Harness Engineering: Constraints, Feedback, and Deterministic Controls for AI Coding Agents
Harness engineering is the practice of designing layered constraints, feedback loops, and quality gates to make AI coding agents reliable by enforcing deterministic behaviors over probabilistic promp…Building an AI SDLC Harness with a Self-Evolving Pattern
An AI SDLC harness is a structured framework that orchestrates AI agents through the software development life cycle (SDLC), incorporating self-evolving mechanisms to iteratively improve performance …Frontend Harness for Development: Empowering Scalable and Efficient Frontend Workflows
There is a quiet, expensive assumption in most "agent + LLM" coding stacks: that the model is the thing producing structure. We treat the LLM as a draftsman, then bolt on linters, schemas, …Web Development Without Builds: Leveraging Web Components and AI for Superior Performance
Web development without traditional build tools relies on Web Components —native browser standards for reusable, encapsulated UI elements—combined with AI to generate efficient, vanilla HTML, CSS, and…Minimum Viable Harness Design: Principles and Best Practices
Minimum Viable Harness (MVH) design applies lean product principles to wiring harnesses , creating the simplest functional version that meets core electrical, mechanical, and environmental requirement…The AI Bubble: Speculation, Risks, and Economic Implications
The AI bubble refers to a theorized stock market bubble fueled by rapid investment in artificial intelligence (AI) technologies, drawing parallels to the dot-com era while raising concerns about over…
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