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Methodology

How this wiki was made, what its labels mean, and where it can be wrong.

Sources

  • Videos: the uploads of Higgsfield AI's YouTube channel (long-form, Shorts, livestreams) and the lessons of Higgsfield Academy: 533 recordings recordings (41 hours), 2025–2026.
  • Texts: 666 texts Higgsfield blog articles, changelog entries, help-centre articles and tool, model, MCP and app pages. Tool and app pages describe the product on the day they were saved ("as of"), not a release date.
  • Comments: the channel's own comments, and viewer questions the channel answered (the question is shown as the context of the answer; viewers' words are never recorded as the channel's).
  • Transcripts: Whisper large-v3; the channel uploads no captions. Model and tool names are normalised to their official spelling; misheard names may remain in quotes.

How each source was read

  1. An analyst model reads the transcript or text and records statements (how-to steps, recommendations, capabilities, limitations, prompt patterns, settings, prices, workflow stages, comparisons, studio practice, releases), the models, tools and techniques named, and dated answers to practice questions.
  2. A second model audits that record against the source and fixes invented or distorted content, wrong attribution, marketing read as fact, and missed answers.
  3. Code checks that every quote and evidence span is copied from the source and anchors it to its time.
  4. A registrar merges new models, tools, techniques and threads into one registry.

Nothing is added from outside knowledge.

Labels

  • Vendor claim: a marketing statement by Higgsfield or a model maker ("no identity drift", "15× cheaper"). Kept, never used as an answer on its own.
  • One creator's experience: what worked for one creator on one project with one model version.
  • Time-bound: an offer or deadline, shown with its end date and left out of evergreen answers.

Practice questions

Each answer is dated and attributed: first on record, restate, refine, shift, revise, tension

Threads and their statuses

A thread follows one thing across sources. Its status is a state, not the last thing that happened:

kind status
release history proposed, running, completed, lapsed; completed, not continued; last documented in YYYY when nothing new is recorded for over two years; known from looking back
promise kept, kept late, dropped, changed; the project it belongs to reported its result; standing commitment; open (no report in 2025–2026); open (updates through YYYY, not reported done); postponed (YYYY); not reported kept; said in jest (not tracked)
ask reported back; the project it belongs to reported its result; asked again year after year; asked again in N years (YYYY–YYYY); asked in YYYY; no response reported; reminder only; promotion, announcement, invitation, joke or advice (not a request)
prediction came true, partly came true, proved wrong, or unresolved (no horizon named); due YYYY; outcome not yet known; its date passed (YYYY); no outcome reported; said in jest (not tracked)
story told N×; followed over N videos; updates only

The events on a thread are named:

kind events
ask asked, reminder, result reported, thanks, closed
prediction predicted, repeated, recalled, came true, partly came true, proved wrong
promise promised, progress update, kept, dropped, changed, kept late, postponed, recalled
project history proposed, announced, launched, milestone, setback, rule change, paused, restarted, outcome, looked back
story told, retold, update, mentioned, stopped

Dates

Dates are upload dates, which set the order. Where the speaker gives a different recording date in the video, it is added as "said on YYYY-MM-DD, implied" (derived from the date said in the video).

Limits

  • Machine reading makes mistakes; the audit catches many, not all.
  • Coverage ends October 24, 2026: later releases and changes in advice are not here.
  • Prices, limits and plans change often; every figure carries its date.