From tools to productivity, OpenClaw leads the paradigm shift in Agents

OpenClaw is promoting the upgrade of Agents from "productivity tools" to "continuously operating productivity." From passive response to proactive intelligence, from linear execution to daily cycles, its focus is no longer on individual problems but on "a person's day." Relying on efficient interaction, long and short-term memory, and high-level execution capabilities, OpenClaw presents a highly anthropomorphized "AI secretary" form. From now on, AI and SaaS will no longer be on the same level as tools, but AI will become the scheduling hub, while SaaS will sink down to capability modules, and the relationship between AI and SaaS is expected to be reshaped. Looking further into the future, the division of labor between humans and AI will also undergo a rebalancing, just as the spinning jenny replaced manual labor during the Industrial Revolution, the mature Agent form is expected to replace repetitive cognitive labor, thereby promoting a systemic reconstruction of productivity and production relations on a larger scale.

Origin of the Report:

How is OpenClaw different from similar Agent products? From "passive multi-step execution" to "proactive daily cycles," OpenClaw is a severely underestimated paradigm-shifting Agent product. From passive response to proactive intelligence, from linear execution to daily cycles, OpenClaw has achieved a logical leap from productivity tools to productivity itself. In the past, Agents were modeled with the goal of "solving one-time problems," with logical levels corresponding to productivity tools; whereas OpenClaw, by introducing heartbeat mechanisms and memory mechanisms, models "a person's day," upgrading the logical level to productivity itself. In the long run, Agents are expected to achieve self-recursion and evolution, further giving rise to more emergent capabilities.

Core Highlights: The high degree of anthropomorphism is the core highlight of OpenClaw, specifically reflected in efficient and convenient interaction methods, continuous memory of user preferences, and system-level operational permissions.

If we compare OpenClaw to a user's exclusive AI secretary, it possesses the key capabilities of an excellent secretary: 1) Convenient and efficient interaction: By integrating with instant messaging platforms like WhatsApp, Telegram, and Slack, it achieves lightweight and high-efficiency input and output; 2) Continuous memory of user preferences: With long and short-term memory modules, it accurately grasps user preferences, habits, and requirements, automatically executing tasks according to user habits without the need to repeat instructions; 3) Possessing system-level operational permissions: OpenClaw can obtain system-level permissions for computer operations, autonomously completing diverse tasks such as file reading and writing, browser invocation, schedule management, cross-application collaboration, and code assistance. Users can also deploy third-party developed skill components through platforms like ClawHub, helping to build a co-constructed and mutually beneficial Agent ecosystem. However, on the other hand, the high openness of remembering user habits and permissions may also bring privacy and controllability risks. How to ensure that Agents can operate autonomously under safe and controlled conditions may become a key challenge for the future development of Agents

Industry Impact: The relationship between AI and SaaS, as well as between humans and AI, may undergo reconstruction, potentially amplifying volatility in the U.S. tech sector in the short term.

SaaS is essentially a user interaction interface designed for human workflows. As Agents gradually take over human workflows and transition from being "tools" to "the productivity itself," AI is progressively becoming the core "task scheduling layer," assuming understanding and decision-making functions. Meanwhile, at the "task execution layer," enterprise-level SaaS is likely to continue existing as the carrier of business workflows. Even if AI can reorganize workflows and achieve related functions through plugins, it still needs to connect with enterprise applications to jointly complete complex tasks and process loops. At the same time, the division of labor between humans and AI will also be rebalanced. Just as the spinning jenny replaced manual labor during the Industrial Revolution, mature Agent forms are expected to systematically replace repetitive cognitive labor, thereby promoting further reconstruction of productivity and production relations. Against the backdrop of high valuations in the U.S. tech sector and tightening marginal liquidity, the repositioning of AI and SaaS may further amplify volatility in the tech sector.

Risk Factors:

The risks of escalating geopolitical tensions and frictions, potential tariffs and trade policies in the U.S. leading to pressure on tech product exports, the tightening of U.S. restrictions on AI and semiconductors related to China, the risk of macroeconomic growth falling short of expectations, the risk that the large model hallucination problem cannot be completely resolved, hindering application deployment, the risk that the speed of AI application implementation does not meet expectations, and the risk that leading tech companies' quarterly performance may not meet expectations.

Investment Strategy:

Agents represented by OpenClaw are transitioning from "productivity tools" to "the productivity itself," with the operational paradigm shifting from one-time task calls to continuous cyclic execution. The intensity of token consumption and call frequency is rising in tandem, leading to a significant expansion in computational power demand. Driven by the upgrade of Agent capabilities and the deepening of usage, the computational power consumption on the reasoning side is expected to remain high in the long term, making the computational power industry chain a direct beneficiary direction; at the same time, the token usage and ARR of large model vendors are resonating with growth in Agent scenarios; investment opportunities in overseas large models and computational power chains driven by demand for computational power are recommended. For Chinese companies, in addition to benefiting from the increased penetration of Agents, there is also a trend of domestic substitution in computational power and models. It is recommended to focus on overseas computational power chains, self-controllable solutions, and domestic AI large model-related targets.

Risk Warning and Disclaimer

The market has risks, and investment should be cautious. This article does not constitute personal investment advice and does not take into account the specific investment goals, financial conditions, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. Investing based on this is at one's own risk