The Data Exchange with Ben Lorica Predictability Beats Accuracy in Enterprise AI
Sep 4, 2025
Anant Bhardwaj, CEO of Instabase, shares insights on creating effective enterprise AI solutions. He underscores the importance of predictability over accuracy, arguing that user confidence hinges on reliable outcomes. The conversation compares AI agents to robotic process automation, highlighting the need for human oversight in complex workflows. Bhardwaj advocates for Retrieval-Augmented Generation to enhance AI systems and discusses the barriers to AI adoption in enterprises, stressing hands-on engagement and tailored strategies for success.
AI Snips
Chapters
Transcript
Episode notes
Simple Definition Of An Agent
- An agent is defined as a system given only a goal and a set of tools and left to plan and act autonomously.
- It self-determines steps, revises plans, and decides when to stop or fail based on outcomes.
Why Agents Outperform RPA
- RPA records and replays exact human actions, while agents plan and adapt at each step using model reasoning.
- Agents can replace RPA for unstructured, changing tasks but introduce autonomy and control trade-offs.
Agents Best Used At Design Time
- Agents shine during design and build time where exploration and iteration create predictable workflows.
- Runtime production needs predictable, repeatable AI workflows rather than free-running agents.