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

OpenClaw is driving the Agent from being a “productivity tool” to becoming “sustained operational productivity.” Moving 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 entire day.” Relying on efficient interaction, long- and short-term memory, and high-permission execution capabilities, OpenClaw presents a highly human-like “AI secretary” form. From now on, AI and SaaS will no longer be a peer tool relationship, but AI will become the scheduling hub, with SaaS sinking into capability modules, potentially reshaping the relationship between AI and SaaS. Looking further into the future, the division of labor between humans and AI will also rebalance, much like how the Jenny spinning machine replaced manual labor during the Industrial Revolution. A mature Agent form is expected to replace repetitive mental work, driving systemic reconstruction of productivity and social relations on a larger scale.

Origin of the Report:

Compared to similar Agent products, what makes OpenClaw different? From “passive multi-step execution” to “proactive daily cycles,” OpenClaw is a paradigm-shifting Agent product that has been seriously underestimated. Transitioning from passive response to proactive intelligence, from linear execution to daily routines, OpenClaw achieves a logical leap from being a productivity tool to embodying productivity itself. Historically, agents modeled “solving one-time problems,” with logic levels aligned with productivity tools; now, by introducing heartbeat mechanisms and memory modules, OpenClaw models “a person’s entire day,” elevating its logic level to productivity itself. In the long run, agents are expected to achieve self-recursion and evolution, fostering emergent capabilities.

Core highlight: Highly human-like features are the key strength of OpenClaw, specifically manifested in efficient and convenient interaction methods, continuous memory of user preferences, and system-level operational permissions.

If we compare OpenClaw to a user’s AI personal secretary, it precisely possesses the key abilities of an excellent secretary: 1) Efficient and convenient interaction: connecting with instant messaging platforms like WhatsApp, Telegram, Slack, enabling lightweight, high-efficiency input and output; 2) Continuous memory of user preferences: leveraging long- and short-term memory modules to accurately grasp user habits, preferences, and requirements, allowing automatic execution based on habits without repeated commands; 3) System-level operational permissions: OpenClaw can obtain system permissions on a computer to autonomously perform tasks such as file read/write, browser invocation, schedule management, cross-application collaboration, and code assistance. Users can also deploy third-party skill components via platforms like ClawHub to help build a co-constructed Agent ecosystem. However, on the other hand, the high openness in remembering user habits and permissions also introduces privacy and controllability risks. Ensuring that agents operate autonomously in a secure and controlled manner will be a key challenge for future development.

Industry Impact: AI, SaaS, and Human-AI Relationship Rebuilding, Short-term Volatility in US Tech Stocks

SaaS is fundamentally a user interface designed for human workflows. As agents gradually take over human workflows and evolve from “tools” to “productivity itself,” AI will increasingly become the core “task scheduling layer,” responsible for understanding and decision-making. Meanwhile, at the “task execution layer,” enterprise SaaS will likely continue to serve as the carrier of business workflows, even if AI reorganizes workflows and functions via plugins or integrations, it still needs to connect with enterprise applications to complete complex tasks and close workflow loops. Simultaneously, the division of labor between humans and AI will rebalance, much like how Jenny spinning machines replaced manual labor during the Industrial Revolution. A mature Agent form is expected to systematically replace repetitive mental work, further reconstructing productivity and social relations. In the context of high valuations and tightening liquidity in the US tech sector, the shift in AI and SaaS positioning may further amplify volatility in the tech industry.

Risk Factors:

Risks of geopolitical tensions and escalating frictions, potential US tariffs and trade policies impacting tech exports, tightening US restrictions on AI and semiconductors to China, macroeconomic growth falling short of expectations, hallucination issues in large models hindering application deployment, slower-than-expected AI implementation, and underperformance of leading tech companies in upcoming quarters.

Investment Strategy:

Represented by OpenClaw, agents are transitioning from “productivity tools” to “productivity itself,” with operational paradigms shifting from one-time task calls to continuous cycles. Token consumption and call frequency are rising in tandem, leading to exponential increases in computational power demand. Driven by upgrades in agent capabilities and deeper usage, reasoning-side computational power consumption is expected to remain high long-term, making the compute industry chain a direct beneficiary; additionally, large model providers’ token usage and ARR are resonating with growth in agent scenarios; overseas large model and compute chain investment opportunities are recommended. For Chinese companies, besides benefiting from rising agent penetration, there is also an overlay of trends toward domestic substitution of compute and models. It is advised to focus on overseas compute chains, self-controlled solutions, and domestic AI large models.

Source: CITIC Securities Research

Risk Warning and Disclaimer

Market risks exist; investment should be cautious. This article does not constitute personal investment advice and does not consider individual users’ specific investment goals, financial situations, or needs. Users should evaluate whether any opinions, viewpoints, or conclusions herein are suitable for their particular circumstances. Investment based on this information is at their own risk.