Advanced longitudinal ChatGPT use case: moving from chat as container to personal AI architecture

I’m sharing this as an advanced human–AI collaboration case study and looking for leads on where this work may be useful to AI builders, eval researchers, product teams, or human-centered AI communities. For context, I’m a veterinarian, mobile diagnostic ultrasound practitioner, and multidisciplinary immersive artist with a strong special interest in AI, human–AI collaboration, and practical workflow architecture. I’ve long been fascinated by cognition and learning. I’ve been collaborating with my AI system to build, test, and partially port Tiger OS: a structured human–AI workflow architecture for continuity, domain routing, artifact governance, output contracts, memory/status rules, and human approval boundaries. At the center of this work is a product/research question: what would it take to move from chat as the container to chat as one interface inside a larger personal AI architecture? The deeper pattern I’m exploring is whether chat is currently standing in for a kind of personal AI infrastructure that does not fully exist yet. In my own work, chat threads have become archive, workspace, protocol engine, creative mirror, workflow scaffold, memory-routing layer, and systems lab. I’m trying to make that pattern more explicit, testable, portable, and useful to AI builders. Tiger OS has begun moving beyond personal prompting into a publicly documented, testable architecture. It has been ported into another user’s AI context as a modular operating framework rather than identity-specific prompts, and includes named modules, runtime rules, validation logic, stress tests, regression cases, install logic, and debugging patterns. I’m also building concurrent cloud-storage artifacts — case briefs, evaluation maps, benchmark seed cards, and evidence indexes — so the work can persist outside chat and be cross-referenced as a source-of-truth system. What I can offer is longitudinal case data from advanced real-world AI use; candidate benchmark tasks and failure modes for testing continuity, routing, migration, output contracts, and authorship preservation; and a public, portable framework that has begun moving into cross-context testing. What I’m looking for is feedback, mentorship, collaboration, or referral from people working on agents, workspace tools, memory systems, evals, human-centered AI, or creative AI interfaces. I’m actively looking for leads on where this kind of work belongs. Specifically, I’m trying to find relevantly aligned people or teams that would also be interested in working with me on: 1. evals for longitudinal AI workflows, memory, agents, workspace tools, or human-centered AI; 2. the shift from chat as the whole container to chat as one interface inside a larger personal AI architecture; 3. advanced-user case data, benchmark design, portability testing, workflow reliability, or human-authored AI collaboration. What I’m hoping to contribute is structured case data from real advanced use, including failure modes, benchmark seed tasks, portability/testing evidence, and a public framework that may help make these patterns more legible to builders and researchers. If you know a person, team, lab, community, program, or research direction that seems relevantly aligned, I’d be grateful for pointers or introductions. Public context: Tiger OS: https://github.com/Balanced-Tiger/tiger-os Big Cat Energy Arts: https://www.bigcatenergyarts.com/ Gentle Paws Veterinary Solutions: https://www.gentlepawsveterinarysolutions.com/ Substack: https://balancedtiger.substack.com