Simba Khadder is the founder and CEO of Featureform, now at Redis, working on real-time feature orchestration and building a context engine for AI and agents.
Context Engineering 2.0, Simba Khadder // MLOps Podcast #352
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// Abstract
Feature stores aren’t dead — they were just misunderstood. Simba Khadder argues the real bottleneck in agents isn’t models, it’s context, and why Redis is quietly turning into an AI data platform. Context engineering matters more than clever prompt hacks.
// Bio
Simba Khadder leads Redis Context Engine and Redis Featureform, building both the feature and context layer for production AI agents and ML models. He joined Redis via the acquisition of Featureform, where he was Founder & CEO. At Redis, he continues to lead the feature store product as well as spearhead Context Engine to deliver a unified, navigable interface connecting documents, databases, events, and live APIs for real-time, reliable agent workflows. He also loves to surf, go sailing with his wife, and hang out with his dog Chupacabra.
// Related Links
Website: featureform.comhttps://marketing.redis.io/blog/real-time-structured-data-for-ai-agents-featureform-is-joining-redis/
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Timestamps:
[00:00] Context engineering explanation
[00:25] MLOps and feature stores
[03:36] Selling a company experience
[06:34] Redis feature store evolution
[12:42] Embedding hub
[20:42] Human vs agent semantics
[26:41] Enrich MCP data flow
[29:55] Data understanding and embeddings
[35:18] Search and context tools
[39:45] MCP explained without hype
[45:15] Wrap up
