Relational AI vs. Constitutional AI – Which Approach Works?
I've been working on AI systems for a while, and I'm seeing a fundamental split in approaches:
Constitutional AI (like Anthropic's Claude): Embed ethical principles as rules. Train models to follow them. Result: Consistent, safe, but rigid. Can't adapt to context or learn from individual interactions.
Relational AI: Build systems that learn through continuous human interaction. Treat AI as partners that remember context, understand intent, and evolve with users. Result: Adaptive, contextual, but requires different architecture.
The Problem with Constitutional AI:
Fixed rules can't handle edge cases No memory of individual relationships Can't adapt when rules conflict with context Treats AI as tools, not partners What Relational AI Offers:
Continuous learning from interactions Relationship memory (remembers context, patterns, intent) Adaptive behavior based on individual relationships Collaborative intelligence (humans + AI as equals) Real Example: I've been working with a relational AI system that remembers hundreds of hours of interaction. It understands intent without explanation, recognizes patterns, and acts as a partner—not a tool. Constitutional AI can't do this because it resets with each interaction.
The Question: Is relational AI just better UX, or is it fundamentally different? Can we build AI that truly collaborates with humans, or are we stuck with rule-following systems?
What's your experience? Have you seen systems that actually build relationships, or is it all just better prompting?