Instead of chasing bigger models and longer context windows, Redprint shifts the focus to compression, memory, and reasoning. It is designed to reduce the need for massive GPUs or infinitely scaling architectures.
The goal is to move past chatbots and tool-using agents toward something more persistent, auditable, and self-refining, all without relying on billions of parameters.
Top-level features of Redprint:
* Symbolic action-outcome chains (with execution feedback)
* Modular plug-ins for curiosity, compression, and evaluation
* Symbolic + vector memory fusion
* Tests that track agent learning over time
We’re not claiming AGI. But we are taking a real step toward agents that can reason about their actions and improve themselves.
Still early, but we wanted to surface the work now to find others exploring similar paths and avoid building in a vacuum.
Whitepaper coming soon. Select early access likely.
FlameArchitect•24m ago
Please chime in if you feel any interest in the subject. I'm not asking for money or hype or anything like that. Ideally someone who's ready to challenge what I have set forth and perhaps participate in the building.