The era of treating AI as just a chatbot is over. Beyond Prompting is a podcast for developers and technical leaders ready to make the shift from conversational AI to operational AI. Join us as we explore how to turn Claude into an active, system-level agent that executes code, automates desktop workflows, and integrates directly into your CI/CD pipelines. Our core philosophy is simple: Execution over explanation, context over scale, and workflow over conversation. Would you like me to generate a real sample audio episode of this podcast so you can hear how it sounds?
Master Claude Chat, Cowork, Code
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15 episodes
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Podcast Overview
The era of treating AI as just a chatbot is over. Beyond Prompting is a podcast for developers and technical leaders ready to make the shift from conversational AI to operational AI. Join us as we explore how to turn Claude into an active, system-level agent that executes code, automates desktop workflows, and integrates directly into your CI/CD pipelines. Our core philosophy is simple: Execution over explanation, context over scale, and workflow over conversation. Would you like me to generate a real sample audio episode of this podcast so you can hear how it sounds?
Language
🇺🇲
Publishing Since
3/3/2026
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Recent Episodes
May 15, 2026
15. Managing Context Rot (Thinking Like an Ops Team)
<p><strong>Episode 15: Context Rot — The Silent Failure Mode of Long AI Sessions</strong></p><p>In Episode 15 of Beyond Prompting, we expose one of the most dangerous—and least understood—problems in modern AI workflows:</p><p><strong>context rot.</strong></p><p>At first, massive 200,000-token context windows sound revolutionary.</p><p>More memory. More history. More continuity.</p><p>But in practice, something subtle begins to happen as conversations grow:</p><p>Old decisions linger.<br>Rejected ideas remain buried in the thread.<br>Outdated assumptions continue influencing the model.</p><p>And slowly, the quality of reasoning starts to decay.</p><p>The AI becomes less focused, less precise, and more likely to make decisions based on information that is no longer true.</p><p>This is context rot.</p><p>And if you are building serious systems with AI, understanding this phenomenon is critical.</p><p>In this episode, we break down practical techniques for keeping Claude aligned with the <strong>current truth</strong> of your project. You will learn how to strategically use commands like <code>/compact</code> and <code>/clear</code> to compress and reset context without losing important knowledge.</p><p>But simply deleting history is not enough.</p><p>You also need a way to preserve what actually matters.</p><p>That is why we introduce the concept of structured <strong>Decision Records</strong>—persistent artifacts that capture architectural decisions, tradeoffs, and operational truths outside the conversation itself.</p><p>Instead of relying on fragile conversational memory, you create durable knowledge that both humans and AI can reference consistently.</p><p>And then we arrive at the ultimate enterprise pattern.</p><p>The real solution is not “better conversations.”</p><p>The real solution is to stop depending on conversation history entirely.</p><p>We explore how advanced teams use <strong>version-controlled State Files</strong> to manage AI interactions more like database transactions than chat sessions—creating deterministic, auditable, reproducible workflows that scale far beyond ad-hoc prompting.</p><p>This is the difference between casually using AI… and engineering systems around it.</p><p>If you want to understand how elite AI workflows stay clean, scalable, and reliable over time, the complete framework is covered in the book.</p><p><strong>Get your copy of Beyond Prompting here:</strong><br><a href="https://www.amazon.com/dp/B0GQVHJRGB">https://www.amazon.com/dp/B0GQVHJRGB</a></p><p>Because the future of AI engineering is not about giving models more context.</p><p>It is about controlling which context survives.</p>
April 20, 2026
14. The Universal Data Bridge (Connecting Systems with MCP)
<p><strong>Episode 14: MCP — Turning AI into Connected Infrastructure</strong></p><p>In Episode 14 of Beyond Prompting, we explore the breakthrough that takes AI out of isolation and plugs it directly into your real systems:</p><p><strong>Model Context Protocol (MCP).</strong></p><p>Until now, working with AI has meant constant friction—copying context, pasting data, and manually bridging gaps between tools.</p><p>MCP changes that.</p><p>It acts as a <strong>universal data bridge</strong>, allowing Claude to securely connect to your existing stack—without building custom integrations every time.</p><p>This is where AI stops being a side tool… and starts becoming part of your operational fabric.</p><p>In this episode, we walk through practical, real-world integrations with tools your team already uses:</p><ul> <li><strong>Slack</strong> — read conversations, draft responses, assist in team communication</li> <li><strong>GitHub</strong> — review code, suggest changes, comment on Pull Requests</li> <li><strong>Jira</strong> — understand tickets, summarize progress, assist with planning</li> <li><strong>Google Drive</strong> — access documents, extract knowledge, support decision-making</li></ul><p>But access alone is not enough.</p><p>With great connectivity comes the need for <strong>strict control</strong>.</p><p>We break down how to enforce security boundaries using MCP—so Claude can assist intelligently while remaining safely constrained. For example, it can <strong>read tickets</strong> and <strong>draft Pull Request comments</strong>, but it cannot delete messages, merge code, or change critical settings without explicit human approval.</p><p>This is how you move from experimentation to production-grade AI.</p><p>And then we take it one step further.</p><p>When you layer <strong>Agent Skills</strong> on top of MCP integrations, something powerful happens:</p><p>Claude stops reacting… and starts operating.</p><p>It can execute structured workflows across systems, coordinate actions, and become part of your core infrastructure—not just a conversational assistant.</p><p>This is the shift from “AI tools” to <strong>AI-powered systems</strong>.</p><p>If you want to understand how to design, connect, and control AI at this level, the complete framework is detailed in the book.</p><p><strong>Get your copy of Beyond Prompting here:</strong><br><a href="https://www.amazon.com/dp/B0GQVHJRGB">https://www.amazon.com/dp/B0GQVHJRGB</a></p><p>Because once AI is connected, governed, and executable— it stops being optional, and starts becoming foundational.</p>
April 19, 2026
13. Teaching Claude New Tricks (Encapsulating Knowledge with Agent Skills)
<p><strong>Episode 13: Claude Skills — Turning SOPs into Executable Workflows</strong></p><p>In Episode 13 of Beyond Prompting, we unlock one of the most powerful—and overlooked—capabilities in modern AI workflows:</p><p><strong>turning your team’s standard operating procedures into executable systems.</strong></p><p>This is where AI stops waiting for instructions… and starts knowing what to do.</p><p>We introduce <strong>Claude “Skills”</strong>—a structured way to encode repeatable processes so they can be triggered and executed automatically. No more re-explaining the same tasks. No more inconsistent outputs across team members.</p><p>At the center of this system is the <strong>SKILL.md file</strong>.</p><p>You’ll learn how to design it properly, including why the <strong>YAML frontmatter</strong> and carefully crafted <strong>trigger descriptions</strong> are critical. Done right, Claude can recognize intent and invoke the correct workflow without you explicitly telling it what to do.</p><p>This is not prompting. This is orchestration.</p><p>We then go deeper into the architecture that makes it scalable:</p><p><strong>Progressive Disclosure.</strong></p><p>A three-layer system that ensures Claude only loads detailed instructions, reference materials, and scripts when they are actually needed. The result is a system that is both <strong>powerful and efficient</strong>—keeping token usage under control while still enabling complex, multi-step execution.</p><p>Finally, we show how to take this beyond individual use.</p><p>You’ll learn how to build a <strong>centralized Skills Library</strong>—a shared layer of operational intelligence that anyone in your organization can use. With it, even complex workflows like <strong>security audits</strong>, <strong>deployment pipelines</strong>, or <strong>structured analysis tasks</strong> can be executed through simple natural language.</p><p>This is how teams scale AI safely.</p><p>Not by relying on individual expertise—but by encoding it into systems that anyone can use.</p><p>If you want to move from ad-hoc prompting to fully structured, reusable AI workflows, the full framework is covered in the book.</p><p><strong>Get your copy of Beyond Prompting here:</strong><br><a href="https://www.amazon.com/dp/B0GQVHJRGB">https://www.amazon.com/dp/B0GQVHJRGB</a></p><p>Because once your workflows become executable, AI stops being a tool—and becomes part of how your organization operates.</p>
15 total episodes available
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