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Challenge 2: Dashboard Walkthrough + Nash Demo What I Learned I learned how to navigate the Backboard dashboard and use its built-in features without writing any code. I discovered that the dashboard tracks activity with charts, saves conversations as threads, and supports memory so the assistant can recall facts across different chats. I also learned about Nash, a chat app built on the same platform, which allows me to switch between models seamlessly and even generate images. What I Did I logged into my Backboard account and explored the dashboard. I checked the analytics view to see charts for prompts and tokens. I started a new chat, enabled memory, and told the assistant facts about myself (my name and favorite pizza topping). I opened a new thread and confirmed that the assistant remembered my details. I explored the model library and tried chatting with different models. I visited the memory page to see the facts saved and even deleted one to test the controls. I confirmed my promo credits under Settings. I tried Nash by signing in, starting a conversation, switching models mid-chat, and generating an image. I compared responses from different models to see how they varied. Reflection I realized how powerful memory is for building agents that can recall context across conversations. I also saw how Nash simplifies working with multiple models in one place, which saves time and keeps my data organized. This challenge helped me understand the foundation of agent-based workflows and gave me hands-on experience with multi-modal AI. Screenshot Here’s a screenshot of my dashboard and Nash demo:

A conference sold out three separate ticket tiers before the doors even opened. Not "almost sold out." Sold out — Leadership track, gone. Workshops, gone. Late bird tickets, gone. The organizers stopped counting around 6,000 attendees and said they'd officially call it once they crossed 7,000. That's the AI Engineer World's Fair in 2026, and if you've spent any time building with LLMs over the last three years, you already know the name even if you've never been able to get a ticket. I want to walk you through what's actually happening on the ground this week at Moscone West in San Francisco — not the marketing copy, but the track list, the speaker lineup, and the quiet signals buried in the schedule that tell you where AI engineering is actually heading next. Table of Contents What is AI Engineer World's Fair? Why It Matters What Makes It Different Key Technologies AI Agents LLM Engineering MCP RAG Fine-tuning AI Infrastructure Workshops Networking Startups Enterprise AI Major Takeaways Future of AI Engineering Final Thoughts What is AI Engineer World's Fair? AI Engineer World's Fair is the flagship conference run by AI Engineer, the company behind a whole circuit of events — the AI Engineer Summit, Code Summit, and standalone editions in London, New York, Paris, Miami, Singapore, Shanghai, and Melbourne. The World's Fair is the biggest of them all: a four-day event with 29 tracks, 300 speakers, 100 expo partners, and more than 6,000 AI engineers, founders, and VPs of AI in attendance. The 2026 edition runs from Monday June 29 through Thursday July 2, with a Sunday evening orientation night tacked on for first-timers. It's held at Moscone West, 747 Howard Street, in San Francisco. This is the fourth year the event has anchored in San Francisco, and the organizers have leaned into that — discounted hotel blocks at the Marriott Marquis, Parc 55, and InterContinental, all walking distance from the venue. The person behind all of it is Shawn "swyx" Wang. He's the cofou