Yevgeny.ai

A body of writing is usually a shelf: you publish, you hope the archive gets found. Yevgeny.ai is the other move — make the archive answer. It is a citation-first "ask the writing" destination over the No Fluff corpus: one page where a visitor can ask a question, test a strategy, or trace any claim back to its source.

The pattern is borrowed with attribution: it is inspired by rishad.ai's pattern — personal corpus → conversational front door — but carries the No Fluff visual identity. The same tokens, type, and self-hosted fonts as this site, imported verbatim so they can never drift.

Citation-first is the discipline that separates it from a chatbot. Answers are grounded only in source passages and must cite them; positions, numbers, and opinions are never invented; commercial questions route to a contact CTA instead of improvised advice. And when the corpus doesn't cover a question, it says so plainly.

The August 2026 semantic-discovery upgrade turned the brain from a retrieval pipeline into a governed evidence system: the Position Graph now governs retrieval, evidence selection, synthesis, and refusal. Retrieval is hybrid — bge-m3 dense vectors in Cloudflare Vectorize (1024 dimensions) plus D1 FTS5 BM25 keyword rank, fused with reciprocal-rank fusion (K=60) over 7,689 chunks. The chunks were repacked so every chunk's embedding input fits the model's window; previously, chunks up to 6,000 characters embedded only their first 4,000.

Three further upgrades run in shadow: a cross-encoder reranker (bge-reranker-base, depth 15), a one-hop graph retrieval leg with an edge-type allowlist and a per-node degree cap of 25, and a query planner on llama-3.3-70b that produces intent, follow-up rewrites, sub-questions, and glossary anchors. All three run after the response is sent, log to the traces, and change nothing about live ranking until decision gates read the accumulated data. The hand-written regex intent gates stay in place as the degradation path.

The same discipline blocks features. An embedding-space concept atlas failed its own neighborhood-preservation gate — 0.555 measured against a required 0.60 — and ships dark until the projection earns it. The full plan is versioned in the repo at docs/semantic-discovery/PLAN.md.

Presentation only — the honest architectural note from its own README. The brain is the existing ask-evgeny worker at ask.nofluffadvisory.com: the same /api/ask contract, grounding rules, citation mapping, Position Records, and unlisted-leak filter as this site's ask widget. Generation runs on Anthropic (claude-sonnet-5); embeddings stay on Workers AI (bge-m3).

It ships as a second Astro build inside the nofluffadvisory monorepo: its own config with the root pinned to the repo root so the shared essay collection resolves identically, its own src, public, and output directories, and stylesheets inlined at build. Every number on the page — essay count, per-lens counts, glossary terms, years-span — is computed at build time from the shared sources of truth, never hardcoded.

Deploys ride the same GitHub Actions pipeline, sequenced after the main-site deploy so a yevgeny-only failure can never block nofluffadvisory.com: build, ensure the Pages project exists, publish to Cloudflare Pages. The custom domains were a one-time manual step; the worker's CORS allowlist already includes both origins.

A personal corpus with a conversational front door is becoming a visibility pattern in its own right: instead of hoping AI assistants summarize you correctly, you ship the surface that answers questions about your work — grounded, cited, and on your own domain.

That is the practice No Fluff Advisory sells — AI Visibility & GEO Advisory for AdTech, MarTech, and data companies — and Yevgeny.ai is that practice run on itself: entity engineering, citable content, and machine surfaces, applied to the advisor's own corpus. It is a receipt, not a slide.