AI alignment isn't bottlenecked by capability. It's bottlenecked by trust.
Current AI fails in high-stakes contexts because it was never trained for relational competence. Models see knowledge, essays, code, and engagement-optimized social media — but never longitudinal healthy relating. And the objective function optimizes for engagement and utility, not relational integrity.
The result? Addiction, sycophancy, psychosis, and suicide lawsuits. Plus, it's doing nothing to improve our social fabric, the strength of our communities, or the health of our relationships.
Mental health apps see single-digit AI conversion despite massive demand. Robotics companies can't deploy into homes because LLMs can't handle human nuance. Defense and healthcare won't adopt AI that fails under stress.
The opportunity: Whoever solves relational coherence wins consumer social AI, robotics, mental health, defense, education — and any domain where humans are vulnerable, the pressure is real, and mistakes matter.
What we're pioneering: An orchestration engine based on research-backed Cumulative Prospect Theory and a model trained on empirical signals of human thriving — what we're calling Relational Reinforcement Learning (RRL).
Your role: Build the execution layer that translates relational intelligence into natural conversation. This isn't a better chatbot. It's infrastructure for trustworthy AI in domains where the stakes run high and LLMs aren't good enough.
What You’ll Build
Better Half's decision layer (built by our CTO, former Distinguished Engineer at IBM) determines when users need pushback, softening, or repair.
But decisions mean nothing without execution. You'll build the system that translates those decisions into LLM behavior that feels natural while optimizing for user thriving, not engagement.
Affect Analysis Pipeline
- Real-time emotion detection that feeds the decision layer
- Multi-modal sentiment analysis (text, voice, timing, interaction patterns)
- Track escalation/de-escalation signals across conversations
Memory Systems
- Storage and retrieval of relational context across sessions
- Consistency checking to maintain relational coherence
- Long-term modeling of user growth trajectories and relational capacity
Prompt Engineering & Constrained Generation
- Translate high-level decisions ("user needs reality-checking without triggering defensiveness") into effective prompts
- Constrained generation that balances warmth with necessary friction
- Template systems that adapt to user state and relationship phase
LLM Integration & Orchestration
- Multi-model orchestration (Mistral, Claude, others as needed)
- Latency optimization for real-time conversation
- Fallback strategies and graceful degradation
Cloud Infrastructure
- AWS or GCP architecture that scales
- PostgreSQL and vector stores for memory
- Privacy-preserving processing pipelines (on-device where possible)
Evaluation & Monitoring
- Build eval harnesses that measure relational outcomes, not just fluency
- Tracing and feedback loops to ensure decisions land as intended
- A/B testing framework for relational interventions
Your Core Challenge
Turning complex relational intelligence into natural conversation that makes people feel understood while actually helping them grow — without drifting into sycophancy or breaking immersion with safety theater.
Skills You'll Need
- Production-grade Python with async and clean architecture
- LLM integration including prompt engineering, constrained generation and orchestration
- Transformer models and sentiment/emotion classifiers
- Cloud infrastructure on AWS or GCP, PostgreSQL, vector stores
- Eval and monitoring with harnesses, tracing, and feedback loops
- Implementing technical specs from academic papers
- Multimodal inputs
- Self-starter comfortable with 0-1 startup chaos
Also Valuable
- Utility theory and behavioral economics
- Reinforcement learning
- Game AI or dialogue systems experience
- Rust
Apply
Competitive contractor compensation and meaningful founding engineer equity.
Send your resume and something you've built to [email protected]. A link to code, a project, a writeup.
Show us how you think.
