Yep, we’re using OpenClaw to date now

The Era of the Automated DM

I have seen a lot of weird use cases for generative AI over the last year, but we finally hit the inevitable milestone: someone automated their love life. Ben Guez, a developer who clearly values efficiency over traditional romance, recently revealed he has been using a script powered by OpenClaw and Claude to filter and respond to direct messages on Instagram. The result? A digital funnel that has filled his inbox with potential partners from all over the world while he presumably does anything else.

As a builder, your first instinct might be to roll your eyes. It feels like another peak-silicon-valley headline. But if you look past the cringe factor of using a bot to flirt, there is a significant technical shift happening here. We are moving from chatbots that answer support tickets to autonomous agents that can navigate the nuance of social dynamics. That is a massive leap in how we think about agentic workflows.

The Tech Stack Behind the Screen

Guez didn't just build a basic auto-responder. He leveraged OpenClaw, which is an open-source framework designed to give AI models more agency over web interfaces. By combining this with Claude’s coding capabilities, he created a system that can scan incoming messages, evaluate the context of the conversation, and generate a reply that sounds human enough to keep the interaction moving forward.

This isn't your grandfather’s 'if-then' logic. In the past, automated messaging was easy to spot because it was rigid. If you didn't say exactly what the bot expected, it broke. Now, because of large language models (LLMs), these scripts can handle slang, typos, and emotional subtext. They act as a sophisticated filter, doing the heavy lifting of the 'small talk' phase of dating before a human ever has to step in.

Why This Matters for Builders

Forget the dating aspect for a second. Think about the implications for any high-volume social interaction. For founders, this is a look at the future of personal branding and business development. If an agent can successfully navigate the complexities of a romantic interest, it can certainly handle the complexities of a cold lead or a networking request.

• Contextual Awareness: The bot isn't just sending a template; it is analyzing the other person's profile and previous messages to maintain continuity.
• Scalability: A human can only manage a handful of deep conversations at once. An agent can manage hundreds without getting tired or losing track of details.
• Emotional Calibration: LLMs are surprisingly good at matching the tone of the person they are talking to.

For those of us building in the AI space, the takeaway is clear: the friction between 'digital' and 'human' is disappearing. We are entering an era where social capital can be manufactured through well-tuned scripts. It’s efficient, sure. It’s also a little bit haunting.

The Authenticity Problem

Here is where my skepticism kicks in. Every time we automate a human interaction, we devalue that interaction. If I find out the person I’m talking to is actually a script running on a server in Virginia, the connection dies instantly. Guez’s experiment works because the people on the other end don't know they are talking to a machine—at least not initially.

As builders, we have to ask ourselves where the line is. If we build tools that make it impossible to tell what is real, we risk breaking the underlying trust of the internet. We’ve already seen this with dead-internet theory—the idea that most web traffic is just bots talking to other bots. If we start automating our DMs, our dating, and our friendships, what is left for the humans to actually do?

The value of a human connection is often found in the effort it takes to maintain it. When you remove the effort, you might accidentally remove the value.

I’m not saying we shouldn't build these things. The technology is here, and someone is going to use it. But we should be honest about what we are building. Guez is building a funnel. He’s treating human relationships like a sales pipeline. From a founder's perspective, it’s a brilliant optimization. From a human perspective, it’s a warning sign.

The New Reality of Social Discovery

This experiment proves that the 'gatekeeper' phase of social interaction is officially automatable. Whether it's dating, hiring, or sales, agents are going to become the primary interface for our digital lives. You won't talk to a person; you'll talk to their agent. Their agent will talk to yours. If the agents agree that there is a match, only then will the humans be notified.

This creates a bizarre new arms race. If everyone starts using OpenClaw to handle their DMs, then we’ll eventually need defensive AI to sniff out who is a bot and who isn't. We are building a world where machines are performing sincerity for other machines.

The Technical Feat is Real

Despite my reservations about the soul of the project, I have to give credit to the technical execution. Using Claude to write the logic for OpenClaw shows just how low the barrier to entry has become. A year ago, this would have required a dedicated team of engineers. Today, it’s a weekend project for a motivated dev with a specific goal in mind.

It also highlights the power of open-source frameworks. By not relying on a closed ecosystem, developers like Guez can move faster and experiment in ways that big tech platforms would never officially allow. Instagram doesn't want you automating your DMs, but they can't really stop you if your bot is behaving like a human would.

The Long-Term Impact

We are going to see a flood of these 'social agents' in the coming months. It won't just be for dating. It will be for 'influencers' who want to engage with fans, for 'thought leaders' who want to maintain a presence on X, and for 'founders' who want to stay relevant in every Discord community.

The takeaway for builders is simple: the tooling for autonomous social agents is now mature. You can build these things today. The question isn't whether it’s possible—it’s whether you can build it in a way that doesn't make the world feel like a colder, more transactional place. Guez found a way to fill his DMs, but I wonder if he’ll find what he’s actually looking for. Efficiency is great for code; I’m not so sure it’s the right metric for a marriage.

Read the original at TechCrunch AI →