AI tooling sector analysis

Diversum maps where AI software ecosystems converge.

We publish evidence-grounded Sector Radar reports that show the default patterns forming in AI tooling, where real differentiation survives, and what builders should understand before choosing or building.

Live sector map
3published radars
78repos mapped
5evidence dimensions

Field Brief

AI Tooling Convergence Field Brief

A source-backed synthesis from three accepted public Sector Radar reports covering 78 public repositories across MCP memory, browser-extension starters, and IDE-native AI coding agents.

3public Sector Radar reports
78public repositories in scope
0methodology or scoring changes
1public URL for outreach

Latest publication

Sector Radar: VS Code AI Coding Agent Extensions

Our third public report analyzes 22 source-verified VS Code AI coding-agent extensions, mapping the IDE-agent default, protocol-client boundary, lineage signals, and Super Cluster bridge relevance.

22in-cluster accepted candidates
23%Category Leaders
0%Inactive Scaffold rate
3.55Convergence Index

Second publication

Sector Radar: Chrome Extension Starters

Our second public report analyzes 24 fork-and-build Chrome extension starter repositories, mapping a sharply converged MV3 + TypeScript + Vite + React default and the gaps still open for builders.

24in-cluster starter repos
54%Strong Defaults
0%Inactive Scaffold rate
4.00Convergence Index

First publication

Sector Radar: MCP Memory Servers

Our first report analyzes 32 repositories connected to MCP memory, separating primary MCP memory servers from adjacent infrastructure and mapping the cluster roles that define the sector.

32repositories reviewed
20in-cluster MCP memory servers
45%differentiated niche projects
25%category leakage in the full corpus

Public posture

Radar, not leaderboard.

Diversum measures convergence patterns. It does not claim AI authorship, and it does not turn maintainers into targets. Public reports describe sectors; private audits help builders inspect their own work.

Public Sector Radar

Ecosystem-level reports that make defaults, category leakage, and differentiation visible.

Private Diversum Audit

Voluntary repo or idea review for builders who want evidence-grounded convergence feedback before publication.

About

About Diversum

Diversum publishes evidence-grounded sector analysis for AI tooling ecosystems. Our interest is in mapping how open-source AI infrastructure converges, differentiates, and forms defaults.