Workflows & Build

Practical AI systems, explained through evidence and real engineering choices.

A fluent answer is not proof that an agent can choose the right tool, respect a boundary or recover from failure. Learn how to evaluate the job, record traces, test failures and grant authority only when the evidence supports it.

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News & Signals

Open protocols are moving agent systems away from one-off integrations. These reports explain what changed, what remains unsettled and what builders should verify.

EDITOR'S PICKS

Four practical starting points for evaluating AI systems, workflows and local hardware without hiding the trade-offs.

Start here

Build systems that remain inspectable.

Stariy.com turns promising demonstrations into bounded, testable and reversible systems.

Evidence
Keep sources, dates and assumptions visible.
Boundaries
Match authority to the consequences of failure.
Recovery
Design monitoring, approvals and rollback from the start.
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Explore the system

01

AI Systems

Architecture, agents, retrieval, evaluation and controls.

02

Workflows

Repeatable operating steps beyond prompt tricks.

03

Reviews & Research

Decisions supported by explicit criteria and limitations.

04

Build Logs

Decisions, failures and changes without polished-away uncertainty.

About the publication

Independent analysis for people building real AI systems.

Stariy.com is an independent publication by Stanislav Yanchenko about practical AI systems, agent workflows, infrastructure and evidence-based technology decisions. Sources, dates, assumptions and limitations stay visible so readers can distinguish a useful method from a temporary product claim.

About Stanislav and the publication →

DEVICE MATERIALS

AI Hardware for Local Workloads

Evidence-led reviews of compact AI systems, with dated specifications, real product views and a practical comparison.