Across three company field experiments with 4,867 software developers, access to an AI coding assistant increased completed tasks by 26.08% on average; less-experienced developers adopted the tool more and gained more.

SocioLens project,

Claim LD02-HQ-C13 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: institutional position
Verification state: Checked against the primary source. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: Developer employment decline; defect/quality effect beyond measured endpoints; all coding contexts
Limitations: Individual experiments noisy; selected companies; institutional-position disclosure required
Source (as cited): Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026
Source type: Peer-reviewed journal article (recorded as “Peer-reviewed journal article”)
Institutional position: Mixed; includes Microsoft Research affiliation
Maturity of the evidence: Mature evidence
Recorded date: 25 September 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026 (Peer-reviewed journal article)
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Version

This page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): ESTIMATE (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (INSTITUTIONAL_POSITION) (as printed: “ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): PEER_REVIEWED_JOURNAL_ARTICLE
Maturity (coded): MATURE

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD02-HQ-C13	—
2	PUBLIC-FACING CLAIM	Across three company field experiments with 4,867 software developers, access to an AI coding assistant increased completed tasks by 26.08% on average; less-experienced developers adopted the tool more and gained more.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	B — Task-level productivity and quality	—
5	MATURITY	MATURE	states: MATURE
6	SOURCE	Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026	source_ids: SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026
7	SOURCE TYPE	Peer-reviewed journal article	classes: PEER_REVIEWED_JOURNAL_ARTICLE
8	INSTITUTIONAL POSITION	Mixed; includes Microsoft Research affiliation	—
9	SCOPE	Three company developer experiments	—
10	DESIGN	Randomised field experiments	—
11	SAMPLE / DATASET	4,867 developers	—
12	MODEL / TOOL / VERSION	AI coding assistant / GitHub Copilot environment	—
13	COMPARATOR	Randomised no-access/control	—
14	MAIN RESULT	+26.08% completed tasks pooled; SE 10.3%; larger gains for less-experienced developers	—
15	INFERENTIAL TARGET	Developer task-output effect of assigned AI access	—
16	DOES NOT LICENSE	Developer employment decline; defect/quality effect beyond measured endpoints; all coding contexts	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Individual experiments noisy; selected companies; institutional-position disclosure required	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with novice-gain pattern in customer support	—
20	GEOGRAPHY / LANGUAGE	Multicompany / English	—
21	DISTRIBUTIONAL LEDGER	Less-experienced developers benefit more	—
22	R01 / FIELD-MAP LINKS	D2, L-A, R-2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Larger preregistered replications showing materially different pooled effect	—
24	PUBLICATION STATUS	ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER	state: ELIGIBLE · qualifiers: INSTITUTIONAL_POSITION
25	RECORDED DATE	2026-09-25	—

Field 22 references resolved against Field Map v0.2: D2 (DOMAIN); L-A (LENS); R-2 (LENS)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026” → Cui et al. (2026), “The Effects of Generative AI on…” (SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026--v1.0) — Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026; class PEER_REVIEWED_JOURNAL_ARTICLE (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, September 25). Across three company field experiments with 4,867 software developers, access to an AI coding assistant increased completed tasks by 26.08% on average; less-experienced developers adopted the tool more and gained more [Claim LD02-HQ-C13, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld02-hq-c13/v1.0/

@misc{sociolens_ld02_hq_c13_v1_0,
  author = {{SocioLens project}},
  title = {Across three company field experiments with 4,867 software developers, access to an AI coding assistant increased completed tasks by 26.08\% on average; less-experienced developers adopted the tool more and gained more.},
  year = {2026},
  date = {2026-09-25},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld02-hq-c13/v1.0/}},
  note = {Claim LD02-HQ-C13, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 c6943f1a47871fb0f9671519a39d5e4b078a6faae81b41b3c774f2ce436d40de.

Frozen Drive-derived inputs

R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED (v1.0) — Drive ID 1y7Iid5SaEnjKaPZ7ZsSSVj8dASVlSF8b; revision: NOT_EXPOSED_BY_DRIVE_TEXT_EXPORT; Drive modified ; block “ENTRY 13 — LD02-HQ-C13” SHA-256 f2ab1309c158023c682585ce9ec112037df9e27fcae3507246301e87e8f5d53f; SocioLens — Programme Status & Authority Register v0.6 status “CURRENT.”; frozen fixture fixtures/frozen/r05-ld02-claim-ledger-v1.0-canonical.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the locked R05 canonical ledger v1.0; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 1 authorizes completion of its existing canonical claim corpus. This is the first materialized version of this logical Claim, not a research update.
CURRENT_POINTER = true — basis: SocioLens — Programme Status & Authority Register v0.6 status for "R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED": "CURRENT."
FIELD_6_SOURCE_REFERENCE = SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026--v1.0 — basis: field 6 of ENTRY 13 — LD02-HQ-C13 cites "Cui et al., “The Effects of Generative AI on High-Skilled Work,” Management Science, 2026"; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5: this exact frozen field-6 citation segment selects SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026--v1.0 under ruling 4; identity established by B3 lines 76–102 and the pinned R05 ledger fields 6/7/8.
SOURCE_PROVENANCE_PIN = SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026--v1.0 — basis: HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5 / Publication System Amendment v1.2 §§4,6: explicit version-pinned public provenance selection of SRC-LD02-CUI-MANAGEMENT-SCIENCE-2026--v1.0 for LD02-HQ-C13--v1.0. Preserve the canonical qualification and independently authorized Source metadata.