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Agents Have Entered the Harness-Driven Era

The article discusses the significance of the leaked Claude Code from Anthropic, highlighting its revelation of advanced Agent engineering practices centered on "Harness" design. Rather than relying solely on model capabilities, modern AI systems now depend on a structured engineering framework—the Harness—to maximize performance. This framework includes six core components: multi-layered System Prompts, Tool Schema, Tool Call Loop (with Plan and Execute modes), Context Manager, Sub-Agent coordination, and Verification Hooks. The Harness enables tighter integration between training and inference, supports long-chain tool execution, and improves reliability through objective verification. It also drives six key training directions: behavior alignment via System Prompt, end-to-end tool-use training, integrated plan-execute training, memory compression, sub-agent orchestration, and multi-objective reinforcement learning. The shift to Harness-driven development reduces the emphasis on pure prompt engineering, favoring instead multidisciplinary talent with skills in AI, backend engineering, and infrastructure. The market is evolving toward more secure, private, and vertically integrated Agent deployments, with "model shell" companies needing either strong infrastructure or deep domain expertise to compete. Claude Code’s leak underscores that future AI advancements will be shaped by engineering architecture as much as by algorithmic innovation.

marsbit04/15 10:11

Agents Have Entered the Harness-Driven Era

marsbit04/15 10:11

Behind the $TAO Crash: The Bittensor Internal Strife and the 'Impossible Trinity' of DeAI

The decentralized AI (DeAI) sector is facing a major crisis following a public conflict within Bittensor ($TAO), a leading DeAI project. Covenant AI, one of its top development teams, which recently successfully trained a 72-billion-parameter large language model, announced its exit from the Bittensor network. The team accused founder Jacob Steeves of having "absolute and dictatorial" control over the network, alleging he arbitrarily cut off token rewards to their subnet without transparent governance. This triggered a panic sell-off, causing $TAO’s price to drop 15-25% in a single day and wiping out hundreds of millions in market value. The incident has raised serious questions about the viability of decentralized AI, highlighting a fundamental tension—referred to as DeAI’s "impossible trilemma"—between model quality and scale, credible neutrality of decentralization, and Sybil-resistant incentive alignment. Covenant’s departure exposed the centralized reality beneath Bittensor’s decentralized facade: although the network relies on a Yuma consensus mechanism for reward distribution, key validator nodes are controlled by early investors and the founder, allowing unilateral intervention. The event underscores systemic governance risks that may deter high-quality developers and institutional participants, threatening the entire DeAI narrative centered around trustless, incentive-driven AI development.

marsbit04/15 08:59

Behind the $TAO Crash: The Bittensor Internal Strife and the 'Impossible Trinity' of DeAI

marsbit04/15 08:59

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