AI Agents Conference 2026 - Day 1
summary
Conference day surveys a jump from 66% to 90% production success for end-to-end AI projects and shows concrete wins and hazards: agents run multiagent orchestration, write millions of rhymes in hours with claimed 99% accuracy, and sustain week‑long autonomous runs using million‑token contexts and MCP tool hooks. Builders demo GitHub Copilot/CoPilot CLI, Squad orchestration, Google ADK, OpenClaw templates, and DeltaStream for live context; semantic chunking + knowledge graph raise a real system from ~62% accuracy to near‑production levels with eval loops and human‑in‑the‑loop gating.
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chapters (37)
- 0:00Opening and welcome
- 2:33Keynote: Retesh Modi
- 7:19The evolution of AI agents
- 13:24Agent capability leap
- 15:23Future agent architecture
- 21:05Human-AI collaboration
- 23:19Future projections and Q&A
- 33:31Expert chat: Rohit Gupta
- 48:52Prompting and context
- 59:10Prompting techniques
- 1:15:00AI coding and tools
- 1:30:05Community engagement
- 1:33:46Building AI agents
- 1:46:53Google AI SDK tutorial
- 1:54:33Agent deployment and MCP
- 2:03:54Future of the agentic economy
- 2:09:01Windows AI development
- 2:15:28Agent architecture and trust
- 2:40:31Entrepreneurship and AI
- 2:48:23The agentic layer
- 3:09:05Building real-world agents
- 3:26:43Reverse engineering business
- 3:34:08Operationalizing agents
- 3:44:04Managing AI agents
- 3:53:52Context kings in AI
- 4:04:20Production-grade LLMs
- 4:15:07Evaluating agent performance
- 4:23:42Security and compliance
- 4:34:00AI in education
- 4:51:18The future of EdTech
- 5:07:31AI agentic loops
- 5:21:47Context management in production
- 5:40:36Real-time context integration
- 5:56:30Agent reliability in finance
- 6:30:32Evaluation metrics and loops
- 6:43:23Educational AI paradigms
- 7:09:39Conclusion
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