Stanislav Yanchenko

October 14, 2026

Workflow vs Autonomous Agent vs Multi-Agent System: Choose the Smallest Architecture

The most capable architecture is not automatically the best architecture. A fixed workflow, one tool-using agent and a multi-agent system trade predictability for flexibility at different rates.
October 14, 2026

How My AI OS Is Built Around Projects Workflows Agents and Controlled Automation

My AI OS is a control and knowledge system around my work. It connects projects, persistent workspaces, reusable workflows, agent roles and tools. Its memory does not belong to one conversation, and its authority does not come from a model saying that an action seems reasonable.
October 14, 2026

Human-in-the-Loop AI: Where Approval Helps and Where It Becomes Theatre

Adding an “Approve” button does not automatically make an AI workflow safe. Human review works only when the reviewer has the information, time and authority to detect a meaningful problem before the action occurs.
October 14, 2026

Continual Improvement for AI Agents: Turn Failures Into Verified Capability

An agent does not improve merely because it performs more tasks. Experience becomes capability only when outcomes are evaluated, lessons are represented in the right layer and changes pass regression tests.
October 14, 2026

How Coding Agents Work: Context Sandboxes Tests and Recovery

A coding agent is not a model that produces a large code block. It is a tool-using system that can inspect a repository, edit files, run commands, observe failures and repeat the cycle until an external check says the change works.