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What Makes 5% of AI Agents Actually Work in Production?

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Most founders think they’re building AI products. They’re actually building context selection systems. This Monday, I moderated a panel in San Francisco with engineers and ML leads from Uber, WisdomAI, EvenUp, and Datastrato. The event, Beyond the Prompt, drew 600+ registrants, mostly founders, engineers, and early AI product builders. We weren’t there to rehash prompt engineering tips. We talked about context engineering, inference stack design, and what it takes to scale agentic systems inside enterprise environments. If “prompting” is the tip of the iceberg, this panel dove into the cold, complex mass underneath: context selection, semantic layers, memory orchestration, governance, and multi-model routing. Here’s the reality check: One panelist mentioned that 95% of AI agent deployments fail in production. Not because the models aren’t smart enough, but because the scaffolding around them, context engineering, security, memory design, isn’t there yet. One metaphor from the night stu

What Makes 5% of AI Agents Actually Work in Production? Beyond the Prompt: Notes from the Context Frontier Oana Olteanu Oct 02, 2025 29 4 6 Share Most founders think they’re building AI products. They’re actually building context selection systems. This Monday, I moderated a panel in San Francisco with engineers and ML leads from Uber, WisdomAI , EvenUp, and Datastrato. The event, Beyond the Prompt , drew 600+ registrants, mostly founders, engineers, and early AI product builders. We weren’t there to rehash prompt engineering tips. We talked about context engineering, inference stack design, a

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