AI AGENT LARGE-SCALE TRAINING MATRIX: STRATEGIC LOGIC & REALITY BLIND SPOTS EVALUATION REPORT 一、5个核心观点（迎合/赞同视角） / I. Five Core Viewpoints (Supportive Perspective) 观点①：2026年2月是"经验边界"的分水岭 / Viewpoint 1: February 2026 is the Watershed of the “Experience Frontier”
Before this, human experience had boundaries—limited by individual reading, organizational databases, and regional information asymmetry. After this, AI Agents (such as Hermes) allow anyone to scrape knowledge that has appeared in any corner of the internet, shifting the experience boundary from “accessible” to “theoretically infinite.”
The information bottleneck shifts from physical mediums to retrieval capabilities. The better one utilizes agents, the larger their “experience radius.” AI Agent Strategic Evaluation Report / AI智能体战略评估报告 1 / 7
Making is the Critical Path to Breaking Wisdom Boundaries
“Ultra-high frequency and ultra-high density decision intensity”—instead of slow reading and deep deliberation, it relies on massive rapid decision-making + instant feedback (driven by Token consumption rankings) to achieve brute-force iteration, allowing college students to accumulate experience extremely fast in actual combat.
AI Agents compress the time from “knowing” to “doing.” Traditional experience accumulation is linear (act → review → improve), whereas AI-assisted execution can be parallel, high-frequency, and at scale, exchanging quantity for a quantum leap in quality.
Students × Mac mini = Large-Scale Agent Training Matrix
Onboard 2,000 fresh graduates within 90 days, each equipped with a Mac mini, ranking Token consumption every half hour to create a live 2,000-person arena. Everyone can see their position in the grand scheme, driving efficiency through competition.
This is not hiring 2,000 programmers to write code; it is hiring 2,000 AI Agent training operators. They do not need traditional development experience, but they must rely heavily on Hermes, be willing to use it at high frequency, and be self-driven under ranking pressure. The Mac mini is the “computing terminal,” and the human is the “decision terminal.” AI Agent Strategic Evaluation Report / AI智能体战略评估报告 2 / 7
Resource; The Company Has Established a First-Mover Advantage
The company has purchased over 500 Mac minis (batches: 100+150+200+300+40), and the accumulated inventory may exceed Apple’s expected production capacity. “Not many companies in the world are competing with us”—this is a window of opportunity for hardware positioning.
Competition in the AI Agent industry will ultimately extend to hardware terminals. Whoever can secure enough local computing terminals (Mac minis) first will possess the ground troops. This is a terminal war—people are easy to find, but machines are not. 观点⑤：人员规模可进一步放大至9000人 / Viewpoint 5: Personnel Scale Can Be Further Expanded to 9,000 People
“If I have 9,000 college students onboard, I can go get 40,000 to 50,000 Mac minis.” The core logic is people first, then machines. Human resources determine the upper limit of hardware investment in the next stage.
First capture the talent pool (fresh graduates have low costs and high plasticity), and then use the scale of talent to leverage larger-scale hardware procurement and bargaining power. AI Agent Strategic Evaluation Report / AI智能体战略评估报告 3 / 7 二、5个交叉批判观点 / II. Five Cross-Critical Points 批判①：「边界突破」≠「质量保证」 / Critique 1: “Frontier Breakthrough” ≠ “Quality Assurance”
While agreeing that information accessibility will surge after 2026, finding information does not equate to using it effectively. The internet contains massive amounts of noise, outdated info, contradictory views, and malicious misinformation. Under high-frequency decision pressure, a fresh graduate without sufficient critical thinking and domain judgment may amplify errors with the acquired experience. High-frequency decision-making accelerates the reinforcement of wrong signals rather than wisdom—making wrong decisions yields wrong results, and the ranking mechanism only incentivizes doing more of the same wrong things next time. 核心问题 / Core Question:
Who will act as the plumber for decision quality? 批判②：2000人竞技场存在"刷量"风险 / Critique 2: Risk of “Metric Gaming” in the 2,000- Person Arena
Ranking Token consumption every half hour will incentivize gaming behavior—using automated scripts to repeatedly call AI to generate meaningless content or execute the same command to boost Token metrics. This ultimately get 2,000 operators who know how to game the rankings, not 2,000 individuals breaking the boundaries of wisdom. 修正建议 / Proposed Correction:
Ranking metrics should be shifted from Token consumption to output quality (e.g., number of agents built, successful tasks completed, time spent resolving complex problems), or at least incorporate an “efficiency ratio” (output/Tokens) into the ranking. AI Agent Strategic Evaluation Report / AI智能体战略评估报告 4 / 7 批判③：90天2000人 × Mac mini 面临现实物流瓶颈 / Critique 3: Reality Logistics Bottlenecks for Mac mini Deployment
Apple’s Mac mini supply chain is indeed tight, but the key issue lies outside first-tier cities. The cities mentioned like Xining, Lanzhou, and Hohhot have far inferior Apple logistics coverage, corporate procurement support, and after-sales service compared to Beijing, Shanghai, Guangzhou, and Shenzhen. Deploying enterprise-level Mac mini orders at scale in remote cities could take a logistics response cycle of 4–8 weeks. Managing procurement → logistics → distribution → training → live ranking simultaneously within 90 days is an extremely complex multi- thread engineering problem, far harder than just “persuading decisions.” 核心问题 / Core Question:
It is not a matter of willpower in execution, but whether the scale logistics/supply chain bottlenecks have been broken down into executable SOPs. 批判④：应届生的AI成熟度可能被高估 / Critique 4: The AI Maturity of Fresh Graduates May Be Overestimated
The assumption of “the 2,000 smartest college students in China” needs to be questioned. The top 1% of fresh graduates are indeed outstanding, but finding 2,000 of them who are willing to join a virtual asset management/ legacy coin company yields an extremely low conversion rate in the talent funnel. More realistically, most graduates have never touched a terminal command line; Hermes will be a wall to them, not a sword. If the training period is too short (90 days), most people might not even pass the “Agent debugging” phase, let alone “break the boundaries of wisdom.” 核心问题 / Core Question:
Is it about finding “ready-made people” or “training people”? The former cannot yield 2,000 candidates, and 90 days is insufficient for the latter. AI Agent Strategic Evaluation Report / AI智能体战略评估报告 5 / 7 批判⑤：「先有人再有机器」的倒挂风险 / Critique 5: The Inversion Risk of “People Before Machines”
The logic of “9,000 people → 40,000–50,000 Mac minis” equals hiring people before buying equipment. However, the salary, social security, management costs, office/housing, and training systems for 9,000 graduates constitute a monthly multi-million-dollar labor expense. If 9,000 people are hired but only 5,000 Mac minis arrive, 4,000 people will have no computing power available, creating a Ponzi-like structure in human resources. The risk is that intensive synchronization between talent cost and hardware procurement is required, rather than “people waiting for machines” or “machines waiting for people.” 核心问题 / Core Question:
Which comes first? If hardware supply cannot keep up with human expansion, labor costs will rapidly consume any early-mover advantage. AI Agent Strategic Evaluation Report / AI智能体战略评估报告 6 / 7 三、总结：这套逻辑的亮点和盲区 / III. Summary: Highlights and Blind Spots
DIMENSION 亮点 / HIGHLIGHTS 盲区 / BLIND SPOTS
Philosophical
Sharp judgment on breaking experience frontiers by
Ignores information quality control and decision correction mechanisms
Operational
Creative idea of scale competition-driven workflow
Ranking metrics distort behavior; logistics & training are unrealistic
Resource
Correct first-mover strategy of locking Mac mini hardware
Logistics fulfillment in 3rd/4th tier cities remains unverified
Talent
Fresh graduates offer low costs and high plasticity
Weak baseline skills; a true 2,000-person elite pool is questionable
Financial
Aggressive growth mindset of “people first, machines later”
Extreme upfront risk exposure of massive labor costs AI Agent Strategic Evaluation Report / AI智能体战略评估报告 7 / 7