Your LLM is smart, but it’s static. It doesn’t learn from what actually drives your success.
Honey Nudger changes that.
It’s a self-learning extension for your LLM that continuously improves its outputs based on your real-world goals—without human intervention.
Think of it as a feedback engine that trains your AI in real time, so every interaction gets closer to the result you want. Faster sales. Better conversions. Smarter decisions.
A reinforcement learning loop using (p)assive reward signals from your app's users.
Automatically curates a RAG "Golden Set" of high-value prompt-injected examples and triggers economically-aware PEFT trainings to the onboard Small Language Model (SLM).
Autonomously spawns and trains new SLM "experts" for each distinct use case that it identifies.
A/B tests each of its new model updates and auto-scales the winner.
Intelligently distributes RL rewards to the right outputs in conversational AI systems.
Organically throttles its resource usage and pauses recursive learning once it reaches diminishing returns.
The future of AI isn't just accuracy; it's effectiveness.
We're building the open-source, self-learning agent to get there, and we're starting with a private Founder's Circle of builders and visionaries.
We believe that self-learning AI is a fundamental capability that should be accessible to every developer, not a secret weapon hoarded by Big Tech. If you believe in this mission and want to help shape the future of AI alignment, apply below.
Members get early access to the code, a direct line to the founding team, and a foundational role in the movement.
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