#llmsmap.me

Independent technical audit

kvinogradov.com

kvinogradov.com

Overall AI readiness score

A combined result across all audit signals.

86of 100Excellent
AI readiness audit: 7/21/2026Public technical data

Overall AI readiness assessment

How ready kvinogradov.com is for AI systems

86/100

Konstantin Vinogradov was independently audited by llmsmap. kvinogradov.com currently scores 86/100 for AI readiness. The result combines AI-specific files, crawler policy, sitemap discovery, structured homepage data, and—when available—the mobile Google Lighthouse technical profile.

Audit context

llms.txt is accessible and contains 1,501 tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.

robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. The homepage exposes Schema.org types Person, WebSite; 9 OpenGraph tags were found and markup completeness is 90%.

The mobile Lighthouse profile adds Performance 99/100, Accessibility 100/100, Best Practices 100/100, SEO 100/100, and experimental Agentic Browsing 100/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.

Confirmed strengths

  • Accessible llms.txt
  • 1 sitemap declaration
  • Schema.org: Person, WebSite
  • Complete social metadata
  • Strong Google agentic signals

Priority improvements

  1. 1Add llms-full.txt for richer first-party context.
llms.txt tokens1,501
llms-full.txt tokens
ai.txt
sitemap.xml

Google Lighthouse technical profile

A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.

Mobile · Lighthouse
99

Performance

100

Accessibility

100

Best Practices

100

Technical SEO

100

Agentic Browsing

What these results mean

The mobile page renders efficiently; its largest visible content block appeared in 1.7 s.

Accessibility scored 100/100, Best Practices 100/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 100/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.

1

Free the main thread and accelerate the first view

Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.

2

Reduce code that loads without helping the page

Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.

3

Reduce network delay

Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.

FCP1.6 s

First content

LCP1.7 s

Main content

CLS0

Layout stability

TBT40 ms

Blocking time

SI1.6 s

Visual speed

Metric glossary
FCP · First content
When the first text or image appeared on screen.
LCP · Main content
When the largest visible element in the first viewport rendered.
CLS · Layout stability
How much content shifted unexpectedly while loading; lower is better.
TBT · Blocking time
How long the browser main thread could not respond quickly to input.
SI · Visual speed
How quickly the visible viewport filled with content.
7/21/2026Lighthouse 13.4.0Mobile profile

AI readiness checks

Machine-readable files, crawler policy, discovery, and homepage markup.

llms.txt

File found and accessible

https://kvinogradov.com/llms.txt
llms-full.txt

Full version was not found

ai.txt

ai.txt file was not found

Sitemap in robots.txt1

1 sitemap found

Schema.org (JSON-LD)

Types: Person, WebSite

OpenGraph90%

9 OG tags found

AI bot access

Based on robots.txt analysis

GPTBotNot mentioned
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedNot mentioned
ClaudeBotNot mentioned
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotNot mentioned
PerplexityBotNot mentioned
Perplexity-UserNot mentioned

Sitemaps

Declared discovery routes for crawlers and agents.

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 90%
og:site_nameKonstantin Vinogradov
og:localeen_US
og:typewebsite
og:titleKonstantin Vinogradov
og:urlhttps://kvinogradov.com/
og:descriptionKonstantin Vinogradov — VC investor in open source, AI, and infrastructure. Notes on venture capital investments, tech startups, open source and philanthropy.
og:image:width1200
og:image:height630

Schema.org markup

Structured entities and properties exposed on the homepage.

Types found: 2 · Properties: 4
PersonWebSite
nameKonstantin Vinogradov
urlhttps://kvinogradov.com
descriptionVC investor specializing in open source, AI, and infrastructure software. Angel investor and founder of the Open Source Endowment.
sameAshttps://github.com/vinogradovkonst, https://linkedin.com/in/kvinogradov, https://x.com/@vinogradovk
# Konstantin Vinogradov

> VC investor specializing in open source, AI, and infrastructure software. Previously General Partner at Runa Capital ($600M+ AUM). Based in London, often in the SF Bay Area.

Notes on venture capital, tech startups, open source, and philanthropy.

## About
- [Konstantin Vinogradov](https://kvinogradov.com/): Personal page with background, investments, philanthropy, and writings on venture capital, open source software, and technology startups.
- [Writing](https://kvinogradov.com/writing/): A collection of articles exploring open source growth, investment theses, OSS funding, and developer ecosystem analysis.

## Venture Capital and Investments
- [Investment in open source AI agent framework Mastra](https://kvinogradov.com/mastra/): Investment thesis on Mastra, the leading open source TypeScript AI agent framework. Discusses the agentic AI market, the distinction between "AI People" (Python) and "Software People" (TypeScript), and why TypeScript-native AI tooling matters. Mastra raised a $13M seed round.
- [Investment in open source CRM Twenty](https://kvinogradov.com/twenty/): Investment thesis on Twenty, the leading open source CRM. Covers the history of open source business infrastructure, Salesforce's dominance, and how Twenty is building a modern, data-centric, AI-native CRM platform. Runa led the $5M seed round.
- [Investment in open source AIOps platform Keep](https://kvinogradov.com/keep/): Investment thesis on Keep, an open source AIOps and alert management platform. Discusses enterprise alert fatigue, observability stack fragmentation, and how open source can outperform closed-source incumbents in adapting to diverse enterprise environments. Runa led the pre-seed round. Keep was later acquired by Elastic.
- Other select investments include [Entire](https://entire.io/) (next-gen developer platform for humans and AI agents), [Dosu](https://dosu.dev/) (AI teammate for engineering teams), [White Circle](https://whitecircle.ai/) (AI guardrails and red-teaming), [Higgsfield](https://higgsfield.ai/) (AI video/image generator, $100M+ ARR), and [Sidekick](https://www.meetsidekick.com/) (work-focused browser, acquired by Perplexity).
- [Runa Capital](https://runacap.com/): Global venture capital firm where Konstantin was a General Partner. Portfolio includes n8n, Mambu, Nginx, MariaDB, and Pasqal.

## Open Source Research and Initiatives
- [It's time for the Open Source Endowment](https://kvinogradov.com/osendowment/): Thesis and launch of the Open Source Endowment — the world's first endowment fund dedicated to sustainably funding critical open source software maintenance. Covers why 96% of codebases depend on OSS yet 60% of maintainers are unpaid, why current funding models fall short, the university endowment analogy, and how OSE works as a US 501(c)(3) with ~$700K from 60+ founding donors including the founders of HashiCorp, Elastic, ClickHouse, Supabase, NGINX, Vue.js, Pandas, Pydantic, and curl.
- [Open Source Endowment website](https://endowment.dev/): The first endowment fund exclusively dedicated to open source software, enabling sustainable long-term funding for OSS maintainers. Community-led nonprofit founded in 2025.
- [ROSS Index](https://runacap.com/ross-index/): The Runa Open Source Startup Index, tracking the fastest-growing open source startups quarterly from 2020 to 2025 based on GitHub star growth.
- [GitHub repo with OSS startup alternatives to SaaS](https://github.com/RunaCapital/awesome-oss-alternatives): A curated list of open source startup alternatives to traditional SaaS products.
- [What Open Source can learn from universities to fix its funding](https://kvinogradov.com/oss-universities/): Original proposal arguing that open source communities resemble research universities in culture and function, and that the endowment model used by top universities can solve the OSS sustainability crisis.
- [How I algorithmically donated $5,000+ to OSS via GitHub Sponsors and PyPI data](https://kvinogradov.com/algo-sponsors/): A data-driven experiment in algorithmic open source philanthropy. Analyzes GitHub Sponsors data, PyPI download distributions, and the disconnect between project popularity and importance, culminating in microgrants to 866 GitHub users.
- [Open Source Growth Benchmarks and the 20 Fastest-Growing OSS Startups](https://kvinogradov.com/open-source-growth-benchmarks/): Introduces open source growth benchmarks using GitHub stars and forks, reveals power-law distributions in OSS popularity, and presents the first top-20 fastest-growing OSS startups list (Q2 2020).
- [More Open Source Benchmarks, the ROSS Index and the Fastest-Growing OSS Startups](https://kvinogradov.com/more-oss-benchmarks/): Extends OSS benchmarks with programming language-specific analysis (Go, Python, C++, Java, JavaScript, etc.), introduces the ROSS Index methodology, and presents Q3 2020 fastest-growing startups.
- [Open Source Contributors Analysis and deep dive into OSS databases](https://kvinogradov.com/oss-contributors-analysis/): Comprehensive contributor analysis applying product analytics (MAU, retention, engagement, churn) to open source databases. Introduces the concept of "active qualified contributors" and uses the Herfindahl-Hirschman Index for measuring OSS project decentralization.

## Media and Recognition
- [Media page](https://kvinogradov.com/media/): Selected publications, presentations, and media comments. Quoted in TechCrunch, Wired, Bloomberg, Business Insider. Published in InfoWorld and LeadDev. Speaker at Cambridge University, DevDays Europe, Connected Data World, OpenCore Summit. Awards: OpenUK Honours List (2026), Data-Driven VC Top 100 Thought Leaders (2024), UK Global Talent Visa (2022).

## Philanthropy and Community Engagement
- [Project leader for a tech charity](https://kvinogradov.com/charity-leader/): A job description for leading a next-gen nonprofit initiative at the intersection of fintech, developer tools, and social impact.

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Added 7/19/2026
kvinogradov.com - AI readiness audit | llmsmap.me