AI Adoption Playbook

AI build vs buy: How do you choose between custom tools vs vendors? | Diamond Bishop

10 snips
May 29, 2025
Diamond Bishop, Director of Engineering and AI at Datadog, discusses innovative approaches in building AI agents for production incident management. He emphasizes the transition from simple workflow automation to defining AI agents with real decision-making autonomy. The conversation highlights the critical need for trust and reliability in enterprise AI through root cause identification, enabling proactive solutions before engineers are needed. Additionally, Diamond explores the significance of adopting standards like Anthropic's MCP for seamless tool integration across diverse environments.
Ask episode
AI Snips
Chapters
Books
Transcript
Episode notes
INSIGHT

Defining True AI Agents

  • AI agents are systems with autonomy over control flow, not just fixed workflows or simple chatbots.
  • True agents observe, act, and decide dynamically, such as skipping steps or gathering more data.
ANECDOTE

AI Prevents Midnight Engineer Alerts

  • Datadog's Bits AI agent analyzes logs and runbooks to diagnose issues before engineers wake up.
  • It can identify root causes like faulty deployments or dependent service failures, saving time during outages.
ADVICE

Build Trust Via Precise Evaluations

  • Build trust in AI agents by establishing precise, scenario-specific evaluation metrics.
  • Share clear precision and recall statistics to show when and how the agent performs well.
Get the Snipd Podcast app to discover more snips from this episode
Get the app