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MCPs are often flaky, face multiple security vulnerabilities, and are generally hard to scale. Most enterprises struggle to use more than single digit numbers of MCPs due to issues with security, observability, and access control.
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A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features.
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April 21, 2026 - all times in EST -- 9:00am - Welcome to Day 2 -- 9:10am - David House, G2i Transforming Programming Mindsets: Case Studies in Agentic Coding Adoption -- 9:35am - Sarah Chieng, Cerebras Help!
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AI Engineer session on Principles for Prompt Engineering - Karina Nguyen (Claude Instant @ Anthropic). It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Open Questions for AI Engineering: Simon Willison. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on [Workshop] AI Engineering 101. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Retrieval Augmented Generation in the Wild: Anton Troynikov. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Building Blocks for LLM Systems & Products: Eugene Yan. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Supabase Vector: The Postgres Vector database: Paul Copplestone. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Weekend AI Engineer: Hassan El Mghari. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Harnessing the Power of LLMs Locally: Mithun Hunsur. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on [Workshop] AI Engineering 201: Inference. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on 120k players in a week: Lessons from the first viral CLIP app: Joseph Nelson. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Climbing the Ladder of Abstraction: Amelia Wattenberger. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Building Production-Ready RAG Applications: Jerry Liu. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Pragmatic AI with TypeChat: Daniel Rosenwasser. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Hidden Life of Embeddings: Linus Lee. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The Future of Work: Toran Bruce Richards, Silen Naihin et al. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Using AI to Build an Infinite Game: Jeff Schomay. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on GPT Web App Generator - 10,000 apps created in a month: Matija Sosic. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on The AI Pivot: With Chris White of Prefect & Bryan Bischof of Hex. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on See, Hear, Speak, Draw: Logan Kilpatrick & Simón Fishman. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Domain adaptation and fine-tuning for domain-specific LLMs: Abi Aryan. It adds practical context for how teams are building and operating AI systems in production.
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AI Engineer session on Building Context-Aware Reasoning Applications with LangChain and LangSmith: Harrison Chase. It adds practical context for how teams are building and operating AI systems in production.