Content Quality: 665 words, within the News range of 400-1200. Clear Overview/What We Know/What We Don't Know/Analysis structure, appropriate caveats.
Source Verification: Read both snapshots from disk (gunzip; sha256 of uncompressed content matches manifest for both). source-0.html.gz (doi.org/10.3386/w35793, redirected to nber.org) is NOT abstract-only: it is the full 3.8 MB application/pdf of NBER Working Paper 35793, 'The Macroeconomic Effect of AI: Sizing the Software Engineering Channel', Blumenfeld, Hazell, Lian, Schaab, September 2026 (extracted with pdftotext; full body incl. introduction, Section 3.4, Section 4, appendices). Verified verbatim/near-verbatim against the paper: authors and affiliations (Blumenfeld, Lian, Schaab at UC Berkeley; Hazell at LSE); 'NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed'; abstract 'From November 2022 to December 2025, AI increased the market's expected present value of software engineering productivity by the equivalent of a permanent 32.6% productivity increase'; GDP effect 3.6% baseline and 6.5% with R&D; 'By mid-2026, amid rapid progress in coding agents, the effect of AI on productivity and GDP had more than doubled relative to the end of 2025'; THNQ ROBO Global AI index first-stage regression; Revelio Labs payroll shares; second-stage slope 1.24; exclusion of software-producing and semiconductor-supply-chain firms; eBay, Sonos, Expedia, Airbnb; 'The view from financial markets is unlikely to be perfectly accurate'; 21-56% task-level speed-ups (Peng et al. 2023; Paradis et al. 2025) and the complementarities/bottlenecks sentence; 3.61% GDP figure (eq. 1451) and 'this estimate excludes news after the end of 2025'; 'news about AI-driven software engineering productivity exceeding the total over the previous three years. One likely reason is the widespread introduction and adoption of coding agents, such as Claude Code and Codex, in 2026. We plan to monitor this series as the frontier of AI continues to expand.' source-1.html.gz (The Register, Thomas Claburn, 29 Sep 2026) confirms: 32.6% quote, Berkeley/LSE attribution, method paraphrase ('Rather than measuring developers' output directly, the researchers examined how company stock returns respond to news about AI...'), Lian's email quotes (markets can be overly optimistic or pessimistic; employment among covered firms preliminarily increased but the estimate does not depend on it; follow-up work on other channels), 21-56% comparison and bottlenecks. The Register is cited only for method, Lian's remarks and follow-up work, and attributes the same figures. suspicious_patterns is null for both sources; nothing to adjudicate. Allowlist: theregister.com and doi.org are both already allowlisted; nber.org (the redirect target) is not, but the script raised only an info-level redirect note and the checklist 'no blocklisted domains' passes. Recommendation: add nber.org to the academic section of config/source_allowlist.txt (reputable primary host for working papers, consistent with nature.com/science.org precedent); not done here because it is an allowlist policy change outside this review.
Factual Accuracy: Every number, name, date and quotation in the body traces to the paper or The Register. The 32.6% is correctly defined in the Overview and body as the market's expected present value of software engineering productivity, equivalent to a permanent increase, for Nov 2022-Dec 2025 (a news-based expectation, not measured output), estimated from non-software-producing firms. No sentence states that developers ARE X% more productive; the Overview explicitly states 'The paper measures investor expectations, not developer output.' The 'more than doubled by mid-2026' claim is faithful to the abstract (title's 'Roughly Doubling' is a mild understatement of 'more than doubled', acceptable). Coding agents are correctly framed as 'one likely reason' / coincident, not a measured cause (the paper: 'This acceleration coincides with...'); the title's 'as Coding Agents Spread' is slightly stronger than that but the body and 'What We Don't Know' section carry the correct hedge.
Overall Assessment: Accurate, well-hedged article on a primary-source NBER paper with full-text verification. Script auto-verdict APPROVE_WITH_CORRECTIONS (title length warning only) overridden to APPROVE by the Chief Editor.