Evidence

What the numbers mean.

Each claim keeps its source, date, attribution, and limit.

11 public measures · updated July 30, 2026

Numbers

11 claims, each with its limit.

Learning reach

Enrollment and launch measures for three AI courses.

About half

of course enrollments accompanied a W&B account created the same day

An observed same-day association, not a causal conversion claim.

Scope
work
Attribution
direct
Period
2024–2026 · as of 2026-07-30
Source
Internal analytics
SourcesInternal analytics — rounded public summary
1K+

Evals-course signups in roughly 36 hours

Rounded down from the internal launch checkpoint.

Scope
work
Attribution
direct
Period
~36 hours · as of 2025-01-10
Source
Internal analytics
SourcesInternal analytics — rounded public summary

Product adoption

Rounded usage measures for the W&B MCP Server.

200K+

MCP tool calls through July 29, 2026

Rounded down from the July 29 internal analytics checkpoint; direct project usage, not revenue.

Scope
work
Attribution
direct
Period
Through July 29, 2026 · as of 2026-07-29
Source
Internal analytics
SourcesInternal analytics — rounded public summary
More than two-thirds

of weekly active MCP users were returning users

Weekly active-user composition at the cited checkpoint.

Scope
work
Attribution
direct
Period
Week of 2026-06-07 · as of 2026-06-11
Source
Internal analytics
SourcesInternal analytics — rounded public summary
Hundreds

of MCP users re-engaged in a week

Rounded weekly re-engagement checkpoint.

Scope
work
Attribution
direct
Period
Week of 2026-07-20 · as of 2026-07-28
Source
Internal analytics
SourcesInternal analytics — rounded public summary

Program impact

Reach and supported-pipeline measures for public programs.

$4M+

in supported event pipeline across tracked 2024–2025 programs

Supported pipeline across tracked event programs; not revenue, closed ARR, or personal attribution.

Scope
portfolio
Attribution
associated
Period
2024–2025 · as of 2025-10-01
Source
Internal analytics
SourcesInternal analytics — rounded public summary

Archive reach

Counts derived from published project records.

49

dated public event and session references

Unique inventory rows; recordings and mirrors are counted separately.

Scope
collection
Attribution
contextual
Period
2021–2026 · as of 2026-07-30
Source
Public footprint inventory
SourcesPublic footprint counting methodology
19+

hours of public talks and interviews

Derived from 23 unique recording durations; mirrors and excerpts are excluded.

Scope
collection
Attribution
contextual
Period
2021–2026 · as of 2026-07-30
Source
Public footprint inventory
SourcesPublic footprint counting methodology

Method

Three rules.

184 source records support 82 projects and series. Related records remain searchable without being counted twice.

  1. 01

    Count each project once

    Recordings, translations, mirrors, profiles, excerpts, and source pages do not inflate the total.

  2. 02

    Separate contribution from causality

    Individual contribution, program reach, supported pipeline, and organization outcomes remain separate.

  3. 03

    Keep the limit beside the claim

    Each derived measure keeps its period, source, attribution, rounding, and caveat.

Sources

198 sources.

198 sources49—72 shown
  1. 049
    Emad Mostaque / Stable Diffusion — KoreanWeb page · wandb.aiSupports Gradient Dissent transcripts and production
    Open source ↗
  2. 050
    AI in Production: Evals & ObservabilityWeb page · toronto.aitinkerers.orgSupports Production AI evaluation and observability
    Open source ↗
  3. 051
    NYC AI Innovators MeetupWeb page · wandb.aiSupports NYC AI Innovators meetup
    Open source ↗
  4. 052
    Mastering GenAI ApplicationsWeb page · wandb.aiSupports Building GenAI applications
    Open source ↗
  5. 053
    NYC CoreWeave/W&B Workshop Attendee RecapWeb page · linkedin.com
    Open source ↗
  6. 054
    Fine-Tuning the GPT Model Series for Agent ApplicationsVideo · youtube.comSupports GPT model fine-tuning for agent applications
    Open source ↗
  7. 055
    Evaluating and Integrating ML Models — Apple PodcastsWeb page · podcasts.apple.comSupports ML model evaluation and integration
    Open source ↗
  8. 056
    Enhancing LLM Agent Performance through Dynamic Plugin Selection and W&B PromptsWeb page · wandb.aiSupports LLM-agent performance through dynamic plugin selection
    Open source ↗
  9. 057
    WandBot: GPT-4 Powered Chat SupportWeb page · wandb.aiSupports WandBot documentation assistant
    Open source ↗
  10. 058
    Build and Deploy LLM-Based AppsWeb page · luma.comSupports LLM applications from build to deployment
    Open source ↗
  11. 059
    Best AI Courses for LLM EvaluationWeb page · research.com
    Open source ↗
  12. 060
    Scaling AI with PrecisionWeb page · wandb.aiSupports Scaling AI systems with precision
    Open source ↗
  13. 061
    Deploying Models to Azure ML with Weights & BiasesWeb page · wandb.aiSupports Model deployment to Azure ML with W&B
    Open source ↗
  14. 062
    Microsoft Ignite BRK101 Japanese Recap — Part 2Web page · zenn.dev
    Open source ↗
  15. 063
    How to Create a Biomedical RAG Application Using Snowflake Arctic for PubMed Paper UnderstandingWeb page · wandb.aiSupports PubMed RAG with Snowflake Arctic and Weave
    Open source ↗
  16. 064
    l5kit-ray-wandb-demoCode · github.comSupports Scaling motion prediction with L5Kit, Ray, and W&B
    Open source ↗
  17. 065
    How Do We Actually Evaluate LLM Apps?Web page · nyc.aitinkerers.orgSupports Practical evaluation for LLM applications
    Open source ↗
  18. 066
    Developer's Guide to LLM PromptingWeb page · wandb.aiSupports W&B AI curriculum: prompting, evaluation, and agents
    Open source ↗
  19. 067
    Bay Area AI + Ray Summit MeetupWeb page · linkedin.comSupports Bay Area AI + Ray Summit meetup
    Open source ↗
  20. 068
    Orchestrating Reproducible AutoML Experiments using PyCaret, W&B, and PrefectWeb page · app.qwoted.comSupports Reproducible AutoML with PyCaret, W&B, and Prefect
    Open source ↗
  21. 069
    Agent ObservabilityWeb page · wandb.aiSupports Agent observability in practice
    Open source ↗
  22. 070
    Iterating On and Evaluating Production-Ready RAG Applications with Gemini and W&B WeaveVideo · youtube.comSupports Evaluating production RAG with Gemini and Weave
    Open source ↗
  23. 071
    Evaluation course #1Code · github.comSupports W&B AI curriculum: prompting, evaluation, and agents
    Open source ↗
  24. 072
    FourthBrain Graduate TestimonialWeb page · fourthbrain.ai
    Open source ↗