Building AI agents that learn from feedback: BigPanda's drag-and-drop system | Alexander Page
Автор: Credal AI
Загружено: 2025-08-07
Просмотров: 193
Описание:
Alexander Page, Engineering Director (Applied AI) at BigPanda, demonstrates how customer-driven development creates AI systems that actually work in production. He explores how design partners beat perfect technical architecture and describes the frameworks BigPanda uses to build reliable AI agents for Fortune 500 IT operations. Alexander transitioned from sales engineering to AI architecture after ChatGPT's release, leading development of "Biggy." His experience spans both technical implementation and customer validation of enterprise AI systems.
Chapters:
0:00 Introduction
0:18 Alexander's background and transition to AI
2:05 ChatGPT moment and first prototype development
4:16 BigPanda's IT operations and monitoring tools
9:50 AI accessibility compared to traditional ML
11:17 Building Biggy with Fortune 500 customers
15:02 Customer-driven development and feedback loops
16:37 Three categories of customer feedback
19:35 Problem management and semantic search limitations
22:06 Evaluating AI agent performance challenges
24:56 Drag-and-drop feedback and correction systems
27:20 When will AI replace your job?
28:21 Sensory data requirements for AI advancement
31:39 Where to learn more about BigPanda
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