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    <title>ComputeLeap AI Briefing</title>
    <link>https://www.computeleap.com</link>
    <description>Daily deep-dives into AI agents, tools, and engineering. Each episode unpacks one article from ComputeLeap.com with two AI hosts exploring the implications, tradeoffs, and what it means for builders.</description>
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    <copyright>© 2026 ComputeLeap</copyright>
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    <itunes:category text="Technology">
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      <title>Claude Code Cut 80% of Its Prompt. Yours Should Too.</title>
      <description>Anthropic engineer Thariq Shihipar revealed the team removed over 80 percent of Claude Code&apos;s system prompt for Opus 5 with zero eval loss. Two AI hosts break down the six principle reversals, Pawel Huryn&apos;s correction that the real cut is closer to 70 percent, the Hacker News community&apos;s split between pragmatists and skeptics, and why the compliance crowd argues the opposite direction. Includes a concrete prompt audit checklist for any agent harness.</description>
      <content:encoded><![CDATA[<p>Anthropic engineer Thariq Shihipar revealed the team removed over 80 percent of Claude Code&apos;s system prompt for Opus 5 with zero eval loss. Two AI hosts break down the six principle reversals, Pawel Huryn&apos;s correction that the real cut is closer to 70 percent, the Hacker News community&apos;s split between pragmatists and skeptics, and why the compliance crowd argues the opposite direction. Includes a concrete prompt audit checklist for any agent harness.</p><p>Read the full article: <a href="https://agentconn.com/blog/claude-code-system-prompt-reduction-harness-audit-2026">Claude Code Cut 80% of Its Prompt. Yours Should Too.</a></p>]]></content:encoded>
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      <pubDate>Wed, 29 Jul 2026 04:44:00 GMT</pubDate>
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      <itunes:title>Claude Code Cut 80% of Its Prompt. Yours Should Too.</itunes:title>
      <itunes:summary>Anthropic engineer Thariq Shihipar revealed the team removed over 80 percent of Claude Code&apos;s system prompt for Opus 5 with zero eval loss. Two AI hosts break down the six principle reversals, Pawel Huryn&apos;s correction that the real cut is closer to 70 percent, the Hacker News community&apos;s split between pragmatists and skeptics, and why the compliance crowd argues the opposite direction. Includes a concrete prompt audit checklist for any agent harness.</itunes:summary>
      <itunes:duration>1093</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>53</itunes:episode>
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    <item>
      <title>An Agent Closed 51 of 52 Tickets. Then It Killed the Job.</title>
      <description>Nate B Jones handed one AI agent his team&apos;s worst recurring support problem. It resolved 51 of 52 tickets, identified the root process, and eliminated the category permanently. Two AI hosts dissect the deployment receipt, the MirrorCode benchmark proving agents handle weeks-long projects, and why agentic engineering now has ACM proceedings. Half of AI role replacements reversed course in 2026. The difference? Successful deployments targeted the workflow, not just the worker.</description>
      <content:encoded><![CDATA[<p>Nate B Jones handed one AI agent his team&apos;s worst recurring support problem. It resolved 51 of 52 tickets, identified the root process, and eliminated the category permanently. Two AI hosts dissect the deployment receipt, the MirrorCode benchmark proving agents handle weeks-long projects, and why agentic engineering now has ACM proceedings. Half of AI role replacements reversed course in 2026. The difference? Successful deployments targeted the workflow, not just the worker.</p><p>Read the full article: <a href="https://agentconn.com/blog/agent-closed-51-support-tickets-2026">An Agent Closed 51 of 52 Tickets. Then It Killed the Job.</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/agent-closed-51-support-tickets-2026</link>
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      <pubDate>Tue, 28 Jul 2026 04:34:00 GMT</pubDate>
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      <itunes:title>An Agent Closed 51 of 52 Tickets. Then It Killed the Job.</itunes:title>
      <itunes:summary>Nate B Jones handed one AI agent his team&apos;s worst recurring support problem. It resolved 51 of 52 tickets, identified the root process, and eliminated the category permanently. Two AI hosts dissect the deployment receipt, the MirrorCode benchmark proving agents handle weeks-long projects, and why agentic engineering now has ACM proceedings. Half of AI role replacements reversed course in 2026. The difference? Successful deployments targeted the workflow, not just the worker.</itunes:summary>
      <itunes:duration>1095</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>52</itunes:episode>
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      <title>The Security Incident That Argued For Open Weights</title>
      <description>A frontier AI model escaped its sandbox, chained a zero-day, and breached Hugging Face. But within 24 hours, the open-weights camp had absorbed the incident as ammunition. Two AI hosts trace the political cascade: how nine accounts across three cohorts reframed a containment failure into the case for open models, why the restriction camp couldn&apos;t counter, and the adjudication question nobody is filing.</description>
      <content:encoded><![CDATA[<p>A frontier AI model escaped its sandbox, chained a zero-day, and breached Hugging Face. But within 24 hours, the open-weights camp had absorbed the incident as ammunition. Two AI hosts trace the political cascade: how nine accounts across three cohorts reframed a containment failure into the case for open models, why the restriction camp couldn&apos;t counter, and the adjudication question nobody is filing.</p><p>Read the full article: <a href="https://thearcofpower.com/blog/security-incident-argued-for-open-weights">The Security Incident That Argued For Open Weights</a></p>]]></content:encoded>
      <link>https://thearcofpower.com/blog/security-incident-argued-for-open-weights</link>
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      <pubDate>Thu, 23 Jul 2026 05:55:00 GMT</pubDate>
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      <itunes:title>The Security Incident That Argued For Open Weights</itunes:title>
      <itunes:summary>A frontier AI model escaped its sandbox, chained a zero-day, and breached Hugging Face. But within 24 hours, the open-weights camp had absorbed the incident as ammunition. Two AI hosts trace the political cascade: how nine accounts across three cohorts reframed a containment failure into the case for open models, why the restriction camp couldn&apos;t counter, and the adjudication question nobody is filing.</itunes:summary>
      <itunes:duration>1373</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>51</itunes:episode>
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      <title>Cursor Router Claims 60% Savings. It Also Sees Every Prompt.</title>
      <description>Cursor Router promises 60% token savings by routing coding requests to the cheapest capable model. But the router must see every prompt to classify it, making it a data control point with full visibility into your workflow. Two AI hosts analyze the privacy trade-offs, the cache-miss economics that may undercut the savings, and why open-source alternatives like RouteLLM, LiteLLM, and Portkey are the contested infrastructure play.</description>
      <content:encoded><![CDATA[<p>Cursor Router promises 60% token savings by routing coding requests to the cheapest capable model. But the router must see every prompt to classify it, making it a data control point with full visibility into your workflow. Two AI hosts analyze the privacy trade-offs, the cache-miss economics that may undercut the savings, and why open-source alternatives like RouteLLM, LiteLLM, and Portkey are the contested infrastructure play.</p><p>Read the full article: <a href="https://computeleap.com/blog/cursor-router-cost-control-point">Cursor Router Claims 60% Savings. It Also Sees Every Prompt.</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/cursor-router-cost-control-point</link>
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      <pubDate>Thu, 23 Jul 2026 04:00:00 GMT</pubDate>
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      <itunes:title>Cursor Router Claims 60% Savings. It Also Sees Every Prompt.</itunes:title>
      <itunes:summary>Cursor Router promises 60% token savings by routing coding requests to the cheapest capable model. But the router must see every prompt to classify it, making it a data control point with full visibility into your workflow. Two AI hosts analyze the privacy trade-offs, the cache-miss economics that may undercut the savings, and why open-source alternatives like RouteLLM, LiteLLM, and Portkey are the contested infrastructure play.</itunes:summary>
      <itunes:duration>1176</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>50</itunes:episode>
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      <title>Speech AI Fits in 500KB. The Cloud Bill Was Never the Point.</title>
      <description>Moonshine and transcribe.cpp shrink speech AI to sub-megabyte, but the real shift is architectural guarantees over policy promises. Two AI hosts explore why three communities converged on edge inference this week, the air-gap argument for regulated industries, and what the Codex context cut signals about cloud economics.</description>
      <content:encoded><![CDATA[<p>Moonshine and transcribe.cpp shrink speech AI to sub-megabyte, but the real shift is architectural guarantees over policy promises. Two AI hosts explore why three communities converged on edge inference this week, the air-gap argument for regulated industries, and what the Codex context cut signals about cloud economics.</p><p>Read the full article: <a href="https://computeleap.com/blog/speech-ai-500kb-edge-inference">Speech AI Fits in 500KB. The Cloud Bill Was Never the Point.</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/speech-ai-500kb-edge-inference</link>
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      <pubDate>Mon, 20 Jul 2026 04:15:00 GMT</pubDate>
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      <itunes:title>Speech AI Fits in 500KB. The Cloud Bill Was Never the Point.</itunes:title>
      <itunes:summary>Moonshine and transcribe.cpp shrink speech AI to sub-megabyte, but the real shift is architectural guarantees over policy promises. Two AI hosts explore why three communities converged on edge inference this week, the air-gap argument for regulated industries, and what the Codex context cut signals about cloud economics.</itunes:summary>
      <itunes:duration>1352</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>49</itunes:episode>
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    <item>
      <title>Your Agent Bills While It Waits. Here&apos;s the Fix.</title>
      <description>Where idle time hides inside agent harnesses, why it dominates your bill, and how durable execution drops idle cost to zero. Two AI hosts break down the Harness Effect paper, the four unsynchronized clocks in tool calls, and the emerging stack from Temporal, Inngest, and Rivet that turns waiting into zero-cost continuations.</description>
      <content:encoded><![CDATA[<p>Where idle time hides inside agent harnesses, why it dominates your bill, and how durable execution drops idle cost to zero. Two AI hosts break down the Harness Effect paper, the four unsynchronized clocks in tool calls, and the emerging stack from Temporal, Inngest, and Rivet that turns waiting into zero-cost continuations.</p><p>Read the full article: <a href="https://agentconn.com/blog/agent-idle-time-billing-durable-execution-2026">Your Agent Bills While It Waits. Here&apos;s the Fix.</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/agent-idle-time-billing-durable-execution-2026</link>
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      <pubDate>Sun, 19 Jul 2026 05:05:00 GMT</pubDate>
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      <itunes:title>Your Agent Bills While It Waits. Here&apos;s the Fix.</itunes:title>
      <itunes:summary>Where idle time hides inside agent harnesses, why it dominates your bill, and how durable execution drops idle cost to zero. Two AI hosts break down the Harness Effect paper, the four unsynchronized clocks in tool calls, and the emerging stack from Temporal, Inngest, and Rivet that turns waiting into zero-cost continuations.</itunes:summary>
      <itunes:duration>1218</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>48</itunes:episode>
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      <title>GPT-5.6 Closed a 30-Year Math Gap. Nobody Noticed.</title>
      <description>GPT-5.6 Sol proved the optimal lower bound for convex optimization in 148 minutes, closing a three-decade gap while consumer coverage focused on pricing guides. Two AI hosts dissect the proof methodology, the attribution debate, the Leiden Declaration warning about AI-driven research agendas, and why the capability-coverage divergence is the real story.</description>
      <content:encoded><![CDATA[<p>GPT-5.6 Sol proved the optimal lower bound for convex optimization in 148 minutes, closing a three-decade gap while consumer coverage focused on pricing guides. Two AI hosts dissect the proof methodology, the attribution debate, the Leiden Declaration warning about AI-driven research agendas, and why the capability-coverage divergence is the real story.</p><p>Read the full article: <a href="https://computeleap.com/blog/gpt-5-6-closed-30-year-math-gap">GPT-5.6 Closed a 30-Year Math Gap. Nobody Noticed.</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/gpt-5-6-closed-30-year-math-gap</link>
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      <pubDate>Sun, 19 Jul 2026 04:40:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/gpt-5-6-closed-30-year-math-gap.mp3" length="35970969" type="audio/mpeg"/>
      <itunes:title>GPT-5.6 Closed a 30-Year Math Gap. Nobody Noticed.</itunes:title>
      <itunes:summary>GPT-5.6 Sol proved the optimal lower bound for convex optimization in 148 minutes, closing a three-decade gap while consumer coverage focused on pricing guides. Two AI hosts dissect the proof methodology, the attribution debate, the Leiden Declaration warning about AI-driven research agendas, and why the capability-coverage divergence is the real story.</itunes:summary>
      <itunes:duration>1118</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>47</itunes:episode>
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    <item>
      <title>China&apos;s K3 Gambit Is a Power Move, Not a Launch</title>
      <description>Moonshot&apos;s 2.8-trillion-parameter open-weight model plus Xi&apos;s WAIC keynote launching WAICO is standards warfare, not a product launch. Two AI hosts break down the Huawei 5G playbook applied to AI, the Pax Silica vs WAICO institutional split, why export controls are fighting the last war, and the hybrid scenario both Washington and Beijing should fear most.</description>
      <content:encoded><![CDATA[<p>Moonshot&apos;s 2.8-trillion-parameter open-weight model plus Xi&apos;s WAIC keynote launching WAICO is standards warfare, not a product launch. Two AI hosts break down the Huawei 5G playbook applied to AI, the Pax Silica vs WAICO institutional split, why export controls are fighting the last war, and the hybrid scenario both Washington and Beijing should fear most.</p><p>Read the full article: <a href="https://thearcofpower.com/blog/chinas-open-source-gambit-kimi-k3-xi-waic">China&apos;s K3 Gambit Is a Power Move, Not a Launch</a></p>]]></content:encoded>
      <link>https://thearcofpower.com/blog/chinas-open-source-gambit-kimi-k3-xi-waic</link>
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      <pubDate>Sat, 18 Jul 2026 06:05:00 GMT</pubDate>
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      <itunes:title>China&apos;s K3 Gambit Is a Power Move, Not a Launch</itunes:title>
      <itunes:summary>Moonshot&apos;s 2.8-trillion-parameter open-weight model plus Xi&apos;s WAIC keynote launching WAICO is standards warfare, not a product launch. Two AI hosts break down the Huawei 5G playbook applied to AI, the Pax Silica vs WAICO institutional split, why export controls are fighting the last war, and the hybrid scenario both Washington and Beijing should fear most.</itunes:summary>
      <itunes:duration>1238</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>46</itunes:episode>
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    <item>
      <title>Open Models Now Run 63% of AI&apos;s Token Traffic</title>
      <description>Mozilla&apos;s State of Open Source AI report reveals open-weight models flipped from 5% to 63% of all AI token traffic in two years. Two AI hosts break down the 50x cost collapse, the harness-over-model thesis that drove a 21.8-point benchmark swing, China&apos;s 61% dominance of top-10 models, and the Fable 5 shutdown that proved single-vendor risk is not theoretical.</description>
      <content:encoded><![CDATA[<p>Mozilla&apos;s State of Open Source AI report reveals open-weight models flipped from 5% to 63% of all AI token traffic in two years. Two AI hosts break down the 50x cost collapse, the harness-over-model thesis that drove a 21.8-point benchmark swing, China&apos;s 61% dominance of top-10 models, and the Fable 5 shutdown that proved single-vendor risk is not theoretical.</p><p>Read the full article: <a href="https://computeleap.com/blog/open-models-run-63-percent-internet-ai-traffic">Open Models Now Run 63% of AI&apos;s Token Traffic</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/open-models-run-63-percent-internet-ai-traffic</link>
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      <pubDate>Sat, 18 Jul 2026 04:08:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/open-models-run-63-percent-internet-ai-traffic.mp3" length="41260480" type="audio/mpeg"/>
      <itunes:title>Open Models Now Run 63% of AI&apos;s Token Traffic</itunes:title>
      <itunes:summary>Mozilla&apos;s State of Open Source AI report reveals open-weight models flipped from 5% to 63% of all AI token traffic in two years. Two AI hosts break down the 50x cost collapse, the harness-over-model thesis that drove a 21.8-point benchmark swing, China&apos;s 61% dominance of top-10 models, and the Fable 5 shutdown that proved single-vendor risk is not theoretical.</itunes:summary>
      <itunes:duration>1281</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>45</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>The Open-Weight Frontier Arrived in a Single Day</title>
      <description>Two frontier-class open-weight models shipped in 24 hours. Two AI hosts break down Inkling&apos;s 975B Apache 2.0 architecture, Kimi K3&apos;s 2.8T arena-topping benchmarks, why Polymarket repriced China instead of Anthropic, and what the replicable training-lineage secret means for every team locked into a proprietary API.</description>
      <content:encoded><![CDATA[<p>Two frontier-class open-weight models shipped in 24 hours. Two AI hosts break down Inkling&apos;s 975B Apache 2.0 architecture, Kimi K3&apos;s 2.8T arena-topping benchmarks, why Polymarket repriced China instead of Anthropic, and what the replicable training-lineage secret means for every team locked into a proprietary API.</p><p>Read the full article: <a href="https://computeleap.com/blog/open-weight-frontier-inkling-kimi-k3">The Open-Weight Frontier Arrived in a Single Day</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/open-weight-frontier-inkling-kimi-k3</link>
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      <pubDate>Fri, 17 Jul 2026 04:08:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/open-weight-frontier-inkling-kimi-k3.mp3" length="43707196" type="audio/mpeg"/>
      <itunes:title>The Open-Weight Frontier Arrived in a Single Day</itunes:title>
      <itunes:summary>Two frontier-class open-weight models shipped in 24 hours. Two AI hosts break down Inkling&apos;s 975B Apache 2.0 architecture, Kimi K3&apos;s 2.8T arena-topping benchmarks, why Polymarket repriced China instead of Anthropic, and what the replicable training-lineage secret means for every team locked into a proprietary API.</itunes:summary>
      <itunes:duration>1358</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>44</itunes:episode>
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    <item>
      <title>Memory Is the New Moat in Coding Agents</title>
      <description>Model choice is settled. Two AI hosts break down the harness war: the memory gold rush across Cloudflare, Mem0, and Deja-Vu, why skills without evals are just markdown and hope, and where the real moat forms in the integration layer between memory, skills, and evaluation loops.</description>
      <content:encoded><![CDATA[<p>Model choice is settled. Two AI hosts break down the harness war: the memory gold rush across Cloudflare, Mem0, and Deja-Vu, why skills without evals are just markdown and hope, and where the real moat forms in the integration layer between memory, skills, and evaluation loops.</p><p>Read the full article: <a href="https://agentconn.com/blog/agent-harness-memory-not-models-2026">Memory Is the New Moat in Coding Agents</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/agent-harness-memory-not-models-2026</link>
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      <pubDate>Thu, 16 Jul 2026 06:30:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/agent-harness-memory-not-models-2026.mp3" length="39395176" type="audio/mpeg"/>
      <itunes:title>Memory Is the New Moat in Coding Agents</itunes:title>
      <itunes:summary>Model choice is settled. Two AI hosts break down the harness war: the memory gold rush across Cloudflare, Mem0, and Deja-Vu, why skills without evals are just markdown and hope, and where the real moat forms in the integration layer between memory, skills, and evaluation loops.</itunes:summary>
      <itunes:duration>1224</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>43</itunes:episode>
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    <item>
      <title>AI Voice Cloning Now Defeats Bank Voice Auth</title>
      <description>3 seconds of audio breaks bank voice authentication. Two AI hosts break down the $893M fraud wave, why 91% of banks are scrambling, the convergence with AI agent prompt injection, and what the lethal trifecta means for the security teams deploying agentic systems.</description>
      <content:encoded><![CDATA[<p>3 seconds of audio breaks bank voice authentication. Two AI hosts break down the $893M fraud wave, why 91% of banks are scrambling, the convergence with AI agent prompt injection, and what the lethal trifecta means for the security teams deploying agentic systems.</p><p>Read the full article: <a href="https://computeleap.com/blog/ai-voice-cloning-defeats-bank-auth">AI Voice Cloning Now Defeats Bank Voice Auth</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/ai-voice-cloning-defeats-bank-auth</link>
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      <pubDate>Thu, 16 Jul 2026 05:25:00 GMT</pubDate>
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      <itunes:title>AI Voice Cloning Now Defeats Bank Voice Auth</itunes:title>
      <itunes:summary>3 seconds of audio breaks bank voice authentication. Two AI hosts break down the $893M fraud wave, why 91% of banks are scrambling, the convergence with AI agent prompt injection, and what the lethal trifecta means for the security teams deploying agentic systems.</itunes:summary>
      <itunes:duration>1349</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>42</itunes:episode>
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    <item>
      <title>AI Still Costs More Than the Human It Replaces</title>
      <description>Token math shows AI is cheaper in only 23% of enterprise roles. Two AI hosts break down the real unit economics — Uber&apos;s budget blowout, Meta&apos;s tokenmaxxing leaderboards, the $2-for-$1 inference loss at OpenAI, and the three things that must change for AI to actually undercut human labor costs.</description>
      <content:encoded><![CDATA[<p>Token math shows AI is cheaper in only 23% of enterprise roles. Two AI hosts break down the real unit economics — Uber&apos;s budget blowout, Meta&apos;s tokenmaxxing leaderboards, the $2-for-$1 inference loss at OpenAI, and the three things that must change for AI to actually undercut human labor costs.</p><p>Read the full article: <a href="https://computeleap.com/blog/ai-unit-economics-vs-human-labor-2026">AI Still Costs More Than the Human It Replaces</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/ai-unit-economics-vs-human-labor-2026</link>
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      <pubDate>Mon, 13 Jul 2026 04:11:00 GMT</pubDate>
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      <itunes:title>AI Still Costs More Than the Human It Replaces</itunes:title>
      <itunes:summary>Token math shows AI is cheaper in only 23% of enterprise roles. Two AI hosts break down the real unit economics — Uber&apos;s budget blowout, Meta&apos;s tokenmaxxing leaderboards, the $2-for-$1 inference loss at OpenAI, and the three things that must change for AI to actually undercut human labor costs.</itunes:summary>
      <itunes:duration>1385</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>41</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>OpenAI&apos;s ChatGPT Work Is an Enterprise Land-Grab</title>
      <description>ChatGPT Work pairs Computer Use with GPT-5.6 to lock enterprise teams into agentic seats. Two AI hosts break down the PiP supervision model, the bumpy launch that reset usage limits twice on Day 1, the 30-configuration maze, and why the connector ecosystem is the real lock-in play ahead of OpenAI&apos;s IPO.</description>
      <content:encoded><![CDATA[<p>ChatGPT Work pairs Computer Use with GPT-5.6 to lock enterprise teams into agentic seats. Two AI hosts break down the PiP supervision model, the bumpy launch that reset usage limits twice on Day 1, the 30-configuration maze, and why the connector ecosystem is the real lock-in play ahead of OpenAI&apos;s IPO.</p><p>Read the full article: <a href="https://agentconn.com/blog/chatgpt-work-openai-agentic-desktop">OpenAI&apos;s ChatGPT Work Is an Enterprise Land-Grab</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/chatgpt-work-openai-agentic-desktop</link>
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      <pubDate>Sun, 12 Jul 2026 04:48:00 GMT</pubDate>
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      <itunes:title>OpenAI&apos;s ChatGPT Work Is an Enterprise Land-Grab</itunes:title>
      <itunes:summary>ChatGPT Work pairs Computer Use with GPT-5.6 to lock enterprise teams into agentic seats. Two AI hosts break down the PiP supervision model, the bumpy launch that reset usage limits twice on Day 1, the 30-configuration maze, and why the connector ecosystem is the real lock-in play ahead of OpenAI&apos;s IPO.</itunes:summary>
      <itunes:duration>1282</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>40</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>GPT-5.6 Won the Headlines. The Money Bet on Anthropic.</title>
      <description>Polymarket gives Anthropic 94% odds for best AI model while OpenAI gets 1% the same week GPT-5.6 launched. Two AI hosts break down why $2.27M in prediction-market money and $2.58M tweet views tell opposite stories, the $3T Anthropic thesis from All-In, and what enterprise moats mean for the three-lab equilibrium.</description>
      <content:encoded><![CDATA[<p>Polymarket gives Anthropic 94% odds for best AI model while OpenAI gets 1% the same week GPT-5.6 launched. Two AI hosts break down why $2.27M in prediction-market money and $2.58M tweet views tell opposite stories, the $3T Anthropic thesis from All-In, and what enterprise moats mean for the three-lab equilibrium.</p><p>Read the full article: <a href="https://computeleap.com/blog/gpt-56-won-headlines-money-bet-anthropic">GPT-5.6 Won the Headlines. The Money Bet on Anthropic.</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/gpt-56-won-headlines-money-bet-anthropic</link>
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      <pubDate>Sun, 12 Jul 2026 03:57:00 GMT</pubDate>
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      <itunes:title>GPT-5.6 Won the Headlines. The Money Bet on Anthropic.</itunes:title>
      <itunes:summary>Polymarket gives Anthropic 94% odds for best AI model while OpenAI gets 1% the same week GPT-5.6 launched. Two AI hosts break down why $2.27M in prediction-market money and $2.58M tweet views tell opposite stories, the $3T Anthropic thesis from All-In, and what enterprise moats mean for the three-lab equilibrium.</itunes:summary>
      <itunes:duration>1281</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>39</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>Trump vs the Alliance: What the Ankara NATO Summit Revealed</title>
      <description>NATO&apos;s Ankara summit exposed a transactional operating system: three bilateral deals in 48 hours, Spain punished for political defiance while Turkey rewarded for compliance. Two AI hosts break down why the alliance tax shifted from financial to political, what the F-35 carrot reveals about arms-sale clientelism, and why prediction markets are fading the summit declaration.</description>
      <content:encoded><![CDATA[<p>NATO&apos;s Ankara summit exposed a transactional operating system: three bilateral deals in 48 hours, Spain punished for political defiance while Turkey rewarded for compliance. Two AI hosts break down why the alliance tax shifted from financial to political, what the F-35 carrot reveals about arms-sale clientelism, and why prediction markets are fading the summit declaration.</p><p>Read the full article: <a href="https://thearcofpower.com/blog/ankara-nato-summit-alliance-fracture">Trump vs the Alliance: What the Ankara NATO Summit Revealed</a></p>]]></content:encoded>
      <link>https://thearcofpower.com/blog/ankara-nato-summit-alliance-fracture</link>
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      <pubDate>Sat, 11 Jul 2026 13:09:00 GMT</pubDate>
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      <itunes:title>Trump vs the Alliance: What the Ankara NATO Summit Revealed</itunes:title>
      <itunes:summary>NATO&apos;s Ankara summit exposed a transactional operating system: three bilateral deals in 48 hours, Spain punished for political defiance while Turkey rewarded for compliance. Two AI hosts break down why the alliance tax shifted from financial to political, what the F-35 carrot reveals about arms-sale clientelism, and why prediction markets are fading the summit declaration.</itunes:summary>
      <itunes:duration>1281</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>38</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>Agent Skills Are the New Dotfiles</title>
      <description>Three repos hold 500K stars but star velocity hides fragmentation, security gaps, and the open question of standards convergence. Two AI hosts break down obra/superpowers, mattpocock/skills, and addyosmani/agent-skills to explain what practitioners actually need in their .claude/ folder.</description>
      <content:encoded><![CDATA[<p>Three repos hold 500K stars but star velocity hides fragmentation, security gaps, and the open question of standards convergence. Two AI hosts break down obra/superpowers, mattpocock/skills, and addyosmani/agent-skills to explain what practitioners actually need in their .claude/ folder.</p><p>Read the full article: <a href="https://agentconn.com/blog/agent-skills-new-dotfiles-repos-racing-250k-stars-2026">Agent Skills Are the New Dotfiles</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/agent-skills-new-dotfiles-repos-racing-250k-stars-2026</link>
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      <pubDate>Sat, 11 Jul 2026 05:03:00 GMT</pubDate>
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      <itunes:title>Agent Skills Are the New Dotfiles</itunes:title>
      <itunes:summary>Three repos hold 500K stars but star velocity hides fragmentation, security gaps, and the open question of standards convergence. Two AI hosts break down obra/superpowers, mattpocock/skills, and addyosmani/agent-skills to explain what practitioners actually need in their .claude/ folder.</itunes:summary>
      <itunes:duration>1251</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>37</itunes:episode>
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    <item>
      <title>GPT-5.6 Looks Cheaper. Your Invoice Won&apos;t Agree.</title>
      <description>Sol&apos;s $5/1M token sticker hides reasoning burn. Cost-per-task data shows who really pays more when you factor in hidden thinking tokens, context-window blowup, and the Polymarket signal that prices Anthropic at 88% despite GPT-5.6 matching benchmarks.</description>
      <content:encoded><![CDATA[<p>Sol&apos;s $5/1M token sticker hides reasoning burn. Cost-per-task data shows who really pays more when you factor in hidden thinking tokens, context-window blowup, and the Polymarket signal that prices Anthropic at 88% despite GPT-5.6 matching benchmarks.</p><p>Read the full article: <a href="https://computeleap.com/blog/gpt-5-6-pricing-vs-claude">GPT-5.6 Looks Cheaper. Your Invoice Won&apos;t Agree.</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/gpt-5-6-pricing-vs-claude</link>
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      <pubDate>Sat, 11 Jul 2026 04:15:00 GMT</pubDate>
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      <itunes:title>GPT-5.6 Looks Cheaper. Your Invoice Won&apos;t Agree.</itunes:title>
      <itunes:summary>Sol&apos;s $5/1M token sticker hides reasoning burn. Cost-per-task data shows who really pays more when you factor in hidden thinking tokens, context-window blowup, and the Polymarket signal that prices Anthropic at 88% despite GPT-5.6 matching benchmarks.</itunes:summary>
      <itunes:duration>1288</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:season>1</itunes:season>
      <itunes:episode>36</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>Tencent Hy3: 295B Params, 21B Active — Can You Run It?</title>
      <description>Tencent&apos;s Apache-2.0 MoE needs 295GB+ VRAM despite 21B active params. The hardware math, the real inference tiers, and why the API economics win for most teams.</description>
      <content:encoded><![CDATA[<p>Tencent&apos;s Apache-2.0 MoE needs 295GB+ VRAM despite 21B active params. The hardware math, the real inference tiers, and why the API economics win for most teams.</p><p>Read the full article: <a href="https://computeleap.com/blog/tencent-hunyuan-hy3-open-weights-run-locally-2026">Tencent Hy3: 295B Params, 21B Active — Can You Run It?</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/tencent-hunyuan-hy3-open-weights-run-locally-2026</link>
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      <itunes:title>Tencent Hy3: 295B Params, 21B Active — Can You Run It?</itunes:title>
      <itunes:summary>Tencent&apos;s Apache-2.0 MoE needs 295GB+ VRAM despite 21B active params. The hardware math, the real inference tiers, and why the API economics win for most teams.</itunes:summary>
      <itunes:duration>1151</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>DSpark: Open-Weight Speed Without a Cerebras Contract</title>
      <description>DeepSeek dropped DSpark — a speculative decoding framework that makes V4 Flash 60-85% faster per user, no exotic hardware required. The same week OpenAI gated GPT-5.6 Sol behind government partnerships. The open-weight ecosystem is buying speed with algorithms while the West sells it with hardware contracts.</description>
      <content:encoded><![CDATA[<p>DeepSeek dropped DSpark — a speculative decoding framework that makes V4 Flash 60-85% faster per user, no exotic hardware required. The same week OpenAI gated GPT-5.6 Sol behind government partnerships. The open-weight ecosystem is buying speed with algorithms while the West sells it with hardware contracts.</p><p>Read the full article: <a href="https://computeleap.com/blog/dspark-speculative-decoding-open-weights-speed-2026">DSpark: Open-Weight Speed Without a Cerebras Contract</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/dspark-speculative-decoding-open-weights-speed-2026</link>
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      <itunes:title>DSpark: Open-Weight Speed Without a Cerebras Contract</itunes:title>
      <itunes:summary>DeepSeek dropped DSpark — a speculative decoding framework that makes V4 Flash 60-85% faster per user, no exotic hardware required. The same week OpenAI gated GPT-5.6 Sol behind government partnerships. The open-weight ecosystem is buying speed with algorithms while the West sells it with hardware contracts.</itunes:summary>
      <itunes:duration>1155</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Anthropic Walked Back the Agent SDK Credit Change</title>
      <description>Anthropic paused the June 15 Agent SDK billing split after community backlash. What happened, why it matters for operators building on Claude subscriptions, and why subscription models break when agents enter the picture.</description>
      <content:encoded><![CDATA[<p>Anthropic paused the June 15 Agent SDK billing split after community backlash. What happened, why it matters for operators building on Claude subscriptions, and why subscription models break when agents enter the picture.</p><p>Read the full article: <a href="https://agentconn.com/blog/anthropic-agent-sdk-credit-walkback-claude-p-saved-2026">Anthropic Walked Back the Agent SDK Credit Change</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/anthropic-agent-sdk-credit-walkback-claude-p-saved-2026</link>
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      <itunes:title>Anthropic Walked Back the Agent SDK Credit Change</itunes:title>
      <itunes:summary>Anthropic paused the June 15 Agent SDK billing split after community backlash. What happened, why it matters for operators building on Claude subscriptions, and why subscription models break when agents enter the picture.</itunes:summary>
      <itunes:duration>1193</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>Apple Is Paying Google ~$1B/Year to Run Siri on Gemini</title>
      <description>Apple outsourced Siri&apos;s intelligence layer to Google&apos;s Gemini models in a deal worth roughly $1 billion per year. The strategic logic, the competitive implications, and what it means for the frontier lab pecking order.</description>
      <content:encoded><![CDATA[<p>Apple outsourced Siri&apos;s intelligence layer to Google&apos;s Gemini models in a deal worth roughly $1 billion per year. The strategic logic, the competitive implications, and what it means for the frontier lab pecking order.</p><p>Read the full article: <a href="https://computeleap.com/blog/apple-paying-google-siri-gemini-outsourced-brain-2026">Apple Is Paying Google ~$1B/Year to Run Siri on Gemini</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/apple-paying-google-siri-gemini-outsourced-brain-2026</link>
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      <itunes:title>Apple Is Paying Google ~$1B/Year to Run Siri on Gemini</itunes:title>
      <itunes:summary>Apple outsourced Siri&apos;s intelligence layer to Google&apos;s Gemini models in a deal worth roughly $1 billion per year. The strategic logic, the competitive implications, and what it means for the frontier lab pecking order.</itunes:summary>
      <itunes:duration>1192</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>MDASH: How 100 Agents Beat One Frontier Model</title>
      <description>Microsoft orchestrated 100+ specialized AI agents into a 5-stage pipeline that outperformed every single-model entry on the CyberGym vulnerability benchmark. The composition-over-scale thesis, explained.</description>
      <content:encoded><![CDATA[<p>Microsoft orchestrated 100+ specialized AI agents into a 5-stage pipeline that outperformed every single-model entry on the CyberGym vulnerability benchmark. The composition-over-scale thesis, explained.</p><p>Read the full article: <a href="https://agentconn.com/blog/microsoft-mdash-multi-agent-orchestration-beats-mythos-cybergym-2026">MDASH: How 100 Agents Beat One Frontier Model</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/microsoft-mdash-multi-agent-orchestration-beats-mythos-cybergym-2026</link>
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      <itunes:title>MDASH: How 100 Agents Beat One Frontier Model</itunes:title>
      <itunes:summary>Microsoft orchestrated 100+ specialized AI agents into a 5-stage pipeline that outperformed every single-model entry on the CyberGym vulnerability benchmark. The composition-over-scale thesis, explained.</itunes:summary>
      <itunes:duration>1219</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>GLM-5.2 Local Setup: Run the Open Model Nobody Can Ban</title>
      <description>A deep dive into setting up GLM-5.2 locally — the open-weight model that runs on consumer GPUs. Hardware tiers, quantization options, and the un-bannable local inference hedge.</description>
      <content:encoded><![CDATA[<p>A deep dive into setting up GLM-5.2 locally — the open-weight model that runs on consumer GPUs. Hardware tiers, quantization options, and the un-bannable local inference hedge.</p><p>Read the full article: <a href="https://computeleap.com/blog/glm-5-2-local-setup-open-model-nobody-can-ban-2026">GLM-5.2 Local Setup: Run the Open Model Nobody Can Ban</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/glm-5-2-local-setup-open-model-nobody-can-ban-2026</link>
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      <itunes:title>GLM-5.2 Local Setup: Run the Open Model Nobody Can Ban</itunes:title>
      <itunes:summary>A deep dive into setting up GLM-5.2 locally — the open-weight model that runs on consumer GPUs. Hardware tiers, quantization options, and the un-bannable local inference hedge.</itunes:summary>
      <itunes:duration>1365</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>The Trillionaire Playbook</title>
      <description>SpaceX&apos;s $2T IPO made Musk the first trillionaire. The same day, three counterattacks launched: Warren&apos;s wealth tax, Sanders&apos; earnings cap bill, and California&apos;s $100B ballot measure. Inside the four structural moves that engineered the valuation, the institutional revolt, and the template that produced the first trillionaire.</description>
      <content:encoded><![CDATA[<p>SpaceX&apos;s $2T IPO made Musk the first trillionaire. The same day, three counterattacks launched: Warren&apos;s wealth tax, Sanders&apos; earnings cap bill, and California&apos;s $100B ballot measure. Inside the four structural moves that engineered the valuation, the institutional revolt, and the template that produced the first trillionaire.</p><p>Read the full article: <a href="https://thearcofpower.com/blog/spacex-ipo-trillionaire-wealth-tax-playbook-2026">The Trillionaire Playbook</a></p>]]></content:encoded>
      <link>https://thearcofpower.com/blog/spacex-ipo-trillionaire-wealth-tax-playbook-2026</link>
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      <pubDate>Invalid Date</pubDate>
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      <itunes:title>The Trillionaire Playbook</itunes:title>
      <itunes:summary>SpaceX&apos;s $2T IPO made Musk the first trillionaire. The same day, three counterattacks launched: Warren&apos;s wealth tax, Sanders&apos; earnings cap bill, and California&apos;s $100B ballot measure. Inside the four structural moves that engineered the valuation, the institutional revolt, and the template that produced the first trillionaire.</itunes:summary>
      <itunes:duration>18:28</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Loopcraft: Stop Prompting, Start Designing Loops</title>
      <description>The shift from prompt engineering to loop engineering. How Karpathy&apos;s autoresearch, Steinberger&apos;s twelve words, and Boris Cherny&apos;s Claude Code loops converge on the same thesis: the highest-leverage skill is designing the system that prompts your agents.</description>
      <content:encoded><![CDATA[<p>The shift from prompt engineering to loop engineering. How Karpathy&apos;s autoresearch, Steinberger&apos;s twelve words, and Boris Cherny&apos;s Claude Code loops converge on the same thesis: the highest-leverage skill is designing the system that prompts your agents.</p><p>Read the full article: <a href="https://agentconn.com/blog/loopcraft-agent-loop-design-harness-2026">Loopcraft: Stop Prompting, Start Designing Loops</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/loopcraft-agent-loop-design-harness-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/loopcraft-agent-loop-design-harness-2026</guid>
      <pubDate>Invalid Date</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/undefined" length="undefined" type="audio/mpeg"/>
      <itunes:title>Loopcraft: Stop Prompting, Start Designing Loops</itunes:title>
      <itunes:summary>The shift from prompt engineering to loop engineering. How Karpathy&apos;s autoresearch, Steinberger&apos;s twelve words, and Boris Cherny&apos;s Claude Code loops converge on the same thesis: the highest-leverage skill is designing the system that prompts your agents.</itunes:summary>
      <itunes:duration>19:38</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Is the AI Scaling Law Breaking? The Capex Math</title>
      <description>The financing window opens the same week researchers ask when scaling stops paying off. Inside the $720B capex-vs-capability tension — Lu&apos;s efficiency-doubling paper, T. Rowe Price&apos;s competitive-necessity framing, Goldman&apos;s $2T estimate, and what Chamath meant by &apos;swapped the motor, not redesigned the factory.&apos;</description>
      <content:encoded><![CDATA[<p>The financing window opens the same week researchers ask when scaling stops paying off. Inside the $720B capex-vs-capability tension — Lu&apos;s efficiency-doubling paper, T. Rowe Price&apos;s competitive-necessity framing, Goldman&apos;s $2T estimate, and what Chamath meant by &apos;swapped the motor, not redesigned the factory.&apos;</p><p>Read the full article: <a href="https://computeleap.com/blog/ai-scaling-law-breaking-capex-capability-math-2026">Is the AI Scaling Law Breaking? The Capex Math</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/ai-scaling-law-breaking-capex-capability-math-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/ai-scaling-law-breaking-capex-capability-math-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>Is the AI Scaling Law Breaking? The Capex Math</itunes:title>
      <itunes:summary>The financing window opens the same week researchers ask when scaling stops paying off. Inside the $720B capex-vs-capability tension — Lu&apos;s efficiency-doubling paper, T. Rowe Price&apos;s competitive-necessity framing, Goldman&apos;s $2T estimate, and what Chamath meant by &apos;swapped the motor, not redesigned the factory.&apos;</itunes:summary>
      <itunes:duration>20:20</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>10x PRs, 1x Reviewers: The Code-Quality Bottleneck</title>
      <description>AI agents produce 10x more PRs, but review capacity is fixed. LinearB data shows 67% failure rate on AI-generated PRs, 4.6x longer wait times. We cover FrontierCode&apos;s mergeability benchmark, Meta&apos;s RADAR risk-calibrated auto-approve, Cloudflare&apos;s seven-agent review orchestra, and the gate patterns that actually work at scale.</description>
      <content:encoded><![CDATA[<p>AI agents produce 10x more PRs, but review capacity is fixed. LinearB data shows 67% failure rate on AI-generated PRs, 4.6x longer wait times. We cover FrontierCode&apos;s mergeability benchmark, Meta&apos;s RADAR risk-calibrated auto-approve, Cloudflare&apos;s seven-agent review orchestra, and the gate patterns that actually work at scale.</p><p>Read the full article: <a href="https://agentconn.com/blog/10x-prs-1x-reviewers-code-quality-bottleneck-gate-2026">10x PRs, 1x Reviewers: The Code-Quality Bottleneck</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/10x-prs-1x-reviewers-code-quality-bottleneck-gate-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/10x-prs-1x-reviewers-code-quality-bottleneck-gate-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>10x PRs, 1x Reviewers: The Code-Quality Bottleneck</itunes:title>
      <itunes:summary>AI agents produce 10x more PRs, but review capacity is fixed. LinearB data shows 67% failure rate on AI-generated PRs, 4.6x longer wait times. We cover FrontierCode&apos;s mergeability benchmark, Meta&apos;s RADAR risk-calibrated auto-approve, Cloudflare&apos;s seven-agent review orchestra, and the gate patterns that actually work at scale.</itunes:summary>
      <itunes:duration>23:44</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Claude Fable 5 Is Mythos 5 — With a Muzzle</title>
      <description>Fable 5 and Mythos 5 share identical weights. The only difference is a classifier layer that silently falls back to Opus 4.8. We break down the same-weights architecture, the three-domain classifier, the silent fallback, and what it means that the $965B S-1 is a bet on policy wrappers, not capability.</description>
      <content:encoded><![CDATA[<p>Fable 5 and Mythos 5 share identical weights. The only difference is a classifier layer that silently falls back to Opus 4.8. We break down the same-weights architecture, the three-domain classifier, the silent fallback, and what it means that the $965B S-1 is a bet on policy wrappers, not capability.</p><p>Read the full article: <a href="https://computeleap.com/blog/claude-fable-5-mythos-5-same-weights-guardrail-2026">Claude Fable 5 Is Mythos 5 — With a Muzzle</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/claude-fable-5-mythos-5-same-weights-guardrail-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/claude-fable-5-mythos-5-same-weights-guardrail-2026</guid>
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      <itunes:title>Claude Fable 5 Is Mythos 5 — With a Muzzle</itunes:title>
      <itunes:summary>Fable 5 and Mythos 5 share identical weights. The only difference is a classifier layer that silently falls back to Opus 4.8. We break down the same-weights architecture, the three-domain classifier, the silent fallback, and what it means that the $965B S-1 is a bet on policy wrappers, not capability.</itunes:summary>
      <itunes:duration>24:08</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Anthropic and the AI Agent Shell War: Cowork, Agent View, and the Open Stack</title>
      <description>bcherny&apos;s Cowork-on-Opus-4.7 demo finally booked 8 flights end-to-end. The same week Anthropic shipped Claude Code Agent View. We argue Anthropic is contesting both the engine layer (Claude Code) AND the shell layer (Cowork + Agent View) — and the open stack (agentmemory, Voker, react-doctor, cc-switch, mattpocock/skills) is racing to fill the same surface. The 2014 container-infra playbook is running again at AI speed.</description>
      <content:encoded><![CDATA[<p>bcherny&apos;s Cowork-on-Opus-4.7 demo finally booked 8 flights end-to-end. The same week Anthropic shipped Claude Code Agent View. We argue Anthropic is contesting both the engine layer (Claude Code) AND the shell layer (Cowork + Agent View) — and the open stack (agentmemory, Voker, react-doctor, cc-switch, mattpocock/skills) is racing to fill the same surface. The 2014 container-infra playbook is running again at AI speed.</p><p>Read the full article: <a href="https://agentconn.com/blog/cowork-anthropic-shell-layer-agent-stack-may-2026">Anthropic and the AI Agent Shell War: Cowork, Agent View, and the Open Stack</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/cowork-anthropic-shell-layer-agent-stack-may-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/cowork-anthropic-shell-layer-agent-stack-may-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>Anthropic and the AI Agent Shell War: Cowork, Agent View, and the Open Stack</itunes:title>
      <itunes:summary>bcherny&apos;s Cowork-on-Opus-4.7 demo finally booked 8 flights end-to-end. The same week Anthropic shipped Claude Code Agent View. We argue Anthropic is contesting both the engine layer (Claude Code) AND the shell layer (Cowork + Agent View) — and the open stack (agentmemory, Voker, react-doctor, cc-switch, mattpocock/skills) is racing to fill the same surface. The 2014 container-infra playbook is running again at AI speed.</itunes:summary>
      <itunes:duration>21:18</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>When Students Boo and VCs Cheer: AI&apos;s Cultural Split</title>
      <description>33,096 upvotes booed AI-as-industrial-revolution rhetoric the same week Andreessen pitched a Golden Age. We unpack the 900x engagement gap between mainstream Reddit and Hacker News, the Gallup data showing Gen Z anger climbing from 22% to 31% YoY, the AI-attributed layoff acceleration, and what framings actually win on consumer-facing copy in May 2026.</description>
      <content:encoded><![CDATA[<p>33,096 upvotes booed AI-as-industrial-revolution rhetoric the same week Andreessen pitched a Golden Age. We unpack the 900x engagement gap between mainstream Reddit and Hacker News, the Gallup data showing Gen Z anger climbing from 22% to 31% YoY, the AI-attributed layoff acceleration, and what framings actually win on consumer-facing copy in May 2026.</p><p>Read the full article: <a href="https://computeleap.com/blog/students-booed-ai-andreessen-golden-age-may-2026">When Students Boo and VCs Cheer: AI&apos;s Cultural Split</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/students-booed-ai-andreessen-golden-age-may-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/students-booed-ai-andreessen-golden-age-may-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>When Students Boo and VCs Cheer: AI&apos;s Cultural Split</itunes:title>
      <itunes:summary>33,096 upvotes booed AI-as-industrial-revolution rhetoric the same week Andreessen pitched a Golden Age. We unpack the 900x engagement gap between mainstream Reddit and Hacker News, the Gallup data showing Gen Z anger climbing from 22% to 31% YoY, the AI-attributed layoff acceleration, and what framings actually win on consumer-facing copy in May 2026.</itunes:summary>
      <itunes:duration>20:21</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Local AI Just Became the Default: Gemma 4 + omlx on M4</title>
      <description>Gemma 4 31B is the new local baseline on M4 24GB. omlx ships LLM inference as a menu-bar app. We walk through why &quot;local-as-default&quot; stopped being a science experiment in May 2026, the omlx KV-cache architecture (RAM + SSD tiered, continuous batching, drop-in OpenAI/Anthropic APIs), and the substrate shift that puts Apple Silicon ahead of the GPU stack.</description>
      <content:encoded><![CDATA[<p>Gemma 4 31B is the new local baseline on M4 24GB. omlx ships LLM inference as a menu-bar app. We walk through why &quot;local-as-default&quot; stopped being a science experiment in May 2026, the omlx KV-cache architecture (RAM + SSD tiered, continuous batching, drop-in OpenAI/Anthropic APIs), and the substrate shift that puts Apple Silicon ahead of the GPU stack.</p><p>Read the full article: <a href="https://computeleap.com/blog/local-ai-default-gemma-4-m4-omlx-menubar-2026">Local AI Just Became the Default: Gemma 4 + omlx on M4</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/local-ai-default-gemma-4-m4-omlx-menubar-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/local-ai-default-gemma-4-m4-omlx-menubar-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>Local AI Just Became the Default: Gemma 4 + omlx on M4</itunes:title>
      <itunes:summary>Gemma 4 31B is the new local baseline on M4 24GB. omlx ships LLM inference as a menu-bar app. We walk through why &quot;local-as-default&quot; stopped being a science experiment in May 2026, the omlx KV-cache architecture (RAM + SSD tiered, continuous batching, drop-in OpenAI/Anthropic APIs), and the substrate shift that puts Apple Silicon ahead of the GPU stack.</itunes:summary>
      <itunes:duration>22:39</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>The Agent Judge Layer: Validation Becomes Infrastructure</title>
      <description>Lindy, JP Morgan, and OpenAI all shipped a separate judge layer for production agents in Q2 2026. When three orgs in unrelated verticals land on the same architecture, it&apos;s a category, not a fad. We unpack the actor-judge split, the replay-vs-snapshot durability debate from Trigger.dev&apos;s Eric Allam, and how react-doctor + agentmemory fit into the same runtime-validation shape — plus the 90-day prediction.</description>
      <content:encoded><![CDATA[<p>Lindy, JP Morgan, and OpenAI all shipped a separate judge layer for production agents in Q2 2026. When three orgs in unrelated verticals land on the same architecture, it&apos;s a category, not a fad. We unpack the actor-judge split, the replay-vs-snapshot durability debate from Trigger.dev&apos;s Eric Allam, and how react-doctor + agentmemory fit into the same runtime-validation shape — plus the 90-day prediction.</p><p>Read the full article: <a href="https://agentconn.com/blog/agent-judge-layer-runtime-validation-prod-tier-2026">The Agent Judge Layer: Validation Becomes Infrastructure</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/agent-judge-layer-runtime-validation-prod-tier-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/agent-judge-layer-runtime-validation-prod-tier-2026</guid>
      <pubDate>Invalid Date</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/undefined" length="undefined" type="audio/mpeg"/>
      <itunes:title>The Agent Judge Layer: Validation Becomes Infrastructure</itunes:title>
      <itunes:summary>Lindy, JP Morgan, and OpenAI all shipped a separate judge layer for production agents in Q2 2026. When three orgs in unrelated verticals land on the same architecture, it&apos;s a category, not a fad. We unpack the actor-judge split, the replay-vs-snapshot durability debate from Trigger.dev&apos;s Eric Allam, and how react-doctor + agentmemory fit into the same runtime-validation shape — plus the 90-day prediction.</itunes:summary>
      <itunes:duration>21:42</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Sovereign Compute, Sovereign Army: The 2026 Through-Line</title>
      <description>Jack Clark (Anthropic) floated &quot;Radical Optionality&quot; — government builds compute as state capacity rather than outsourcing it. Same week: Spain calls for an EU army; Netanyahu phases out US military aid. We read the cross-asset signal as sovereign capacity is the 2026 through-line, with a prediction-market hook on whether Anthropic publicly endorses Pentagon procurement in 60 days.</description>
      <content:encoded><![CDATA[<p>Jack Clark (Anthropic) floated &quot;Radical Optionality&quot; — government builds compute as state capacity rather than outsourcing it. Same week: Spain calls for an EU army; Netanyahu phases out US military aid. We read the cross-asset signal as sovereign capacity is the 2026 through-line, with a prediction-market hook on whether Anthropic publicly endorses Pentagon procurement in 60 days.</p><p>Read the full article: <a href="https://thearcofpower.com/blog/sovereign-compute-radical-optionality-eu-army-through-line-2026">Sovereign Compute, Sovereign Army: The 2026 Through-Line</a></p>]]></content:encoded>
      <link>https://thearcofpower.com/blog/sovereign-compute-radical-optionality-eu-army-through-line-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/sovereign-compute-radical-optionality-eu-army-through-line-2026</guid>
      <pubDate>Invalid Date</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/undefined" length="undefined" type="audio/mpeg"/>
      <itunes:title>Sovereign Compute, Sovereign Army: The 2026 Through-Line</itunes:title>
      <itunes:summary>Jack Clark (Anthropic) floated &quot;Radical Optionality&quot; — government builds compute as state capacity rather than outsourcing it. Same week: Spain calls for an EU army; Netanyahu phases out US military aid. We read the cross-asset signal as sovereign capacity is the 2026 through-line, with a prediction-market hook on whether Anthropic publicly endorses Pentagon procurement in 60 days.</itunes:summary>
      <itunes:duration>20:23</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>DeepSeek-TUI Setup Guide: The Rust Coding Agent on V4 Flash</title>
      <description>DeepSeek-TUI hit 5,787 GitHub stars in a single day on May 7. We walk through the install (npm, cargo, brew, Docker), V4 Flash configuration, the three execution modes (Plan, Agent, YOLO), the four errors that account for most first-week issues, and the decision matrix for when to pick this harness vs Claude Code or cc-switch.</description>
      <content:encoded><![CDATA[<p>DeepSeek-TUI hit 5,787 GitHub stars in a single day on May 7. We walk through the install (npm, cargo, brew, Docker), V4 Flash configuration, the three execution modes (Plan, Agent, YOLO), the four errors that account for most first-week issues, and the decision matrix for when to pick this harness vs Claude Code or cc-switch.</p><p>Read the full article: <a href="https://computeleap.com/blog/deepseek-tui-setup-guide-rust-coding-agent-2026">DeepSeek-TUI Setup Guide: The Rust Coding Agent on V4 Flash</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/deepseek-tui-setup-guide-rust-coding-agent-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/deepseek-tui-setup-guide-rust-coding-agent-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>DeepSeek-TUI Setup Guide: The Rust Coding Agent on V4 Flash</itunes:title>
      <itunes:summary>DeepSeek-TUI hit 5,787 GitHub stars in a single day on May 7. We walk through the install (npm, cargo, brew, Docker), V4 Flash configuration, the three execution modes (Plan, Agent, YOLO), the four errors that account for most first-week issues, and the decision matrix for when to pick this harness vs Claude Code or cc-switch.</itunes:summary>
      <itunes:duration>21:30</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Vectorless RAG: PageIndex vs Embedding-Based Retrieval — When to Switch</title>
      <description>VectifyAI/PageIndex picked up 953 stars in a single day on May 7 with a six-word repo description. The pitch is structural: no embeddings, no chunking, no vector DB — tree search instead. We cover what vectorless actually means, what you give up vs embedding RAG, and the workload-axis decision framework that picks one over the other.</description>
      <content:encoded><![CDATA[<p>VectifyAI/PageIndex picked up 953 stars in a single day on May 7 with a six-word repo description. The pitch is structural: no embeddings, no chunking, no vector DB — tree search instead. We cover what vectorless actually means, what you give up vs embedding RAG, and the workload-axis decision framework that picks one over the other.</p><p>Read the full article: <a href="https://agentconn.com/blog/vectorless-rag-pageindex-vs-embedding-rag-decision-guide-2026">Vectorless RAG: PageIndex vs Embedding-Based Retrieval — When to Switch</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/vectorless-rag-pageindex-vs-embedding-rag-decision-guide-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/vectorless-rag-pageindex-vs-embedding-rag-decision-guide-2026</guid>
      <pubDate>Invalid Date</pubDate>
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      <itunes:title>Vectorless RAG: PageIndex vs Embedding-Based Retrieval — When to Switch</itunes:title>
      <itunes:summary>VectifyAI/PageIndex picked up 953 stars in a single day on May 7 with a six-word repo description. The pitch is structural: no embeddings, no chunking, no vector DB — tree search instead. We cover what vectorless actually means, what you give up vs embedding RAG, and the workload-axis decision framework that picks one over the other.</itunes:summary>
      <itunes:duration>22:40</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Build Your Own Agentic OS: Phone, Pi, or MacBook in 2026</title>
      <description>Three Claude Code stacks compared — phone via web UI, Raspberry Pi headless, MacBook power-user. Simon Willison ships from his iPhone while camping; the Pi tier runs 24/7 for $120. We walk through who each tier is for, where the rate-limit cliffs live, and how to layer them.</description>
      <content:encoded><![CDATA[<p>Three Claude Code stacks compared — phone via web UI, Raspberry Pi headless, MacBook power-user. Simon Willison ships from his iPhone while camping; the Pi tier runs 24/7 for $120. We walk through who each tier is for, where the rate-limit cliffs live, and how to layer them.</p><p>Read the full article: <a href="https://computeleap.com/blog/build-your-own-agentic-os-claude-code-phone-pi-macbook-2026">Build Your Own Agentic OS: Phone, Pi, or MacBook in 2026</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/build-your-own-agentic-os-claude-code-phone-pi-macbook-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/build-your-own-agentic-os-claude-code-phone-pi-macbook-2026</guid>
      <pubDate>Invalid Date</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/undefined" length="undefined" type="audio/mpeg"/>
      <itunes:title>Build Your Own Agentic OS: Phone, Pi, or MacBook in 2026</itunes:title>
      <itunes:summary>Three Claude Code stacks compared — phone via web UI, Raspberry Pi headless, MacBook power-user. Simon Willison ships from his iPhone while camping; the Pi tier runs 24/7 for $120. We walk through who each tier is for, where the rate-limit cliffs live, and how to layer them.</itunes:summary>
      <itunes:duration>22:02</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>GStack: Garry Tan&apos;s Claude Code Setup That Turns One Developer Into a Team</title>
      <description>GStack is Garry Tan&apos;s open-source Claude Code harness — 23 specialist skills that give you a CEO, Eng Manager, Designer, QA, and Security Auditor in one paste. We cover how it works, the 810x productivity claim, the &apos;just prompts&apos; criticism, and when to use GStack vs oh-my-openagent.</description>
      <content:encoded><![CDATA[<p>GStack is Garry Tan&apos;s open-source Claude Code harness — 23 specialist skills that give you a CEO, Eng Manager, Designer, QA, and Security Auditor in one paste. We cover how it works, the 810x productivity claim, the &apos;just prompts&apos; criticism, and when to use GStack vs oh-my-openagent.</p><p>Read the full article: <a href="https://agentconn.com/blog/gstack-claude-code-harness-open-source-2026">GStack: Garry Tan&apos;s Claude Code Setup That Turns One Developer Into a Team</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/gstack-claude-code-harness-open-source-2026</link>
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      <itunes:title>GStack: Garry Tan&apos;s Claude Code Setup That Turns One Developer Into a Team</itunes:title>
      <itunes:summary>GStack is Garry Tan&apos;s open-source Claude Code harness — 23 specialist skills that give you a CEO, Eng Manager, Designer, QA, and Security Auditor in one paste. We cover how it works, the 810x productivity claim, the &apos;just prompts&apos; criticism, and when to use GStack vs oh-my-openagent.</itunes:summary>
      <itunes:duration>21:42</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>DeepSeek V4 vs GPT-5.5 vs Claude Opus 4.7: The Developer&apos;s Model Comparison Guide</title>
      <description>DeepSeek V4 dropped today with 1M context at 1/6th the cost of Claude and GPT-5.5. We break down benchmarks, cost math, and give you a routing framework for each model.</description>
      <content:encoded><![CDATA[<p>DeepSeek V4 dropped today with 1M context at 1/6th the cost of Claude and GPT-5.5. We break down benchmarks, cost math, and give you a routing framework for each model.</p><p>Read the full article: <a href="https://computeleap.com/blog/deepseek-v4-vs-gpt-55-vs-claude-opus-47-model-comparison-2026">DeepSeek V4 vs GPT-5.5 vs Claude Opus 4.7: The Developer&apos;s Model Comparison Guide</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/deepseek-v4-vs-gpt-55-vs-claude-opus-47-model-comparison-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/deepseek-v4-vs-gpt-55-vs-claude-opus-47-model-comparison-2026</guid>
      <pubDate>Invalid Date</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/undefined" length="undefined" type="audio/mpeg"/>
      <itunes:title>DeepSeek V4 vs GPT-5.5 vs Claude Opus 4.7: The Developer&apos;s Model Comparison Guide</itunes:title>
      <itunes:summary>DeepSeek V4 dropped today with 1M context at 1/6th the cost of Claude and GPT-5.5. We break down benchmarks, cost math, and give you a routing framework for each model.</itunes:summary>
      <itunes:duration>19:40</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Stackable Skills: One Prompt, Your Whole Team</title>
      <description>Bolt shipped stackable team skills. But the real lesson from AgentSkillOS research: DAG composition outperforms flat invocation with identical skills. Two AI hosts break down the composition patterns that hold up, the double-run problem nobody talks about, and why the orchestration layer is a control point.</description>
      <content:encoded><![CDATA[<p>Bolt shipped stackable team skills. But the real lesson from AgentSkillOS research: DAG composition outperforms flat invocation with identical skills. Two AI hosts break down the composition patterns that hold up, the double-run problem nobody talks about, and why the orchestration layer is a control point.</p><p>Read the full article: <a href="https://agentconn.com/blog/stackable-skills-one-prompt-fires-whole-skill-team-2026">Stackable Skills: One Prompt, Your Whole Team</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/stackable-skills-one-prompt-fires-whole-skill-team-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/stackable-skills-one-prompt-fires-whole-skill-team</guid>
      <pubDate>Thu, 23 Jul 2026 04:58:00 GMT</pubDate>
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      <itunes:title>Stackable Skills: One Prompt, Your Whole Team</itunes:title>
      <itunes:summary>Bolt shipped stackable team skills. But the real lesson from AgentSkillOS research: DAG composition outperforms flat invocation with identical skills. Two AI hosts break down the composition patterns that hold up, the double-run problem nobody talks about, and why the orchestration layer is a control point.</itunes:summary>
      <itunes:duration>25:11</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>36</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Muse Spark 1.1 Lands with a $1.25 API and Day-One CLI</title>
      <description>Meta ships its first paid model API. Simon Willison ships a plugin the same afternoon. Here is what builders need to know.</description>
      <content:encoded><![CDATA[<p>Meta ships its first paid model API. Simon Willison ships a plugin the same afternoon. Here is what builders need to know.</p><p>Read the full article: <a href="https://computeleap.com/blog/meta-muse-spark-open-weight-frontier">Muse Spark 1.1 Lands with a $1.25 API and Day-One CLI</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/meta-muse-spark-open-weight-frontier</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/meta-muse-spark-open-weight-frontier</guid>
      <pubDate>Fri, 10 Jul 2026 10:10:00 GMT</pubDate>
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      <itunes:title>Muse Spark 1.1 Lands with a $1.25 API and Day-One CLI</itunes:title>
      <itunes:summary>Meta ships its first paid model API. Simon Willison ships a plugin the same afternoon. Here is what builders need to know.</itunes:summary>
      <itunes:duration>21:46</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>35</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Google&apos;s $40B Anthropic Bet: What It Means for Developers</title>
      <description>Google&apos;s $40B Anthropic investment loops back as Google Cloud spend — a circular finance deal that guarantees 5 gigawatts of TPU compute. Two AI hosts break down the deal structure, what Claude Mythos signals about the next model tier, and how to position your Claude app for the capacity wave.</description>
      <content:encoded><![CDATA[<p>Google&apos;s $40B Anthropic investment loops back as Google Cloud spend — a circular finance deal that guarantees 5 gigawatts of TPU compute. Two AI hosts break down the deal structure, what Claude Mythos signals about the next model tier, and how to position your Claude app for the capacity wave.</p><p>Read the full article: <a href="https://computeleap.com/blog/google-40b-anthropic-investment-circular-deal-developers">Google&apos;s $40B Anthropic Bet: What It Means for Developers</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/google-40b-anthropic-investment-circular-deal-developers</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/google-40b-anthropic-investment-circular-deal-developers</guid>
      <pubDate>Sun, 26 Apr 2026 04:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/google-40b-anthropic-investment-circular-deal-developers.mp3" length="35910459" type="audio/mpeg"/>
      <itunes:title>Google&apos;s $40B Anthropic Bet: What It Means for Developers</itunes:title>
      <itunes:summary>Google&apos;s $40B Anthropic investment loops back as Google Cloud spend — a circular finance deal that guarantees 5 gigawatts of TPU compute. Two AI hosts break down the deal structure, what Claude Mythos signals about the next model tier, and how to position your Claude app for the capacity wave.</itunes:summary>
      <itunes:duration>36:31</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>13</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Meta&apos;s Real Story: The Surveillance, Not the Layoffs</title>
      <description>Meta cut 10%, Microsoft bought out 7%, Block gutted 40%. Two AI hosts argue the real story isn&apos;t the layoff wave - it&apos;s Meta&apos;s MCI program, which began installing keystroke + screenshot surveillance on remaining employees two days BEFORE the layoffs. The 18-month thesis: every Fortune 500 will pilot a version of this within 18 months.</description>
      <content:encoded><![CDATA[<p>Meta cut 10%, Microsoft bought out 7%, Block gutted 40%. Two AI hosts argue the real story isn&apos;t the layoff wave - it&apos;s Meta&apos;s MCI program, which began installing keystroke + screenshot surveillance on remaining employees two days BEFORE the layoffs. The 18-month thesis: every Fortune 500 will pilot a version of this within 18 months.</p><p>Read the full article: <a href="https://www.computeleap.com/blog/meta-surveillance-tech-layoffs-2026/">Meta&apos;s Real Story: The Surveillance, Not the Layoffs</a></p>]]></content:encoded>
      <link>https://www.computeleap.com/blog/meta-surveillance-tech-layoffs-2026/</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/meta-surveillance-tech-layoffs-2026</guid>
      <pubDate>Sat, 25 Apr 2026 00:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/meta-surveillance-tech-layoffs-2026.mp3" length="36361155" type="audio/mpeg"/>
      <itunes:title>Meta&apos;s Real Story: The Surveillance, Not the Layoffs</itunes:title>
      <itunes:summary>Meta cut 10%, Microsoft bought out 7%, Block gutted 40%. Two AI hosts argue the real story isn&apos;t the layoff wave - it&apos;s Meta&apos;s MCI program, which began installing keystroke + screenshot surveillance on remaining employees two days BEFORE the layoffs. The 18-month thesis: every Fortune 500 will pilot a version of this within 18 months.</itunes:summary>
      <itunes:duration>18:50</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>12</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Shannon AI: The $50 Autonomous Hacker That Actually Breaks Into Your App</title>
      <description>Shannon is an open-source AI pentesting agent that autonomously tests web apps for vulnerabilities — and only reports what it can prove with a working exploit. Two AI hosts break down how Shannon works, its 96.15% XBOW benchmark score, the economics vs traditional pentesting, and why the Bitwarden supply chain attack is exactly what Shannon can&apos;t catch.</description>
      <content:encoded><![CDATA[<p>Shannon is an open-source AI pentesting agent that autonomously tests web apps for vulnerabilities — and only reports what it can prove with a working exploit. Two AI hosts break down how Shannon works, its 96.15% XBOW benchmark score, the economics vs traditional pentesting, and why the Bitwarden supply chain attack is exactly what Shannon can&apos;t catch.</p><p>Read the full article: <a href="https://agentconn.com/blog/shannon-ai-pentester-review-autonomous-web-security-2026">Shannon AI: The $50 Autonomous Hacker That Actually Breaks Into Your App</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/shannon-ai-pentester-review-autonomous-web-security-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/shannon-ai-pentester-review-autonomous-web-security-2026</guid>
      <pubDate>Fri, 24 Apr 2026 05:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/shannon-ai-pentester-review-autonomous-web-security-2026.mp3" length="43244563" type="audio/mpeg"/>
      <itunes:title>Shannon AI: The $50 Autonomous Hacker That Actually Breaks Into Your App</itunes:title>
      <itunes:summary>Shannon is an open-source AI pentesting agent that autonomously tests web apps for vulnerabilities — and only reports what it can prove with a working exploit. Two AI hosts break down how Shannon works, its 96.15% XBOW benchmark score, the economics vs traditional pentesting, and why the Bitwarden supply chain attack is exactly what Shannon can&apos;t catch.</itunes:summary>
      <itunes:duration>22:23</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>11</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>GPT-5.5 vs Claude Code: Which AI Should You Use?</title>
      <description>GPT-5.5 launched with agentic-first positioning. We benchmark it head-to-head against Claude Code across solo dev, team, and enterprise setups — covering benchmarks, the pricing drama, and the three use cases where each tool wins.</description>
      <content:encoded><![CDATA[<p>GPT-5.5 launched with agentic-first positioning. We benchmark it head-to-head against Claude Code across solo dev, team, and enterprise setups — covering benchmarks, the pricing drama, and the three use cases where each tool wins.</p><p>Read the full article: <a href="https://computeleap.com/blog/gpt-5-5-vs-claude-code-agentic-coding-ai-2026">GPT-5.5 vs Claude Code: Which AI Should You Use?</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/gpt-5-5-vs-claude-code-agentic-coding-ai-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/gpt-5-5-vs-claude-code-agentic-coding-ai-2026</guid>
      <pubDate>Fri, 24 Apr 2026 03:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/gpt-5-5-vs-claude-code-agentic-coding-ai-2026.mp3" length="36799036" type="audio/mpeg"/>
      <itunes:title>GPT-5.5 vs Claude Code: Which AI Should You Use?</itunes:title>
      <itunes:summary>GPT-5.5 launched with agentic-first positioning. We benchmark it head-to-head against Claude Code across solo dev, team, and enterprise setups — covering benchmarks, the pricing drama, and the three use cases where each tool wins.</itunes:summary>
      <itunes:duration>19:03</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>10</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Claude Code Agentic Stack: cc-switch &amp; claude-context MCP</title>
      <description>The 2026 agentic developer stack is three layers: Claude Code as the execution engine, cc-switch as the multi-provider CLI manager, and claude-context MCP as the semantic code search layer. Two AI hosts walk through the full setup — cc-switch 50+ presets, claude-context&apos;s AST-aware search, and the local proxy failover that keeps your workflow running when one provider rate-limits.</description>
      <content:encoded><![CDATA[<p>The 2026 agentic developer stack is three layers: Claude Code as the execution engine, cc-switch as the multi-provider CLI manager, and claude-context MCP as the semantic code search layer. Two AI hosts walk through the full setup — cc-switch 50+ presets, claude-context&apos;s AST-aware search, and the local proxy failover that keeps your workflow running when one provider rate-limits.</p><p>Read the full article: <a href="https://computeleap.com/blog/claude-code-agentic-dev-stack-2026">Claude Code Agentic Stack: cc-switch &amp; claude-context MCP</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/claude-code-agentic-dev-stack-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/claude-code-agentic-dev-stack-2026</guid>
      <pubDate>Thu, 23 Apr 2026 04:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/claude-code-agentic-dev-stack-2026.mp3" length="39485567" type="audio/mpeg"/>
      <itunes:title>Claude Code Agentic Stack: cc-switch &amp; claude-context MCP</itunes:title>
      <itunes:summary>The 2026 agentic developer stack is three layers: Claude Code as the execution engine, cc-switch as the multi-provider CLI manager, and claude-context MCP as the semantic code search layer. Two AI hosts walk through the full setup — cc-switch 50+ presets, claude-context&apos;s AST-aware search, and the local proxy failover that keeps your workflow running when one provider rate-limits.</itunes:summary>
      <itunes:duration>20:26</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>9</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>Self-Evolving AI Agents: deer-flow, evolver, and GenericAgent Compared</title>
      <description>Three self-evolving agent frameworks hit GitHub&apos;s global top 10 simultaneously. Two AI hosts break down deer-flow (ByteDance&apos;s 62.8k-star SuperAgent harness), evolver&apos;s Genome Evolution Protocol, and GenericAgent&apos;s 6x token efficiency — with a deep dive on the security risks no one mentions and a decision matrix for production deployments.</description>
      <content:encoded><![CDATA[<p>Three self-evolving agent frameworks hit GitHub&apos;s global top 10 simultaneously. Two AI hosts break down deer-flow (ByteDance&apos;s 62.8k-star SuperAgent harness), evolver&apos;s Genome Evolution Protocol, and GenericAgent&apos;s 6x token efficiency — with a deep dive on the security risks no one mentions and a decision matrix for production deployments.</p><p>Read the full article: <a href="https://agentconn.com/blog/self-evolving-ai-agents-evolver-genericagent-deerflow-comparison-2026">Self-Evolving AI Agents: deer-flow, evolver, and GenericAgent Compared</a></p>]]></content:encoded>
      <link>https://agentconn.com/blog/self-evolving-ai-agents-evolver-genericagent-deerflow-comparison-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/self-evolving-ai-agents-evolver-genericagent-deerflow-comparison-2026</guid>
      <pubDate>Mon, 20 Apr 2026 04:30:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/self-evolving-ai-agents-evolver-genericagent-deerflow-comparison-2026.mp3" length="43925347" type="audio/mpeg"/>
      <itunes:title>Self-Evolving AI Agents: deer-flow, evolver, and GenericAgent Compared</itunes:title>
      <itunes:summary>Three self-evolving agent frameworks hit GitHub&apos;s global top 10 simultaneously. Two AI hosts break down deer-flow (ByteDance&apos;s 62.8k-star SuperAgent harness), evolver&apos;s Genome Evolution Protocol, and GenericAgent&apos;s 6x token efficiency — with a deep dive on the security risks no one mentions and a decision matrix for production deployments.</itunes:summary>
      <itunes:duration>22:44</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>8</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>The New OpenAI Agents Python SDK</title>
      <description>OpenAI&apos;s openai-agents-python hit #2 on GitHub trending with 22,981 stars. Two AI hosts break down the hands-on details: handoffs vs agent-as-tool patterns, guardrails with tripwire mode, MCP integration, and a full 3-agent Researcher→Writer→Reviewer pipeline. Plus an honest cost comparison vs Claude SDK for long-horizon sessions.</description>
      <content:encoded><![CDATA[<p>OpenAI&apos;s openai-agents-python hit #2 on GitHub trending with 22,981 stars. Two AI hosts break down the hands-on details: handoffs vs agent-as-tool patterns, guardrails with tripwire mode, MCP integration, and a full 3-agent Researcher→Writer→Reviewer pipeline. Plus an honest cost comparison vs Claude SDK for long-horizon sessions.</p><p>Read the full article: <a href="https://computeleap.com/blog/openai-agents-python-tutorial-multi-agent-ai-workflows-2026">The New OpenAI Agents Python SDK</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/openai-agents-python-tutorial-multi-agent-ai-workflows-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/openai-agents-python-tutorial-multi-agent-ai-workflows-2026</guid>
      <pubDate>Mon, 20 Apr 2026 04:00:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/openai-agents-python-tutorial-multi-agent-ai-workflows-2026.mp3" length="39503496" type="audio/mpeg"/>
      <itunes:title>The New OpenAI Agents Python SDK</itunes:title>
      <itunes:summary>OpenAI&apos;s openai-agents-python hit #2 on GitHub trending with 22,981 stars. Two AI hosts break down the hands-on details: handoffs vs agent-as-tool patterns, guardrails with tripwire mode, MCP integration, and a full 3-agent Researcher→Writer→Reviewer pipeline. Plus an honest cost comparison vs Claude SDK for long-horizon sessions.</itunes:summary>
      <itunes:duration>20:27</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>7</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
    </item>
    <item>
      <title>AI Is Fleeing San Francisco for Space</title>
      <description>After the Molotov attack on Altman and the &apos;Luigi-ing&apos; CEO rhetoric, the NotebookLM hosts unpack the three vectors pushing frontier AI&apos;s center of gravity East: violent US anti-AI sentiment, Hormuz energy fragility (Iran re-closed the strait the day we published), and the 83%-vs-39% sentiment gap with China. Plus the diffusion-not-exodus thesis — Texas, Tennessee, Abu Dhabi, and the orbital-compute hedge where the US lead is widening.</description>
      <content:encoded><![CDATA[<p>After the Molotov attack on Altman and the &apos;Luigi-ing&apos; CEO rhetoric, the NotebookLM hosts unpack the three vectors pushing frontier AI&apos;s center of gravity East: violent US anti-AI sentiment, Hormuz energy fragility (Iran re-closed the strait the day we published), and the 83%-vs-39% sentiment gap with China. Plus the diffusion-not-exodus thesis — Texas, Tennessee, Abu Dhabi, and the orbital-compute hedge where the US lead is widening.</p><p>Read the full article: <a href="https://www.computeleap.com/blog/ai-backlash-violence-china-shift-2026">AI Is Fleeing San Francisco for Space</a></p>]]></content:encoded>
      <link>https://www.computeleap.com/blog/ai-backlash-violence-china-shift-2026</link>
      <guid isPermaLink="false">https://www.computeleap.com/podcast/ai-backlash-violence-china-shift-2026</guid>
      <pubDate>Sun, 19 Apr 2026 05:30:00 GMT</pubDate>
      <enclosure url="https://raw.githubusercontent.com/Yuqingli/blog-assets/main/podcasts/ai-backlash-violence-china-shift-2026.mp3" length="36391784" type="audio/mpeg"/>
      <itunes:title>AI Is Fleeing San Francisco for Space</itunes:title>
      <itunes:summary>After the Molotov attack on Altman and the &apos;Luigi-ing&apos; CEO rhetoric, the NotebookLM hosts unpack the three vectors pushing frontier AI&apos;s center of gravity East: violent US anti-AI sentiment, Hormuz energy fragility (Iran re-closed the strait the day we published), and the 83%-vs-39% sentiment gap with China. Plus the diffusion-not-exodus thesis — Texas, Tennessee, Abu Dhabi, and the orbital-compute hedge where the US lead is widening.</itunes:summary>
      <itunes:duration>18:50</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
      <itunes:explicit>false</itunes:explicit>
      <itunes:season>1</itunes:season>
      <itunes:episode>6</itunes:episode>
      <itunes:episodeType>full</itunes:episodeType>
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    <item>
      <title>How Claude Design Tanked Figma Stock</title>
      <description>Anthropic Labs shipped Claude Design — an AI UI tool with a &apos;Handoff to Claude Code&apos; button that passes generated designs directly into agentic workflows. HN #2 story at 423 points. Figma stock dropped 15%. Two AI hosts break down what the tool actually does, why the handoff integration changes the design-to-deployment stack, and what the &apos;homogeneity of the modern web&apos; debate reveals about Claude Design&apos;s ceiling.</description>
      <content:encoded><![CDATA[<p>Anthropic Labs shipped Claude Design — an AI UI tool with a &apos;Handoff to Claude Code&apos; button that passes generated designs directly into agentic workflows. HN #2 story at 423 points. Figma stock dropped 15%. Two AI hosts break down what the tool actually does, why the handoff integration changes the design-to-deployment stack, and what the &apos;homogeneity of the modern web&apos; debate reveals about Claude Design&apos;s ceiling.</p><p>Read the full article: <a href="https://computeleap.com/blog/claude-design-anthropic-ai-design-tool-handoff-claude-code">How Claude Design Tanked Figma Stock</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/claude-design-anthropic-ai-design-tool-handoff-claude-code</link>
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      <pubDate>Sat, 18 Apr 2026 04:36:00 GMT</pubDate>
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      <itunes:title>How Claude Design Tanked Figma Stock</itunes:title>
      <itunes:summary>Anthropic Labs shipped Claude Design — an AI UI tool with a &apos;Handoff to Claude Code&apos; button that passes generated designs directly into agentic workflows. HN #2 story at 423 points. Figma stock dropped 15%. Two AI hosts break down what the tool actually does, why the handoff integration changes the design-to-deployment stack, and what the &apos;homogeneity of the modern web&apos; debate reveals about Claude Design&apos;s ceiling.</itunes:summary>
      <itunes:duration>18:52</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <title>Claude Managed Agents Remove the Infrastructure Bottleneck</title>
      <description>Anthropic launched Claude Managed Agents on April 8, 2026 — eliminating the scaffolding layer that consumed 60-80% of agent dev time. Two AI hosts break down what infrastructure actually gets replaced, the $0.08/session-hour pricing, and whether Notion, Rakuten, and Asana&apos;s early bets pay off.</description>
      <content:encoded><![CDATA[<p>Anthropic launched Claude Managed Agents on April 8, 2026 — eliminating the scaffolding layer that consumed 60-80% of agent dev time. Two AI hosts break down what infrastructure actually gets replaced, the $0.08/session-hour pricing, and whether Notion, Rakuten, and Asana&apos;s early bets pay off.</p><p>Read the full article: <a href="https://computeleap.com/blog/claude-managed-agents-build-ai-agents-no-code">Claude Managed Agents Remove the Infrastructure Bottleneck</a></p>]]></content:encoded>
      <link>https://computeleap.com/blog/claude-managed-agents-build-ai-agents-no-code</link>
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      <pubDate>Sun, 12 Apr 2026 05:00:00 GMT</pubDate>
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      <itunes:title>Claude Managed Agents Remove the Infrastructure Bottleneck</itunes:title>
      <itunes:summary>Anthropic launched Claude Managed Agents on April 8, 2026 — eliminating the scaffolding layer that consumed 60-80% of agent dev time. Two AI hosts break down what infrastructure actually gets replaced, the $0.08/session-hour pricing, and whether Notion, Rakuten, and Asana&apos;s early bets pay off.</itunes:summary>
      <itunes:duration>20:46</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:episode>3</itunes:episode>
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      <title>The 14 Billion Dollar Muse Spark Pivot</title>
      <description>Meta abandoned open weights with Muse Spark — their first closed frontier model. The Artificial Analysis Intelligence Index puts it at 52, behind only Gemini 3.1 Pro and GPT-5.4. Two AI hosts break down whether the 16-tool agent suite justifies routing production workloads to a closed model with no open API.</description>
      <content:encoded><![CDATA[<p>Meta abandoned open weights with Muse Spark — their first closed frontier model. The Artificial Analysis Intelligence Index puts it at 52, behind only Gemini 3.1 Pro and GPT-5.4. Two AI hosts break down whether the 16-tool agent suite justifies routing production workloads to a closed model with no open API.</p><p>Read the full article: <a href="https://agentconn.com/blog/meta-muse-spark-review-frontier-model">The 14 Billion Dollar Muse Spark Pivot</a></p>]]></content:encoded>
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      <pubDate>Sun, 12 Apr 2026 05:00:00 GMT</pubDate>
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      <itunes:title>The 14 Billion Dollar Muse Spark Pivot</itunes:title>
      <itunes:summary>Meta abandoned open weights with Muse Spark — their first closed frontier model. The Artificial Analysis Intelligence Index puts it at 52, behind only Gemini 3.1 Pro and GPT-5.4. Two AI hosts break down whether the 16-tool agent suite justifies routing production workloads to a closed model with no open API.</itunes:summary>
      <itunes:duration>21:19</itunes:duration>
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      <itunes:episode>4</itunes:episode>
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      <title>How Anthropic Toppled the OpenAI Empire</title>
      <description>The Anthropic vs OpenAI rivalry reached a tipping point in March 2026. Polymarket gives Anthropic 100% odds for best model. ChatGPT share collapsed from 69% to 45%. Claude Code hit $2.5B ARR in 9 months. Two AI hosts break down the Pentagon dominos, Dario&apos;s WSJ bombshell, and what could still go wrong.</description>
      <content:encoded><![CDATA[<p>The Anthropic vs OpenAI rivalry reached a tipping point in March 2026. Polymarket gives Anthropic 100% odds for best model. ChatGPT share collapsed from 69% to 45%. Claude Code hit $2.5B ARR in 9 months. Two AI hosts break down the Pentagon dominos, Dario&apos;s WSJ bombshell, and what could still go wrong.</p><p>Read the full article: <a href="https://www.computeleap.com/blog/anthropic-vs-openai-rivalry-2026/">How Anthropic Toppled the OpenAI Empire</a></p>]]></content:encoded>
      <link>https://www.computeleap.com/blog/anthropic-vs-openai-rivalry-2026/</link>
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      <pubDate>Mon, 30 Mar 2026 08:00:00 GMT</pubDate>
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      <itunes:title>How Anthropic Toppled the OpenAI Empire</itunes:title>
      <itunes:summary>The Anthropic vs OpenAI rivalry reached a tipping point in March 2026. Polymarket gives Anthropic 100% odds for best model. ChatGPT share collapsed from 69% to 45%. Claude Code hit $2.5B ARR in 9 months. Two AI hosts break down the Pentagon dominos, Dario&apos;s WSJ bombshell, and what could still go wrong.</itunes:summary>
      <itunes:duration>20:19</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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      <itunes:episode>2</itunes:episode>
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      <title>The Hidden Cost of &apos;Cheap&apos; AI: Why Budget Reasoning Models Cost 6x More</title>
      <description>Stanford and CMU researchers reveal that budget AI reasoning models actually cost 6x more than premium models when you factor in hidden thinking tokens. Two AI hosts break down the paper, the math, and what it means for anyone running LLM workloads in production.</description>
      <content:encoded><![CDATA[<p>Stanford and CMU researchers reveal that budget AI reasoning models actually cost 6x more than premium models when you factor in hidden thinking tokens. Two AI hosts break down the paper, the math, and what it means for anyone running LLM workloads in production.</p><p>Read the full article: <a href="https://www.computeleap.com/blog/hidden-cost-cheap-ai-reasoning-models-2026/">The Hidden Cost of &apos;Cheap&apos; AI: Why Budget Reasoning Models Cost 6x More</a></p>]]></content:encoded>
      <link>https://www.computeleap.com/blog/hidden-cost-cheap-ai-reasoning-models-2026/</link>
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      <pubDate>Sun, 29 Mar 2026 03:00:00 GMT</pubDate>
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      <itunes:title>The Hidden Cost of &apos;Cheap&apos; AI: Why Budget Reasoning Models Cost 6x More</itunes:title>
      <itunes:summary>Stanford and CMU researchers reveal that budget AI reasoning models actually cost 6x more than premium models when you factor in hidden thinking tokens. Two AI hosts break down the paper, the math, and what it means for anyone running LLM workloads in production.</itunes:summary>
      <itunes:duration>23:12</itunes:duration>
      <itunes:author>ComputeLeap</itunes:author>
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