What People Build With AI: 1,180 VCL Projects
Productivity leads VCL’s recorded project categories, followed by Developer Tools. A look at 1,180 public listings, with overlapping categories and a fixed cutoff.
Updated November 1, 2026. This article uses dataset v10, with a November 1 cutoff and measurements recorded through October 31. This is a new frozen edition; changes in sample membership, recorded classifications and measurement timing are not within-project growth.
Productivity was the most commonly recorded category in VCL’s November 2026 snapshot: 457 of 1,180 projects with category data, or 38.7%. Developer Tools came second with 237 listings (20.1%), followed by Games with 227 (19.2%).
Games remain a substantial part of this sample, alongside productivity and developer software. The public output of AI-assisted development is not confined to software for other developers.
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Correction history. The original article reported 422 productivity projects out of 1,087. The corrected v7 table has 421 out of 1,085; both round to 38.8%. The v9 edition has 437 out of 1,129 (38.7%). This update uses 457 out of 1,180 (38.7%) from v10.
The eight leading categories
The report contains 1,502 approved, public projects. These percentages use the 1,180 with recorded categories; the other 322 are missing category data.
| Recorded category | Projects | Share of projects with category data |
|---|---|---|
| Productivity | 457 | 38.7% |
| Developer Tools | 237 | 20.1% |
| Games | 227 | 19.2% |
| Business | 208 | 17.6% |
| Social | 194 | 16.4% |
| Education | 190 | 16.1% |
| Marketing | 169 | 14.3% |
| Entertainment | 158 | 13.4% |
Categories are multi-select. A productivity product may also be listed under Business or Education, so the rows are neither an exhaustive partition nor percentages that should add to 100%.
A description of products, not their success
The category mix describes what people submitted to VCL. It does not show which products attracted users, earned revenue or remained active after launch. Nor does it identify how much code AI generated: the report examines projects listed on an AI-assisted-building directory, not audited development histories.
The distinction matters when reporting on “what AI is building.” This is evidence of the types of products reaching a public directory, not a market-share estimate for all AI-built software. Private projects, internal company tools and products never submitted to VCL are outside the sample.
Productivity’s lead is clear within that boundary. Explaining *why* it leads would require evidence about builder motivations or submission patterns that this category table does not provide.
Two follow-up analyses compare AI tool choices within project categories and estimated search traffic across categories.
Data and source. State of Vibe Coding 2026, Dataset v10: project categories, cutoff November 1, 2026 at 00:00 UTC. See the edition’s methodology for inclusion rules and missing data.
The full State of Vibe Coding report also examines reported AI tools, website infrastructure, search visibility and public-page performance.