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Subscribe to AI Agents Podcast Channel:
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In this episode of the AI Agents Podcast, host Demetri Panici sits down with James Luan from Zilliz to talk about how AI is already changing the day to day work of engineers. James explains why coding agents are already taking over parts of his workflow, how vector databases became a core building block for modern AI systems, and why retrieval still matters even in a world obsessed with bigger models.
They also get into the real mechanics behind RAG, hallucinations, MCP, long term memory for agents, and the challenges of building production grade AI systems that can search, reason, and scale reliably. If you want a practical conversation about where agent infrastructure is going and what engineers should actually pay attention to, this episode is worth watching.
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⏰ TIMESTAMPS:
00:00 – AI is already taking parts of engineering work
01:03 – James Luan’s background and first AI moments
07:07 – Why Zilliz was built and how vector databases fit in
16:58 – Long term memory, agent search, and reasoning workflows
21:37 – MCP, tooling limits, and real world production issues
31:02 – Are coding agents already replacing parts of engineering?
35:52 – AI for travel planning, presentations, and parallel work
38:57 – NotebookLM, Gamma, and James’s favorite AI tools
39:45 – Where to find James and Zilliz
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Follow us on:
Twitter ➡️ https://x.com/aiagentspodcast
Instagram ➡️ https://www.instagram.com/aiagentspodcast
TikTok ➡️ https://www.tiktok.com/@aiagentspodcast
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By AI Agents Podcast5
1313 ratings
Subscribe to AI Agents Podcast Channel:
https://link.jotform.com/subscribe-to-podcast
In this episode of the AI Agents Podcast, host Demetri Panici sits down with James Luan from Zilliz to talk about how AI is already changing the day to day work of engineers. James explains why coding agents are already taking over parts of his workflow, how vector databases became a core building block for modern AI systems, and why retrieval still matters even in a world obsessed with bigger models.
They also get into the real mechanics behind RAG, hallucinations, MCP, long term memory for agents, and the challenges of building production grade AI systems that can search, reason, and scale reliably. If you want a practical conversation about where agent infrastructure is going and what engineers should actually pay attention to, this episode is worth watching.
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
⏰ TIMESTAMPS:
00:00 – AI is already taking parts of engineering work
01:03 – James Luan’s background and first AI moments
07:07 – Why Zilliz was built and how vector databases fit in
16:58 – Long term memory, agent search, and reasoning workflows
21:37 – MCP, tooling limits, and real world production issues
31:02 – Are coding agents already replacing parts of engineering?
35:52 – AI for travel planning, presentations, and parallel work
38:57 – NotebookLM, Gamma, and James’s favorite AI tools
39:45 – Where to find James and Zilliz
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Sign up for free ➡️ https://www.jotform.com/
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
Follow us on:
Twitter ➡️ https://x.com/aiagentspodcast
Instagram ➡️ https://www.instagram.com/aiagentspodcast
TikTok ➡️ https://www.tiktok.com/@aiagentspodcast
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