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Exclusive interview with Kevin Ding of Huasi Dynamics: When choosing an agent for the future, it’s important to see what it has learned in the past thirty days.

2026-08-13 08:00 Models 🔥 28.9 heat score
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On August 13, 2026, Jiazi Guangnian conducted an interview with Kevin Ding, CEO of Huosi Dynamics. Regarding the current challenges in choosing AI Agents, Kevin Ding proposed the following key point: To determine whether an AI Agent is worth adopting, one should not only consider its claimed capabilities or long-term plans, but also focus on the skills and behavioral performance it has actually learned and mastered within the past thirty days. This criterion aims to verify the true intelligence level and adaptability of the Agent through rapid iteration in the short term and practical feedback.

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GoogleKevin DingOpenAIPyromind DynamicsSalesforce

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Google × Kevin Ding1Google × OpenAI1Google × Pyromind Dynam…1Google × Salesforce1Kevin Ding × OpenAI1Kevin Ding × Pyromind D…1

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  • Salesforce1
  • OpenAI1
  • Pyromind Dynamics1
  • Kevin Ding1
  • Google1

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甲子光年 zh 2026-08-13 08:00

Interview with Kevin Ding of Huasi Dynamics: When choosing an agent for the future, it’s important to see what it has learned in the past thirty days.

Kevin Ding, founder of Pyromind Dynamics, believes that the key to Agent competition in the future lies in their ability to continuously learn from work results, rather than just relying on basic model capabilities. This view stems from his observation in GUI Agent experiments of the bottleneck where existing Agents “can work but cannot grow”. Currently, both Salesforce and OpenAI emphasize the importance of continuous improvement after launch, and Pyromind Dynamics has taken the lead in productizing Agent continuous learning. Kevin Ding points out that as basic models become more mature, production feedback data accumulates, and reinforcement learning infrastructure improves, market demand and technical conditions are aligned for the first time, prompting companies to shift from “one-time delivery” to a new model of “starting learning immediately after launch”.