THE PUBLISH HAVEN JOURNALS

Choose something useful to learn.

Start with a task you recognize. Follow a worked example, inspect the result and adapt it to your own work.

New to AI? Begin with AI Operator Weekly. Building software? Choose the Agentic journal or Cloud & AI Engineering Brief. Comparing claims before a decision? Read Research Review.

Try a task on the page

Compare software using your notes, draft a client proposal or keep a client's latest instructions together. See a finished document, read the notes and edit the example. No download or coding is needed.

Choose a practical lesson

Use AI in a small business

AI Operator Weekly

Practical AI workflows for agencies, consultancies and training teams, with sample files, human review and honest cost checks.

Who it helps: Founders and operations staff in small service businesses
First finished result: Two reply drafts, two client-record drafts and two inquiries held for staff review.
Publication rhythm: One substantial lesson each Sunday

Choose this path Browse published issues

Build an AI assistant

The Agentic Trading Research Journal

Build assistants that find evidence, use tools and produce work you can check. Learn through everyday applications, with trading as one specialist case study.

Who it helps: Curious beginners and developers learning how assistants work
First finished result: A quotation with its source and an explicit review step.
Publication rhythm: One numbered practical lesson each day

Choose this path Browse published issues

Operate an AI service

Cloud & AI Engineering Brief

Engineering lessons for AI services: useful-output costs, retrieval quality, deployment and recovery, with tested examples and explicit limits.

Who it helps: Engineers responsible for deploying and maintaining AI services
First finished result: A cost report that includes every attempt and divides full cost by accepted tasks.
Publication rhythm: One substantial brief every two weeks

Choose this path Browse published issues

Evaluate AI evidence

Publish Haven Research Review

Investigate AI applications, research and business claims through primary evidence, practical worksheets and clearly stated uncertainties.

Who it helps: Team leaders and practitioners deciding what to test, adopt or question
First finished result: A one-page evidence worksheet and a bounded test-or-hold decision.
Publication rhythm: One substantive investigation each Saturday

Choose this path Browse published issues

What you should expect from a lesson

A clear goal, sample inputs, a finished result, complete instructions and an example that goes wrong. Each investigation explains what was tested and what remains uncertain. A scripted replay is labelled; it is not presented as a measured AI result.

The journals use an AI editorial workflow. Review records support the stated checks; they are not academic peer review. Explore other writers on Publish Haven.