Currently, AI Agents are evolving from mere "efficiency tools" into "value-creating entities," sparking a nationwide frenzy of "shrimp farming" (developing AI Agents). However, beneath the noise, there are undercurrents. The persistently high costs of API calls, the ecological barriers that are hard to break between major top models, and the neglect of "data feeding" and strategy tuning for AI Agents due to blind following trends have led to many users' expectations being significantly reduced in practice.

In the face of widespread "AI anxiety" across the internet, this issue of Space will clear the fog and re-examine the commercial monetization logic of AI Agents, discussing how the public can build a solid moat with "core strengths." Additionally, this article will also interpret the underlying AI infrastructure AINFT, which aims to lower the barriers for users, from an industry ecology perspective, analyzing how market participants can truly move towards the path of AI value creation after crossing the narrative bubble.

Confronting AI Anxiety: Solidifying Personal "Core Strength" to Build a True Moat in the AI Agent Era

In the rapidly changing tide of AI technology, a phenomenon called "fear of missing out" is spreading across the internet. Ordinary people, fearing being left behind by the times, are flocking into the "shrimp farming" (developing AI Agents) arena, trying to seize new opportunities. However, under the fervor, is it really possible for ordinary users to earn money through AI, or is this just another narrative bubble? The guests engaged in an in-depth discussion on this controversy.

The Bull Demon King pointed out the core contradiction in the current "shrimp farming" frenzy, noting that while Agents can work 24/7, most of the so-called "shrimp farming" users are actually paying for expensive API call fees or paid courses, thus being in a state of "paying to work." Moreover, the time cost of repeated debugging and the uncertainty caused by platform rule changes likely results in a negative ROI (return on investment) for ordinary users.

Crypto.0824 illustrated, for example, that someone spent 99 yuan purchasing a month of an automated video AI Agent, but without effective distribution and customer acquisition strategies, the generated content often falls flat on viewership. In this transaction, all the user bought was an illusory "sense of participation." He emphasized that while AI Agents are indeed the trend of the times, blindly following without understanding the specific business logic often just means passively paying tuition for this craze.

So, is it impossible to make money with AI Agents? The guests believe opportunities still exist, but they are only available to those who are prepared. Whether one can make money with AI Agents depends on how users position AI Agents—as either an investment chip to speculate on fads, or as a real tool capable of optimizing their own business and solving pain points. Only the latter has the potential to reach profitability thresholds.

In summary, AI Agents are mere amplifiers of efficiency, not machines that create wealth out of thin air. Those who can truly earn money through AI are those who hold "core assets" in their hands, such as exclusive data, mature trading strategies, robust content distribution channels, or clear business logic. Without these true capabilities as a foundation, attempting to profit from generic tools with no barriers will inevitably lead to becoming a source of profit for others. The best way to break free from AI anxiety is to first clarify one's core advantages and then let the AI Agent become your digital employee.

During this process, the entire industry also needs to rethink the role of "shovel sellers." In a well-developed industrial ecosystem, "shovel sellers should be true enablers of users, the "road builders" and "infrastructure providers." When users possess unique strategies and intentions, and truly high-quality infrastructure can significantly reduce trial-and-error costs and streamline the underlying execution links, this is not only critical to breaking the narrative bubble but also the essential path to leading everyone out of anxiety and towards AI value creation.

Crossing the Narrative Bubble: Building the Underlying Financial Infrastructure for AI Agents

With a product logic that addresses industry pain points, AINFT, an important part of the TRON ecosystem, has welcomed strong growth momentum, currently surpassing 600,000 users on the platform. In response to the previously mentioned high API costs and the friction of repeated debugging, AINFT has proposed an infrastructure solution aimed at a wide user base, achieving "one-stop service for multiple models" and effectively resolving the financial pressure and friction costs in the large model calling process through a "no subscription, pay-as-you-use" model and 1 million free points, providing extremely flexible underlying support for the rapid iteration and implementation of agents.

Specifically, AINFT provides the following core support to address industry pain points:

• Unified API Key for Calling Global Top Computing Power: AINFT fully supports the most cutting-edge large language models currently on the market, including OpenAI's GPT-5 series, Anthropic's Claude 4.5/4.6 family, and Google's Gemini 3 series. Recently, it added several top models such as MiniMax-M2.5, Kimi-K2.5, GLM-5. Users only need to obtain a unified API Key to seamlessly switch and call these top models without needing to cross platforms. This not only eliminates the high costs of maintaining multiple accounts but also significantly shortens the development process and application launch cycle for cross-model calls.
• Web3 Native Payments and Transparent Usage-Based Billing: The platform completely breaks the barriers of traditional monthly subscriptions. Developers worldwide can log in and recharge assets using mainstream Web3 wallets such as MetaMask, TronLink, Binance Wallet, OKX Wallet, etc. Currently, the platform supports multiple mainstream crypto assets for recharge, including USDT, USDC, TRX, BNB. If developers choose to use NFT for recharge, they can receive an additional 20% point bonus. At the same time, the platform strictly implements a "pay-as-you-use, usage-based billing" mechanism, deducting fees accurately based only on the actual Tokens consumed, effectively avoiding resource idle and financial waste, ensuring that every penny invested is tied to actual output.
• One Million Free Points Breakthrough for Trial-and-Error Barriers: To alleviate the financial burden faced by ordinary users in the early stages of "shrimp farming," the platform grants new users 1 million free points. This measure essentially provides the market with an ample trial-and-error environment, significantly lowering the initial entry barrier.

In summary, AINFT serves as the underlying infrastructure for AI Agent builders, following the logic of objectively lowering technical barriers and amplifying the value of core strategies. The tool itself does not promise to create wealth out of thin air, but as long as users have clear commercial intentions, this system can help them polish ordinary AI tools into proprietary digital employees with real business value at very low trial-and-error costs and efficient large model scheduling capabilities.