Every “new chat” is a silent compromise with machine amnesia.

Recently, the open-source project OpenClaw (formerly ClawdBot/MoltBot) has exploded in the AI world. Its rapid rise on GitHub stems not only from its novel technical architecture but also from its precise targeting of a widespread pain point in current AI products.

Poster @yan5xu’s analogy struck a powerful chord: “Every time we converse with an AI, it feels like using old Office software—constantly creating ‘new documents’ and restating the context from scratch.” This resonates deeply because it captures our collective experience: no matter the project we’re discussing with an AI, we have to start explaining from zero each time, as if the AI suffers from severe “goldfish memory,” retaining only 7 seconds of recall.

01 Why is the “New Chat” Model Failing?

The current AI interaction model is, at its core, a technical compromise. Due to limited model context windows and a lack of long-term memory support, developers are forced to slice interactions into isolated conversation fragments. Users become “memory porters”:

• Manually copying and pasting history between different chat windows
• Writing lengthy summaries as “previously on…” before each new conversation
• Managing a forest of browser tabs—dozens for different projects
• Enduring repetitive explanations of the same context, day after day

The result is fragmented AI intelligence. Each interaction feels like collaborating with an expert suffering from amnesia. Users aren’t enjoying technological advancement; they’re accommodating the machine’s “memory deficit.”

02 How Does OpenClaw Solve the “Goldfish Memory” Problem?

OpenClaw’s breakthrough lies in abandoning the traditional “conversation-reset” model. It designs the agent as a continuously running daemon process. By utilizing the filesystem for persistent storage, it enables the AI to:

• Remember user preferences and past decisions
• Maintain context continuity across sessions
• Proactively manage tasks and summarize progress

Developer Brad aptly noted: “Persistent memory is what separates a useful agent from a chatbot.” It knows yesterday’s context, remembers past decisions, and builds new work upon them.

While OpenClaw isn’t perfect—it still faces API limitations and has rudimentary memory management—it proves a crucial point: Providing a continuous, consistent user experience is feasible, and once users experience it, going back becomes difficult.

03 Three Major Barriers: From “Forgetful” to “Memorable”

However, transitioning from a “Session-based Model” to a “Continuous Agent” faces three significant challenges:

The High Wall of Privacy & Compliance
Persistent memory implies indefinite storage of user data, directly challenging regulations like GDPR. For enterprises, the resettable session model ironically acts as a legal "safe harbor."

The Puzzle of Cost & Performance
Continuously running agents need to stay active 24/7, posing immense challenges for computing resources and API costs. Unpredictable expenses deter enterprise adoption.

The Inertia of User Habits
Not everyone craves “being remembered.” Many prefer the psychological security of session-based models—knowing a conversation can be completely erased allows for freer exploration and experimentation.

04 Open Source Charge vs. Big Tech Dilemma: Who Leads the Future?

In this paradigm shift, open-source projects are leading the charge. OpenClaw and its various forks are proliferating on GitHub, exploring the possibilities of continuous interaction.

Meanwhile, big tech companies, accustomed to setting trends, appear relatively quiet. “Continuity” is too fundamental, too architectural, difficult to package as a flashy feature. It’s not as simple as adding a “persistent mode” toggle and declaring victory—this requires rewriting core interaction logic.

05 Final Thoughts: We Don’t Need Better Chatboxes, We Need Continuous Partners

Session-based models won’t disappear tomorrow. They still hold value in scenarios requiring privacy and simplicity. But the trend is clear:

The value of the next-generation AI will come not only from more parameters but from an uninterrupted trajectory of intelligence. When AI can remember you, understand you, and grow with you, it ceases to be just a tool and becomes a partner.

OpenClaw’s explosion in popularity isn’t an accident; it’s a collective vote by users for a better experience. We are witnessing an interaction revolution—from “conversation” to “collaboration,” from “tool” to "partner."

Try experiencing a continuous agent for a week: no repetitive explanations, no memory gaps, just natural, fluid collaboration. Then, return to the “new document” mode that requires constant re-introductions. The sense of disconnection will make it clear: the transformation has already begun.

This revolution isn’t just about how technology works; it’s about how we co-evolve with technology. When AI learns to “remember,” our relationship with machines will also evolve—from command and execution to understanding and synergy.