First, be useful.
Then, earn trust.
A content-first publication for AI/SaaS founders and small teams, focused on the US market.
FindVex begins with a question: how do people who can build a product learn to get it discovered? Our first job is to publish useful answers and develop evidence that readers can inspect.
Current stage: the publication foundation and three launch guides. The milestones below are planned outputs, not achieved traffic or citation results.
One audience, three connected subjects
We write in English for AI/SaaS founders and small teams, with the United States as our primary market. Search research uses US English by default. The initial focus is search discovery through SEO and AI search, supported by founder marketing, content writing and social distribution.
Each guide should help with a real task: choose a topic, fix a discovery problem, explain a product, reach a relevant audience or measure an outcome honestly.
Our first 90 days
Make a useful starting point.
Launch the publication, publish the first three guides and prepare a focused research backlog. Establish a measurement baseline.
Answer the next questions.
Work toward 8–10 reviewed articles, linked around reader needs. Begin a small distribution experiment and prepare original evidence.
Let the work teach us.
Work toward 16–20 articles. Improve existing guides using observed questions and feedback. Publish a transparent progress report.
Build on useful signals.
Aim for 24–30 articles in total, including 3–4 evidence-led studies or reports. Decide what deserves more attention next quarter.
What will make the work worth reading
Useful examples, clearly explained methods, sources you can check and original observations. We will label hypothetical examples and distinguish proposed methods from completed experiments.
Publishing targets depend on the time needed to research and review the work. We will not use article volume as proof that the publication is succeeding.
How we will judge progress
We intend to review relevant search impressions and visits, indexing, repeat readership, independent references and sampled AI citations. Brand mentions, citations and referral visits will remain separate measures.
Reports should show the period and method, including missing data. We will publish what we learn without promising a search ranking or treating every change as proof that one tactic caused it.
What comes later
For now, the work is the publication. Repeated reader problems may inform future services or products. Those decisions will follow the evidence.