[{"code":"B0","criteria":["No accepted persistent system change","Non-RSI reference level"],"definition":"Changes refine an output during the current task or session. Future independent tasks inherit no accepted system update.","framework_id":"duan-2026","id":"duan-2026-b0","is_rsi":false,"name":"In-task AI improvement","order":0,"source_refs":[{"locator":"§3.1 pp.12–14","source_id":"src-duan-v1"}],"subtitle":"Refine output"},{"code":"L1","criteria":["Human-defined what, how and success","Persistent accepted changes"],"definition":"Humans prescribe the target, update procedure and acceptance criteria. AI executes the procedure and accepted changes persist into later tasks or rounds.","framework_id":"duan-2026","id":"duan-2026-l1","is_rsi":true,"name":"Improvement execution autonomy","order":1,"source_refs":[{"locator":"§3.2","source_id":"src-duan-v1"}],"subtitle":"Execute improvements"},{"code":"L2","criteria":["AI chooses improvement strategy","Objectives and acceptance remain external"],"definition":"AI diagnoses weaknesses and chooses interventions and experiments. Humans continue to set objectives, task boundaries and evaluation criteria.","framework_id":"duan-2026","id":"duan-2026-l2","is_rsi":true,"name":"Improvement strategy autonomy","order":2,"source_refs":[{"locator":"§3.3","source_id":"src-duan-v1"}],"subtitle":"Choose how to improve"},{"code":"L3","criteria":["Learner-conditioned experience acquisition","Experience retained for later improvement"],"definition":"AI chooses or generates subsequent learning experience based on the evolving learner’s state. What it learns from changes as the learner changes.","framework_id":"duan-2026","id":"duan-2026-l3","is_rsi":true,"name":"Experience-acquisition autonomy","order":3,"source_refs":[{"locator":"§3.4","source_id":"src-duan-v1"}],"subtitle":"Choose what to learn"},{"code":"L4","criteria":["Persistent adaptation from operational feedback","High-level goals, access, evaluation and release may remain externally governed"],"definition":"Ongoing deployment or environmental interaction determines persistent changes in memory, skills, code, harnesses or parameters reused on later operational tasks.","framework_id":"duan-2026","id":"duan-2026-l4","is_rsi":true,"name":"Environment adaptation autonomy","order":4,"source_refs":[{"locator":"§3.5","source_id":"src-duan-v1"}],"subtitle":"Adapt from deployment"},{"code":"L5","criteria":["Identify the revised mechanism","Verify creation, retention, inheritance and later invocation","Evaluate effectiveness separately from structural reuse"],"definition":"The procedure governing future improvement is itself revised, retained and invoked in subsequent improvement rounds. It may be an improver, search or research policy, evaluator or successor generator.","framework_id":"duan-2026","id":"duan-2026-l5","is_rsi":true,"name":"Recursive inheritance autonomy","order":5,"source_refs":[{"locator":"§3.6 pp.31–35","source_id":"src-duan-v1"}],"subtitle":"Improve the improvement mechanism"}]