QConAI 2025: Architecting Reliable AI with Certainty and Discovery

The Deterministic AI Revolution

This article provides a valuable perspective on building reliable AI systems, emphasizing the importance of deterministic components and bounded operations. The focus on tool selection and role specialization within agentic systems is a significant insight, addressing the 'paradox of choice' and promoting a more controlled and predictable environment. However, the article could benefit from exploring concrete examples of how these principles are implemented in real-world scenarios, particularly concerning the practical challenges of integrating deterministic systems with probabilistic models. Furthermore, while the emphasis on clear boundaries is crucial, the article could delve deeper into the complexities of defining and maintaining those boundaries as systems evolve.

Key Points

• Agentic AI should be treated as a layer over operational systems, not a replacement.
• Reliability comes from combining probabilistic components with deterministic boundaries.
• Tool selection and tool interfaces are critical components of an agentic system.
• Role specialization matters; purpose-built components for specific tasks are key.
• The boundary between discovery (agents explore) and certainty (deterministic tools execute) is where platform engineering resides.

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📖 Source: QConAI NY 2025 - Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery