Vizuara AI Labs - harness engineering Workshop

Description:

Harness Engineering: A Practical Masterclass — a 5-day practical workshop on creating your own working harness for AI coding agents. During the training, you will dissect the architecture of the agent loop, learn to manage tools, context, memory, and session recovery, and in the end, build and present your own coding-agent harness.

What This Masterclass Is About

The course is dedicated to the practical development of a harness—the management layer for an AI coding agent that integrates the model, tools, environment, memory, context, and human participation into a unified working system.

Instead of abstract theory, you sequentially go through the entire cycle of creating an agent system: from basic architecture and tool integration to error processing, state recovery, subagent work, and preparing a production-ready solution.

Practical benchmarks like Claude Code, pi, and Hermes are considered, as well as current approaches to building AI coding agents and autonomous development systems.

What You Will Learn

• Design the architecture of the agent loop for AI coding agents.

• Create your own harness to manage agent actions.

• Connect tools, environments, and external commands to the agent system.

• Configure the management of context, memory, and execution history.

• Implement session recovery after errors and interruptions.

• Use subagents for task segmentation and increased reliability.

• Integrate human-in-the-loop scenarios to control critical decisions.

• Prepare the coding-agent harness for demonstration and further development.

5-Day Workshop Program

Day 1: AI Coding Agent Architecture

You will explore the components of a modern coding agent: model, decision-making cycle, tools, file system, execution environment, and management interface.

• The role of harness in agent architecture.

• Basic agent loop: observation, planning, action, result verification.

• Exploration of Claude Code, pi, and Hermes operating principles.

• First version of your own minimal harness.

Day 2: Tools, Environment, and Command Execution

The second day focuses on the practical integration of the tools that the AI agent interacts with: shell commands, file system, tests, linters, repository, and development environment.

• Safe command execution by the agent.

• Interfaces for reading, modifying, and analyzing code.

• Connecting quality checks and tests.

• Logging agent actions and execution results.

Day 3: Context, Memory, and State

Learn to manage context so the agent retains relevant information, doesn't lose task objectives, and can continue work over long sessions.

• Strategies for prompt formation and working context.

• Short-term and long-term agent memory.

• Compression, updating, and prioritization of context.

• Project state storage and decision history.

Day 4: Session Recovery, Subagents, and Human-in-the-Loop

On the fourth day, you will add resilience mechanisms to the harness: error recovery, task delegation to subagents, and human participation in critical decision-making.

• Recovery of agent session after an error or interruption.

• Task division among specialized subagents.

• Control of risky actions through human-in-the-loop.

• Enhancing reliability and predictability of AI coding agents.

Day 5: Final Assembly and Project Demonstration

In the final phase, you will integrate all the components into a working coding-agent harness, prepare a demonstration, and receive feedback on architecture, implementation quality, and possible improvements.

• Assembly of a production-ready harness version.

• Verification of the complete agent loop on a practical task.

• Participant project demonstrations.

• Analysis of typical errors and directions for further development.

Practical Results After Training

The main result of the course is not a transcript, but your own working project. By the end of the masterclass, you will have assembled a coding-agent harness that can be developed for your specific tasks: development automation, repository management, agent system research, or creating internal AI tools for the team.

• Working architecture of an AI coding agent.

• Code checkpoints for each module.

• Understanding of key engineering decisions in harness engineering.

• Experience comparing different approaches through examples of Claude Code, pi, and Hermes.

• Final demonstration of your own project.

Who the Course Is Suitable For

• Developers who want to create AI tools for coding and automating engineering tasks.

• ML and AI Engineers who need to understand how agent systems around LLM are built.

• Technical Leads evaluating the implementation of AI coding agents in development processes.

• AI Researchers and Enthusiasts looking to move from prompt experimentation to creating full-fledged agent systems.

What Is Included in the Training

• 5 days of intensive practice on harness engineering.

• Daily session recordings for material review.

• Code checkpoints for each module.

• Step-by-step assembly of your own AI coding agent harness.

• Live analysis of participant projects and feedback.

• Practical examples based on Claude Code, pi, and Hermes.

Prerequisites

To comfortably engage in the masterclass, programming experience and a basic understanding of command-line work, Git, and API are recommended. Deep expertise in LLM is not required: key concepts of the agent loop, context, memory, and tools are covered during the training.

Why Study Harness Engineering

AI coding agents are becoming an increasingly important part of modern development, but their effectiveness depends not only on the model. The harness—a technical system that defines agent work rules, manages tools, controls state, and helps turn LLM responses into real coding actions—plays a key role.

By mastering harness engineering, you will not only use ready-made AI tools but also design your own agent solutions for specific tasks, processes, and requirements of your team.