@oran_ge: Every team in the future will be doing harness engineering, and everyone needs to understand this framework. Although there are some non-consensus points, this is a good review.
Summary
An opinion piece suggesting that AI teams will increasingly focus on 'harness engineering' and advocating for a review article on the framework.
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@astaxie: Today the group discussed how to learn Harness. For Harness Engineering, I'm studying these two resources: 1. https://github.com/walkinglabs/learn-harness-engineering… to understand the core mechanisms of each Harness…
A project-based course repository on Harness Engineering for AI coding agents, covering environment setup, state management, verification, and control mechanisms to make AI coding agents work reliably. The course synthesizes best practices from OpenAI and Anthropic on building effective harnesses for long-running agents.
@Kangwook_Lee: https://x.com/Kangwook_Lee/status/2052925157606568217
The author argues that human-designed structural frameworks for AI agents should be replaced by AI-engineered ones, introducing a Three Regimes Framework to show how this shift unlocks mid-sized model capabilities. Citing projects like Meta Harness, they predict an imminent transition where AI will autonomously optimize its own system architecture.
@hongming731: Alibaba's article on organizational R&D in the AI Native era is well worth reading. It addresses a critical foundational issue: for the past two millennia, organizational structures have been built around human limitations. Humans forget, get tired, misunderstand, and have emotions. The number of people one can stably collaborate with and manage is limited, and information inevitably degrades as it passes between hierarchies...
Alibaba released insights on organizational R&D in the AI Native era, pointing out that traditional organizational structures need to shift from accommodating human limitations to adapting to the efficient execution of AI Agents. The article emphasizes that the core bottleneck of AI transformation lies in outdated information formats; implicit experience must be transformed into AI-understandable infrastructure, while preserving the human role in innovation and cultural building.
@djfarrelly: https://x.com/djfarrelly/status/2052779234234380479
The article argues that AI agent development should rely on stable execution primitives rather than rigid frameworks, which frequently change with emerging orchestration patterns. It emphasizes durable steps, persistent state, parallel coordination, event-driven flow, and observability to prevent costly rewrites as best practices evolve.
@JayaGup10: https://x.com/JayaGup10/status/2052870394093408558
As AI capabilities and interfaces converge, this essay argues that durable competitive advantages will increasingly stem from unique organizational structures and talent ecosystems rather than fleeting technical edges. Drawing on examples like OpenAI and Palantir, it highlights how institutional design ultimately shapes which innovators can thrive.