types of retrieval: keyword, semantic, and graph RAG<br>- Why more context actually hurts performance (context rot)<br>- How to build evals that learn from future outcomes<br>- 5 actionable homework items you can start today</p><p>**People mentioned:**</p><p>- Simon Willison (AI Engineer, Creator of Datasette)<br>- Kevin Weil (CPO at OpenAI)</p><p>**Key terms:**</p><p>- Context window<br>- RAG (Retrieval Augmented Generation)<br>- Semantic search / Vector databases<br>- Graph RAG / Knowledge graphs<br>- Context rot<br>- Evals / Data flywheel</p><p>Context engineering is where product strategy meets model behavior. The best AI products aren't using better models—they're using better context.</p>]]>
      </itunes:summary>
      <itunes:keywords>context engineering, prompt engineering, AI product management, RAG, LLM, semantic search, vector database, graph RAG, product manager, AI strategy</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Why Karpathy Saying “I’m Behind”  Should Matter to Every PM</title>
      <itunes:episode>1</itunes:episode>
      <podcast:episode>1</podcast:episode>
      <itunes:title>Why Karpathy Saying “I’m Behind”  Should Matter to Every PM</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">a8662e30-5d0e-4fa0-946f-fbb184a198e0</guid>
      <link>https://share.transistor.fm/s/c140c8b5</link>
      <description>
        <![CDATA[<p><strong>🎧 Episode 001 — If Karpathy Feels Behind, What Does That Mean for Product Managers?</strong></p><p><br></p><p><strong>Summary:</strong></p><p>In this debut episode of <em>Contextually Aware</em>, product manager Luis Calderon dives into a striking moment from the AI world. Andrej Karpathy — former Tesla AI lead, co-founder of OpenAI, and one of the most respected voices in AI — recently said he has <em>“never felt this much behind as a programmer,”</em> because artificial intelligence is fundamentally reshaping how software gets built. That change isn’t incremental — Karpathy describes the profession as being <em>dramatically refactored</em> by AI tools and paradigms.  </p><p><br></p><p>In this episode, we turn that insight into meaning for product managers. What does <em>feeling behind</em> actually signal about how AI is changing software development? And what questions should PMs be asking about strategy, workflows, uncertainty, and success when AI becomes a core part of how products are built?</p><p><br></p><p><strong>Key Topics Covered:</strong></p><p><br></p><ul><li>A clear explanation of Karpathy’s candid reflection on AI and programming.  </li><li>Why this matters to product managers — beyond engineering hype.</li><li>How AI tools and abstractions (agents, workflows, memory layers) are changing mental models for building software.</li><li>Practical product strategy implications: decision-making, risk, and prioritization.</li><li>A big open question to carry forward: <em>How do we define success when the tools we use are probabilistic and evolving?</em></li></ul><p><br></p><p><strong>Who This Episode Is For:</strong></p><p>Product managers, technical leaders, builders, and anyone trying to make sense of <strong>how AI is changing the craft of building products</strong> — and who wants to keep up without drowning in hype.</p><p><br></p><p><strong>Resources Mentioned:</strong></p><p><br></p><ul><li>Karpathy’s reflective post on AI and programming being refactored by AI.  </li><li>Broader context on how software development paradigms are shifting (Software 3.0).  </li></ul><p><br></p><p><strong>Connect &amp; Engage:</strong></p><p>If this resonated, share it with a colleague and join the conversation! Tweet at @ContextuallyAware or connect on LinkedIn — your thoughts will shape future episodes.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p><strong>🎧 Episode 001 — If Karpathy Feels Behind, What Does That Mean for Product Managers?</strong></p><p><br></p><p><strong>Summary:</strong></p><p>In this debut episode of <em>Contextually Aware</em>, product manager Luis Calderon dives into a striking moment from the AI world. Andrej Karpathy — former Tesla AI lead, co-founder of OpenAI, and one of the most respected voices in AI — recently said he has <em>“never felt this much behind as a programmer,”</em> because artificial intelligence is fundamentally reshaping how software gets built. That change isn’t incremental — Karpathy describes the profession as being <em>dramatically refactored</em> by AI tools and paradigms.  </p><p><br></p><p>In this episode, we turn that insight into meaning for product managers. What does <em>feeling behind</em> actually signal about how AI is changing software development? And what questions should PMs be asking about strategy, workflows, uncertainty, and success when AI becomes a core part of how products are built?</p><p><br></p><p><strong>Key Topics Covered:</strong></p><p><br></p><ul><li>A clear explanation of Karpathy’s candid reflection on AI and programming.  </li><li>Why this matters to product managers — beyond engineering hype.</li><li>How AI tools and abstractions (agents, workflows, memory layers) are changing mental models for building software.</li><li>Practical product strategy implications: decision-making, risk, and prioritization.</li><li>A big open question to carry forward: <em>How do we define success when the tools we use are probabilistic and evolving?</em></li></ul><p><br></p><p><strong>Who This Episode Is For:</strong></p><p>Product managers, technical leaders, builders, and anyone trying to make sense of <strong>how AI is changing the craft of building products</strong> — and who wants to keep up without drowning in hype.</p><p><br></p><p><strong>Resources Mentioned:</strong></p><p><br></p><ul><li>Karpathy’s reflective post on AI and programming being refactored by AI.  </li><li>Broader context on how software development paradigms are shifting (Software 3.0).  </li></ul><p><br></p><p><strong>Connect &amp; Engage:</strong></p><p>If this resonated, share it with a colleague and join the conversation! Tweet at @ContextuallyAware or connect on LinkedIn — your thoughts will shape future episodes.</p>]]>
      </content:encoded>
      <pubDate>Sat, 27 Dec 2025 20:45:03 -0800</pubDate>
      <author>Luis Calderon</author>
      <enclosure url="https://media.transistor.fm/c140c8b5/a187706e.mp3" length="7529367" type="audio/mpeg"/>
      <itunes:author>Luis Calderon</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/HaMW7KqkmC9t68SwBozafzFDxSrUpWXxDGHQvdutIkM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MDM1/ZDEwNTQ5MjBhNDE0/MDg0OTg2Njk1Yzcw/YmNmYy5qcGVn.jpg"/>
      <itunes:duration>468</itunes:duration>
      <itunes:summary>
        <![CDATA[<p><strong>🎧 Episode 001 — If Karpathy Feels Behind, What Does That Mean for Product Managers?</strong></p><p><br></p><p><strong>Summary:</strong></p><p>In this debut episode of <em>Contextually Aware</em>, product manager Luis Calderon dives into a striking moment from the AI world. Andrej Karpathy — former Tesla AI lead, co-founder of OpenAI, and one of the most respected voices in AI — recently said he has <em>“never felt this much behind as a programmer,”</em> because artificial intelligence is fundamentally reshaping how software gets built. That change isn’t incremental — Karpathy describes the profession as being <em>dramatically refactored</em> by AI tools and paradigms.  </p><p><br></p><p>In this episode, we turn that insight into meaning for product managers. What does <em>feeling behind</em> actually signal about how AI is changing software development? And what questions should PMs be asking about strategy, workflows, uncertainty, and success when AI becomes a core part of how products are built?</p><p><br></p><p><strong>Key Topics Covered:</strong></p><p><br></p><ul><li>A clear explanation of Karpathy’s candid reflection on AI and programming.  </li><li>Why this matters to product managers — beyond engineering hype.</li><li>How AI tools and abstractions (agents, workflows, memory layers) are changing mental models for building software.</li><li>Practical product strategy implications: decision-making, risk, and prioritization.</li><li>A big open question to carry forward: <em>How do we define success when the tools we use are probabilistic and evolving?</em></li></ul><p><br></p><p><strong>Who This Episode Is For:</strong></p><p>Product managers, technical leaders, builders, and anyone trying to make sense of <strong>how AI is changing the craft of building products</strong> — and who wants to keep up without drowning in hype.</p><p><br></p><p><strong>Resources Mentioned:</strong></p><p><br></p><ul><li>Karpathy’s reflective post on AI and programming being refactored by AI.  </li><li>Broader context on how software development paradigms are shifting (Software 3.0).  </li></ul><p><br></p><p><strong>Connect &amp; Engage:</strong></p><p>If this resonated, share it with a colleague and join the conversation! Tweet at @ContextuallyAware or connect on LinkedIn — your thoughts will shape future episodes.</p>]]>
      </itunes:summary>
      <itunes:keywords>Andre Karpathy Tweet on X</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/c140c8b5/transcript.srt" type="application/x-subrip" rel="captions"/>
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