The core idea here is really interesting and resonates with what I've seen in my own research. The five-layer architecture mapping onto Buddhist phenomenology (the skandhas) is a bold design choice, and the argument for training from scratch rather than fine-tuning is well-reasoned. I feel like the vision for this pitch is really strong.
Where I'd push is on the gap between vision and implementation. There's no prototype or MVP here, so this is a $150K ask based on an architectural description. The hardest technical problem in the whole pitch, the question of how do you formalize "narrative coherence" as a trainable loss function, gets about one sentence. That's arguably the problem, and it needs a much more developed answer before it can justify this funding level.
A few specific questions:
How does this position itself relative to existing work in the space? The ACM Project (theconsciousness.ai) is open-source, actively building, and working on closely related problems — consciousness as emergent from emotional homeostasis, layered architecture, intrinsic motivation through internal state management. The active inference community around Friston's Free Energy Principle is developing formal frameworks for exactly the kind of recursive predictive loops you're describing. Even the "Skandhas in Silicon" discussion is already happening. The pitch should engage with these efforts and explain what this specific approach brings that they don't.
On the infrastructure side, have you looked at existing frameworks like OpenClaw as scaffolding for an easy buildable prototype for the continuous loop? It already handles persistent state, messaging platform integration, and always-on operation. It wouldn't solve the interesting research problems (attentional gating, narrative attractors, the skandha layers), but it could dramatically reduce the engineering overhead and let you focus your research on the novel parts until you have an MVP that increases your chances of pulling in a 6 figure ask. However, there's also the additional security concerns that you'd have to take into account with that approach since this is intended for others to be able to communicate with you system. That said, running any continuous inference loop gets expensive fast via API costs, so the economics of sustaining a system like this need to be addressed in the pitch either way. What's the monthly burn just to keep this thing existing, before anyone even talks to it?
The success metric, "do people describe the experience as qualitatively different", is subjective and hard to validate. Is there a plan for how you'll get feedback from users and how that feedback will correlate with a metric you can use to evaluate if you're moving closer or further from success? Or is there a more concrete intermediate milestone that could demonstrate success, like a constrained demo showing that attentional gating produces measurably different response patterns compared to a standard always-available model? I feel like something more concrete or some sort of quantitative metric that can be tracked would add a lot more weight to the $150k ask.
The team list (Buddhist monk, NDE survivor)...I get the intuition, but it reads as hand-wavy next to a six-figure ask. Ground it more concretely: what specific expertise do those roles contribute to the technical architecture, and at what stage do they become necessary? Not saying that your team has to be full of technical people, but there should be a clearly state reason for choosing each team member and what it is they're providing to the team.
The vision is definitely worth pursuing in my opinion. But right now it needs either a smaller proof of concept to validate the core mechanism, or a much more developed technical plan to justify the funding level, or even just a re-evaluation of what you currently need, which may not be funding at all. There's enough adjacent work happening that you don't have to start from zero. Engaging with what's already out there could get you to a testable prototype faster and cheaper than building the full stack yourself. Good luck with you project!