Episodes
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A behind-the-scenes look at real agentic-coding workflows: visual planning, cloud-first agents, ephemeral PR environments, custom skills, and secrets management.
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How to market and sell to AI agents — discovery channels, CLI vs MCP trade-offs, authentication patterns, and the emerging agent-driven economy.
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Missing episodes?
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A practical, stage-by-stage look at running your entire development lifecycle with AI agents: from PRD to coding to QA.
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A practical look at managing AI budgets across coding agents, customer-facing models, and production inference
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Two real-world use cases are covered: CVE Enrichment for open-source vulnerability detection and real-time Malicious Command Detection, along with practical tips on cost optimization, prompt caching, and open-source vs. commercial model trade-offs.
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Site Reliability Engineer agent auto fixes production issues
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Measure the actual impact of adopting AI across the R&D
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Singularity and AGI are around the corner.
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How AI is used across the SDLC in a real R&D org - requirements, tech design, validation, testing, and code review. What worked, what didn’t, and where teams get stuck.
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Building and testing voice agents with realtime API or chained approach (TTS->LLM->STT)
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The Neuroscience behind the human brain and memories
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the production experience and considerations for fine-tuning a small language model for narrow tasks
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Recap of the major announcements and innovations from the 2025 re:Invent conference, along with our predictions for where things are heading in 2026
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Short and long term memory mechanisms for agents
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Getting started with no-code agentic automations, popular use cases and tips
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The state of best practices for context engineering, focused on AI-coding as a leading use case
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Enabling secured flexibility to your agents and MCP servers
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techniques to combine classic search with agentic retrieval
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The story of building Suna - the open source alternative of Manus the generalist autonomous agent
https://github.com/kortix-ai/suna -
Sharing our workflow with Cursor, Claude Code, GitHub Copilot and others. Listed the useful MCPs and tools, how to measure efficiency gains, and our vision for the future of coding
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