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What are the limitations of using a file-based agent workflow? Why do massive context windows tend to collapse? This week on the show, Mikiko Bazeley from MongoDB joins us to discuss agentic architecture and context engineering.
👉 Links from the show:
Mikiko is an applied AI engineer. She helps developers and organizations build AI and ML applications using MongoDB. We dig into the debate of files versus a database. What are some of the limitations of building an agent with just a folder of files?
We explore the surprising limitations of massive context windows and strategies for fixing them. Mikiko also shares advice and resources to help you get up to speed on building your own agent skills. Our conversation touches on multiple topics in the current development landscape.
This episode is sponsored by SerpApi.
Topics:
- 00:00:00 -- Introduction
- 00:02:31 -- Catching up with MongoDB
- 00:07:02 -- Are the files all you need?
- 00:15:14 -- What is a workflow agent?
- 00:24:43 -- Sponsor: SerpApi
- 00:25:45 -- Model vs harness
- 00:29:57 -- Context rot and tool loadouts
- 00:41:07 -- Sharing state and coordination of agents
- 00:47:27 -- Video Course Spotlight
- 00:49:16 -- What do dataflows look like
- 01:00:38 -- The human-in-the-loop & coding agents
- 01:10:30 -- Resources to explore
- 01:17:49 -- What are you excited about in the world of Python?
- 01:18:38 -- What do you want to learn next?
- 01:22:54 -- Thanks and goodbye
👉 Links from the show:
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2026/05/15
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