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A short reading path to understand what this site is about, and where to start based on your job.

Who am I? About · Press

Mikhail Drozdov (casinokrisa)

Who this is for

  • SEO practitioners who want clarity on indexing, authority, and AI surfaces.
  • Marketers building AI-enabled systems (workflows, quality gates, distribution).
  • Builders who want strategy and measurement that compound over time.

How to read

  1. Start with one pillar (the map).
  2. Pick 2 supporting essays for the exact problem you have.
  3. Come back weekly; this is built as clusters, not isolated posts.

Pick a path

Choose a topic hub. Start with the pillar, then read 1–2 supporting essays.

AI & Automation
Build AI-powered marketing systems. Learn to orchestrate AI tools, automate workflows, and make data-driven decisions.
Start with the pillar
AI Orchestration for Marketing: Systems, Not Prompts

For marketers: how to build AI workflows with quality gates (systems, not prompts).

SEO & Search
Master modern SEO: from pages to entities, AI overviews to topic authority. Build visibility that survives algorithm updates.
Start with the pillar
Modern SEO in 2026: Visibility, Indexing, and Why Keywords Are Not the Unit

For SEO operators: how indexing, interpretation, and AI surfaces changed what "visibility" means.

Marketing Strategy
Connect analytics, strategy, and execution. Build marketing systems that grow through accumulated context, not optimization tactics.
Start with the pillar
Marketing Strategy as a System: Positioning, Measurement, and Compounding

For builders: connect positioning, distribution, and measurement into a strategy that compounds.

Analytics & Data
Build data pipelines that connect metrics to decisions. Measure what matters: LTV, ROMI, and systems-level performance.
Start with the pillar
Analytics as Decision Infrastructure: What to Measure, What to Ignore

For teams: build measurement that drives decisions and survives attribution limits.

Latest

New posts and updates.

  • Domain Authority is not a Google metric: why score-chasing backfires

    DA/DR-style scores feel like control, but they are not what Google optimizes. This essay explains why “domain score” becomes metric theater, how it quietly pushes teams into the wrong work, and when these scores are still useful as rough proxies.

  • How to get a Knowledge Panel for a person (without hacks): the system model

    A Knowledge Panel is not something you "request". It appears when Google is confident it can resolve a stable person entity and connect it to corroborating sources. This guide explains the decision model (identity -> disambiguation -> corroboration -> persistence) and the few changes that actually increase certainty.

  • Indexing is not visibility: why Google stores pages it never intends to show

    In 2026, 'indexed' is an internal bookkeeping state, not a promise of traffic. This essay explains the missing layer between indexing and visibility: retrieval and outcome certainty. If your page gets crawled, even indexed, and still disappears, the system is not confused - it is being conservative.

The core essays

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