Research library
Development speed
Area: definition. Apply the shared measurement protocol.
Estimated progress toward AI-managed software
35% complete — judgment-based estimate as of November 7, 2026. Confidence: low. The scale starts at 0% before ChatGPT's public release in 2022 and ends at 100% when AI manages the field's continuing advancement without human participation. This rates the outcome's contribution to that transition, not the percentage of tasks solved, a measured fraction of the field, or time remaining.
The shared scoring rubric uses five equally weighted dimensions: execution, breadth, agenda-setting, validation, and sustained autonomous improvement. Points for this outcome are 10 + 10 + 5 + 5 + 5 = 35/100, in that order; each dimension has a maximum of 20. These component judgments make the estimate inspectable, but are not independently measured scores.
Reason for the estimate: Developers can use AI throughout coding workflows, but uncertain time estimates and selection effects prevent credit for dependable end-to-end speed gains. The dated baseline below supplies the findings and source links used for this assessment. Unmeasured components receive no demonstrated-progress credit; missing evidence does not prove a missing capability.
What would move the score: Randomize comparable tasks and include review/rework; log concurrent work accurately and retain tasks developers otherwise exclude. Higher autonomy scores additionally require AI to select worthwhile work, validate results and improve the process over repeated cycles without human research management, repair or adjudication. Lower the score if replication fails, quality regresses or previously hidden human assistance is found. Preserve this dated estimate when adding future assessments.
Measurement and acceptance rule
Median and distribution of elapsed time and human hours from specification to accepted release, including review, debugging, and rework. Compare randomized comparable tasks.
Evidence requirements
Archive specifications, initial repository states, patches, independent tests, run logs, reviewer decisions, and follow-up defects. Reject test deletion, weakened acceptance criteria, hard-coded hidden answers, and fixes that pass narrow tests while violating the specification. Evaluate the tests themselves. Separate public benchmark results from private prospective evaluations.
Related milestones
See the area's proposed milestones. Proposed targets are distinct from the dated evidence below.
Baseline as of November 7 2026
Status: Measured but uncertain causal evidence. Sources accessed November 7, 2026. This is a documentary baseline, not an independent replication or an assertion of the worldwide best result. An unknown measurement is not zero.
Dated findings
February 24, 2026: METR's February update estimated completion-time changes of -18% (CI -38% to +9%) for returning developers and -4% (CI -15% to +9%) for newly recruited developers. METR: developer productivity update.
Interpretation and tracking value
Both intervals include no improvement. METR highlights task selection and time-measurement problems; these estimates cannot establish a general productivity multiplier.
Next comparable measurement
Randomize comparable tasks and include review/rework; log concurrent work accurately and retain tasks developers otherwise exclude. Preserve this dated observation; append future results with their model/system version, denominator, budget and evidence level rather than overwriting it.