Project type: Research synthesis / landscape analysis
Created: 2026-05-25
Status: Active — Phase 4 (Publication) | Final document: Agentic AI for Deep-Tech Research.md (v0.2.1, reader-tested)
Agentic AI represents a paradigm shift in deep-tech research: enabling solo investigators to synthesize cross-disciplinary knowledge, prototype complex theoretical models, and bypass traditional institutional bottlenecks. This project surveys the emerging ecosystem of agentic AI research platforms, analyzes their architectural patterns, and identifies domains where autonomous AI-driven research can deliver disproportionate impact.
- In: Agentic AI architectures for scientific discovery, multi-agent research systems, government/academic/private-sector initiatives, QWAV as a benchmark case study, foundational physics applications, quantum information science, geometric unification, materials science, alternative computing architectures, formal proof engineering, AI alignment
- Out: General AI product development, commercial LLM fine-tuning, standard software engineering practices, non-research AI applications
- What architectural patterns distinguish effective agentic AI research systems?
- Which deep-tech domains are most amenable to solo AI-augmented research?
- How does the QWAV model compare to institutional programs (DARPA, Los Alamos, Stanford, Google)?
- What are the fundamental limitations and failure modes of agentic AI in scientific discovery?
- How can agentic AI methodologies transfer from pure science to societal grand challenges (climate, health, etc.)?
| File | Description |
|---|---|
0.1.1.md |
Solo deep-tech research model — five domains benefiting from agentic AI |
0.1.2.md |
Landscape survey — global agentic AI research initiatives |
0.1.3.md |
Multi-domain agent architecture — initial scaffolding |
0.1.4.md |
Architectural deep-dive — unified multi-domain agent design |
0.1.5.md |
Quantitative benchmarking — token costs, latency, context scaling |
0.1.6.md |
Alignment & safety analysis — dual-use surface area, 7 guardrails |
0.2.0.md |
Publication-ready synthesis paper (pre-reader-testing) |
0.2.1.md |
Reader-tested revision — final internal version |
Agentic AI for Deep-Tech Research.md |
Publication-ready descriptive copy (DOI pending) |
From Code to Climate... |
External source on adapting agentic AI to societal challenges |
- DOI: 10.5281/zenodo.20385089 — v4 (corrected PDF + MD + ZIP, 2026-05-25)
- Reader testing: Complete (REVIEWER subagent, v0.2.1)
- Publication language gate: Passed (0 internal terms, 0 straight quotes, 0 bare Unicode math)
- Zenodo record: https://zenodo.org/records/20383595
- All quantitative claims must be
[CODE-EXECUTED] - External sources must be imported and verified
- No web search available internally — search manifests required
- Publication-ready outputs require §11 standards (reader testing, YAML frontmatter, curly quotes)
- solo-scientist — The Force-Multiplier Playbook
- ultrametric-quantum — Ultrametric Quantum Computation
- hierarchical-universe — Geometric Unification Framework