Enterprise AI in Production: Mumbai Call for Proposals
Share what it takes to run AI inside an enterprise: architectures, trade-offs, and lessons from production.
Oct 2026
26 Mon
27 Tue
28 Wed
29 Thu
30 Fri
31 Sat 11:00 AM – 04:00 PM IST
1 Sun
Accepting submissions till 11 Oct 2026, 11:59 PM
Not accepting submissions
Draft slides or a short recorded walkthrough are optional.
Accepting submissions till 11 Oct 2026, 11:59 PM
When Good Agents Disagreed Until We Built Shared UnderstandingAbstract Multi-agent systems are often built around orchestration: an orchestrator routes requests to specialist agents, coordinates their work, and brings their outputs together. But in production, we encountered a more fundamental problem: every agent could be doing its job correctly, while the system as a whole was still wrong. more
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Understanding Your Agents From Traces to TrustAbstract While building and operating LLM-powered systems in production, one lesson keeps repeating itself which is that the hardest failures are often invisible. Unlike traditional software, agentic systems can fail in countless ways while every dashboard remains green. An agent may misunderstand user intent, choose the wrong tool, retrieve stale information, drift from its objective, or silentl… more
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