EP 76: Dashboards Are Wrong in the Background. AI Is Wrong in Your Face | Barr Moses, Monte Carlo
This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Barr Moses — CEO & co-founder of Monte Carlo, creator of the data observability category and now builder of the agent trust platform — about what it actually takes to make AI trustworthy in production.
What's Covered:
"AI Is Wrong in Your Face" — Barr's framing of the trust gap: dashboards were always wrong quietly in the background; AI is wrong out loud, and it'll argue with you. Why trust is the biggest thing standing between pilots and production.
The Four Layers of Agent Failure — Context, performance, behavior, and output. Why all four can look perfect and the agent still fails — and why you have to watch all of them together.
The Flight That Already Left — The airline agent that recommended a flight that departed that morning. The agent was fine; the context was stale. The most surprising failure mode nobody plans for.
Where to Start — Make ONE agent great, not a hundred. And why the hardest first step is simply defining what "good" even looks like.
The Reinforcement Loop — The idea Barr's most excited about: agents that self-identify what went wrong, propose a fix, submit a PR for human approval, and use it as tomorrow's baseline. Agents that rebuild themselves every day — running in production today.
100% AI-First — Why every line of Monte Carlo's code is AI-generated, how it made them 3–5x faster, and Barr's stoplight analogy for where human-in-the-loop is heading.
Key Quote: "Dashboards are wrong in the background. AI is wrong in your face — it'll argue with you."
Connect with Barr: LinkedIn: Barr Moses : https://www.linkedin.com/in/barrmoses/
Monte Carlo: https://www.montecarlo.ai
Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
More description
This episode was recorded live from the Ai4 conference podcast pavilion, where host Mac Goswami sat down with Barr Moses — CEO & co-founder of Monte Carlo, creator of the data observability category and now builder of the agent trust platform — about what it actually takes to make AI trustworthy in production.
What's Covered:
"AI Is Wrong in Your Face" — Barr's framing of the trust gap: dashboards were always wrong quietly in the background; AI is wrong out loud, and it'll argue with you. Why trust is the biggest thing standing between pilots and production.
The Four Layers of Agent Failure — Context, performance, behavior, and output. Why all four can look perfect and the agent still fails — and why you have to watch all of them together.
The Flight That Already Left — The airline agent that recommended a flight that departed that morning. The agent was fine; the context was stale. The most surprising failure mode nobody plans for.
Where to Start — Make ONE agent great, not a hundred. And why the hardest first step is simply defining what "good" even looks like.
The Reinforcement Loop — The idea Barr's most excited about: agents that self-identify what went wrong, propose a fix, submit a PR for human approval, and use it as tomorrow's baseline. Agents that rebuild themselves every day — running in production today.
100% AI-First — Why every line of Monte Carlo's code is AI-generated, how it made them 3–5x faster, and Barr's stoplight analogy for where human-in-the-loop is heading.
Key Quote: "Dashboards are wrong in the background. AI is wrong in your face — it'll argue with you."
Connect with Barr: LinkedIn: Barr Moses : https://www.linkedin.com/in/barrmoses/
Monte Carlo: https://www.montecarlo.ai
Follow and subscribe to AsembleAI: Spotify | Apple Podcasts | Amazon Music | iHeart Radio | YouTube | Substack
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