SWFT wants readers to understand both the claim and how much confidence to place in it. Every article shows its sources, the kind of evidence behind each important statement, where the work came from, and the date of its source window.
What do SWFT's evidence labels mean?
Observed artifact (OBS)
SWFT inspected a public artifact or dated event, such as a page, transcript, repository, release, or document. “Observed” proves what the artifact showed on its recorded access date. It does not prove every claim inside that artifact.
Independent study (STUDY)
The claim comes from research with a described method, sample, evaluation, or analysis. SWFT keeps the population and limits visible. One benchmark or study does not become a universal rule.
First-party report (SELF-REPORT)
A person or organization is describing its own product, system, customers, or results. First-party accounts can contain valuable operating detail. SWFT attributes them and does not present them as independent comparisons.
Analysis (INFERENCE)
This is SWFT's own definition, classification, recommendation, or conclusion drawn from named evidence. Readers can inspect the support and disagree with the interpretation.
The short codes stay in Markdown and data exports so machines and repeat readers can identify the category reliably. The visible labels use everyday language.
How does SWFT choose sources?
SWFT prefers primary research and corrections, official documentation or artifacts, and detailed first-party operating accounts. Independent reporting follows. Secondary summaries help us discover a topic, but they should not carry a factual claim when the underlying source is available.
AI Engineer's 2026 program, Latent Space, and Smol News are useful radar for current vocabulary and debates. SWFT follows those signals to the talk, paper, repository, release, specification, or operator account behind a claim whenever possible.
Commercial affiliation does not disqualify a source. It changes what the source can establish. Product capabilities and company metrics remain first-party reports until independent evidence supports a stronger statement.
How does SWFT choose company cases?
A company enters the comparison when public first-party evidence describes a repeatable path from incoming work through agent action, verification, and a handoff or decision. General use of a coding assistant, one impressive demo, or a product announcement is not enough by itself.
SWFT prefers cases with several dated sources, concrete operating detail, visible artifacts, or reported outcomes. A case can still qualify when the implementation is private, but the access limit and missing evidence must be stated. Inclusion is not a ranking, endorsement, or claim that the archive is complete. It means the public record is detailed enough to teach and compare without inventing the missing parts.
What rules apply to claims?
- Numbers name the organization, population, date, and method available in the source.
- Benchmarks explain what tasks and scoring rules they cover.
- Changing maps and product descriptions show their source-window date.
- Quotations stay short unless SWFT has permission to republish the work.
- “Unknown” stays unknown. Missing public evidence is not proof that something does not exist.
- A model-generated summary never replaces the underlying source.
How does SWFT use AI in editorial work?
SWFT Editorial guides, comparisons, references, and company cases are AI-drafted from cited public sources. Their institutional byline and authorship disclosure appear in HTML, Markdown, feeds, and structured metadata. Ben Guo's personal byline is used only for his authenticated imported essay.
Each admitted page has a dated review record naming the second AI editorial-review agent (Codex), the scope of that check, the evidence type, the closest overlap, the risk if a claim is wrong, and the maintenance trigger. SWFT does not imply that a human or site owner reviewed a page, and an AI editorial check is not qualified clinical, legal, or financial review.
AI drafting does not change the evidence standard. Every factual claim still needs the appropriate source boundary, first-party reports stay labeled, and SWFT Editorial remains responsible for corrections.
Can automation publish an SWFT article?
No. Discovery automation may find, normalize, and group possible sources, but it cannot create a publication record or change a public route. A separately recorded editorial admission must identify the reader job, claim boundary, evidence fit, overlap decision, reviewer, risk, and maintenance plan before a page can enter the registry.
One admitted record drives the HTML page, Markdown version, metadata, structured data, feeds, and source list. A question section is added only when it resolves a follow-up decision the article body does not already answer, and the same wording then powers visible and structured representations. SWFT does not maintain hidden answer-engine copy.
Corrections
How do I request a correction?
Send @hraness a public message on X and include the SWFT page, the disputed sentence or record, and the strongest source you have. The SWFT repository is private, so a GitHub issue link would not be a usable public correction form.
SWFT will reproduce the issue, decide whether it concerns fact, attribution, interpretation, link, or presentation, and correct the canonical record plus every derived surface. A meaningful correction changes the modified date. If the earlier version could materially mislead, the page receives a visible note. Spelling and presentation fixes that do not change meaning can remain silent.
Current corrections
No material corrections have been recorded as of September 2, 2026.
The DORA 2025 errata is one useful model: keep corrections close to the work they qualify and preserve the history. Corrections are part of a trustworthy publication, not something to hide.