Unlock the full potential of Generative AI with Agent Platforms
summary
Blueprint for building an internal agent platform that moves beyond ad‑hoc pilots to production: use existing microservice runtimes and CI/CD, give teams fast prototyping UIs (Streamlit, Gradio), and start with vector stores (in‑memory, Postgres PQ, MongoDB) for RAG. Add observability via distributed tracing that captures prompts, search results, cost and PII considerations, and structured evaluation pipelines with human review. Enable agent-to-agent integration with the Model Context Protocol (MCP) and enforce service registry and tokenized access for security.
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chapters (11)
- 0:00AI agents in enterprise
- 1:49AI agent platforms necessity
- 3:37LLMs and agents characteristics
- 6:46Scaling AI challenges
- 9:59Platform design for users
- 12:10AI agent platform definition
- 15:03Foundational AI platform capabilities
- 21:48Advanced platform features
- 25:19Evaluating agent performance
- 28:53Building agentic enterprise
- 32:26Summary
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