Agent Harness vs Work Harness: One Term, Two Systems, Two Owners
AI harness means two things: the agent harness you buy and the work harness you build. A layered map - and why the layer you build is where your leverage is.
How we bring AI into real engineering work: adoption patterns, the Harness Model, and lessons from hands-on delivery, from Hands-on Architects.
AI harness means two things: the agent harness you buy and the work harness you build. A layered map - and why the layer you build is where your leverage is.
Re-reading Team Topologies for the AI harness era: the harness relocates cognitive load, it does not remove it - and each team type feels it differently.
On AI platforms, architectural governance is the weakest dimension that decides what ships. Learn to treat context engineering as architectural practice.
How we built an E2E test harness for AI agents on a Spring Boot service: domain aggregates and SCNs cut commits per test step 5x at flat CI time.
A 10-dimension maturity matrix for AI engineering teams. Assess where you are, from chatbot-assisted to agentic flywheel, and build the harness that matters.
A practical guide to your first AI-assisted development experiment. Start small, build calibrated trust, and learn context engineering in under an hour.
Our Q1 2026 AI toolset for software architects - five categories from research to QA, prompt engineering as a discipline, and practical lessons from the field.
Understand key factors contributing to the success of an MCP server through architecture, design, and implementation analysis of Context7 - the most popular MCP server
A short overview of AI tools for architecture-aware prototyping and knowledge-driven design workflows that we currently use and explore as software architects.
In this article, we’ll share our experiences with leveraging AI to efficiently generate high-quality Architecture Decision Records. We'll discuss practical techniques, provide examples, and outline the benefits and challenges we've encountered.