Preprint · Release 20
Recursive AI Drift: A 2025 Prediction Timeline External Validation Audit and Technical Note
Abstract
This technical note audits dated 2025 claims about recursive AI drift against later external developments and model behavior. It separates chronology, correspondence, partial support, failures, and unresolved questions rather than treating later events as direct validation of the full architecture.
Plain-language overview
Research question
How do dated 2025 claims about recursive AI drift compare against later external developments and model behavior?
Main contribution
- Audits dated 2025 recursive-AI-drift claims against later developments and observed model behavior.
- Separates chronology, correspondence, partial support, failures, and unresolved questions.
Evidence type
Current limitations
The note deliberately avoids treating later events as direct validation of the full architecture; several questions remain unresolved.
Research assets
- Read & download
- Zenodo record (manuscript and files)
- Research program hub
- geometry_of_resonance — equations, manuscripts, and simulations
Related works
Verification and traceability
This section is generated from the canonical publication traceability registry. Empty fields are reported rather than inferred.
- Claim IDs
- Equation IDs
- SymPy audit
- Lean coverage
- Assumptions
- Formalization
- AUDIT_NOTE
- Empirical state
- CHRONOLOGY_AND_CORRESPONDENCE_AUDIT
- Independent replication
- NONE_RECORDED
- Repositories
Explicit falsifiers
- The dated source claims do not precede the compared developments, or the claimed correspondence fails a preregistered coding rubric.
Open obligations
- Publish a claim-by-claim source ledger, comparison rubric, negative cases, and independent coding review.
Recommended citation
Reyes, R. J. (May 2026). Recursive AI Drift: A 2025 Prediction Timeline External Validation Audit and Technical Note. Zenodo. https://doi.org/10.5281/zenodo.20142976
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Machine-readable identifiers
This landing page provides accessible summaries and citation metadata for an archival preprint. The authoritative manuscript and downloadable files are maintained on the Zenodo DOI record. Wave Confinement Theory is an evolving independent framework; claims should be evaluated according to the derivations, simulations, experiments, data analyses, assumptions, and limitations stated in the paper itself.