# Model Self-Redesign **Entity class:** AI capability concept **Domain:** Artificial intelligence / Model architecture **Maturity:** Developed ## Definition Model self-redesign is the use of a model's outputs to propose or implement changes to its own architecture or to the architecture of a successor. ## Mechanism and significance A genuine redesign loop requires independent evaluation so that apparent improvement is not merely the system redefining success around its own output. ## Relationships - **Research dossier:** [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] - **Ontology route:** [[ASI and RSI Timeline Ontology#Model Architecture and Compute Economics|Model Architecture and Compute Economics]] - **Primary fields:** [[Machine Intelligence]] · [[AI Infrastructure]] · [[Compute Race]] - **Adjacent concepts:** [[World Knowledge and Reasoning Kernel Separation]] · [[Recursive Architectural Self-Improvement]] · [[nanochat]] · [[NanoGPT Speedrun]] ## Sources and provenance - [[research/ASI and RSI Timeline Research Moonshots|ASI and RSI Timeline Research Moonshots]] — immediate source for this node's role in the broadcast research map. ## Evidence boundary The research dossier establishes why this entity or concept belongs in the Moonshots ontology. Time-sensitive organizational, product, policy, and performance claims should be checked against the linked primary source or a current authoritative source before reuse as settled fact. ## Simple Reminders, Quotations, and Thoughts > A major threshold was crossed when AI learned to code: AI is code, and AI can now help rewrite code. Human engineers using AI to build the next generation are already a weak form of recursive self-improvement; stronger forms close the loop over ideation, implementation, and validation. > **— Adapted from Richard Socher**, *MOONSHOTS Live, October 2026* [[reminders/Machine Succession/AI Can Improve AI Because AI Is Code and AI Can Code by Richard Socher|AI Can Improve AI Because AI Is Code and AI Can Code by Richard Socher]]