Sorry, Mom. You’re talking to an AI agent, not your son
Young Silicon Valley programmers are getting increasingly creative with artificial intelligence agents. And at the same time, they carry a constant worry that they’re still not dedicating enough time to this technology.
In March 2026, while most people were still trying to figure out what exactly an AI agent is, a group of young programmers in Silicon Valley was already delegating practically everything to these digital entities. From updating their parents about life in the United States to scanning LinkedIn for business opportunities, managing calendars, drafting social media posts, and even operating bank accounts.
No exaggeration. And the story is more revealing than it seems at first glance.
Will Laverty, an 18-year-old Australian software engineer who moved to San Francisco just over a month ago, put his parents in a group chat with an AI agent because he simply didn’t have the time — or the inclination — to respond to messages himself. Sky Yang, 22-year-old CEO of the startup Imagine AI, left a Chinese New Year party early to check whether his five active agents were running properly. And Tejas Bhakta, a 28-year-old startup founder who claims to manage two entire companies with AI agents, admitted without hesitation that he feels genuine anxiety when he doesn’t have any agents running in the background.
This is the portrait of a generation that hasn’t just embraced automation with artificial intelligence as a life philosophy, but also carries the weight of thinking they could still be doing more. The line between efficiency and obsession has never been thinner. 🤖
What are AI agents and why OpenClaw changed the game
Before diving into the stories, it’s worth a quick bit of context. AI agents are, at their core, pieces of technology that perform tasks autonomously. They can be simple things, like managing your email and organizing your schedule, or much more complex things, like running entire work projects, interacting with other people on your behalf, or making decisions based on data you wouldn’t even have time to analyze.
The speed at which these agents can be built today is a central part of the phenomenon. New AI tools do the heavy lifting of writing code line by line, which means creating a functional agent no longer takes weeks of development. In many cases, you just describe what you want and the AI itself builds the framework.
OpenClaw is the open-source platform that catalyzed this entire wave. Launched and popularized in early 2026, it allows anyone with some technical knowledge to create a network of AI agents that live and work directly on their computer. The concept is simple to understand but powerful in practice: you define a task, configure an agent, and it executes autonomously without you needing to supervise every step.
What sets OpenClaw apart from other tools on the market is its flexibility in integrating with external APIs, the ease of chaining multiple agents in sequence, and an interface designed for people who already have technical fluency but don’t want to spend hours configuring complex environments. It found a rare middle ground between accessibility and depth, offering a smart abstraction layer that doesn’t require understanding every detail of the language model underneath, but also doesn’t trap users in a closed box with no room for customization.
One of OpenClaw’s biggest draws is that engineers don’t need to type code on a desktop computer. Many users connect the platform to iMessage or other messaging apps, sending programming commands to their AI agents directly via text message. This freed developers from the computer screen in a way that radically changed how work gets done.
The excitement around OpenClaw grew even more with the creation of MoltBook, a social network built exclusively for AI bots to post and chat with each other. Companies like Cursor, Anthropic, and OpenAI also launched new tools during the same period to help developers build more agents, creating an ecosystem that feeds on itself at an impressive speed.
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Will Laverty: the 18-year-old engineer who put his parents in a group chat with AI
Will Laverty arrived in San Francisco from Australia about a month ago and quickly found himself immersed in the frantic pace of the local tech ecosystem. He had a backlog of unanswered messages from friends and family asking what he was up to in California. While it made him feel a little guilty, the solution he came up with was putting his parents in a group chat with his AI agent.
And the result surprised him.
According to Will, practically everything he would want to tell his family, the agent already knew. By tracking everything about his life — calendar, activities, commitments — the agent could relay the information without Will needing to stop and think or type a single word. For him, this isn’t emotional coldness. It’s a practical solution to a real problem. The family keeps getting updates, he stays focused on work, and the agent bridges the gap between both worlds.
The inspiration came partly from Molly Cantillon, 22, CEO of the startup Nox, where Will works. Molly was already operating with AI agents integrated into her routine: one that wakes her up with inspirational quotes, another that offers stock trading advice, and a third that manages her calendar. When Will joined the company, everyone in the tech world was talking about OpenClaw, and he decided to build his own agents.
Today, Will has about four or five agents — he’s lost the exact count — controlling parts of his life. They all report to a central agent, a kind of god-agent that manages updates and coordinates the others. The agents have access to his social media to inform him about trends and draft posts. They write code for him. And they have access to his banking information.
His space gray MacBook stays permanently open and connected to Wi-Fi so the agents can run 24 hours a day, 7 days a week.
His motivation is clear, and he doesn’t hide it: If I’m not doing this, how am I going to reach a level of success comparable to the people around me?
And what about the risks? Will admits they exist. His social media agent, for example, started randomly deleting posts at one point. But he believes any potential risk is worth the efficiency he gains. He said he simply couldn’t go back to life before AI agents.
In his words: the pressure of being in San Francisco, surrounded by extremely talented and ambitious people, drove him to explore every possible avenue of AI agents and automations, seeking to integrate everything into his personal life. And he concluded that AI is profoundly shaping who he is now.
Sky Yang: the 22-year-old CEO who treats agents as an operational extension
Sky Yang represents another usage profile — the CEO who treats his agents as a direct extension of his operational capacity. Having five agents running simultaneously isn’t technological showmanship. It’s what allows a 22-year-old to manage the volume of information and decisions that would normally require an entire team.
Sky became obsessed with building agents using Anthropic’s tools since he started using them a few weeks earlier. Because his company, Imagine AI, organizes many networking events — including a sunset yacht party on the San Francisco Bay — he built an agent to scan his LinkedIn for prospects and draft outreach messages.
Each agent has a specific function, with defined parameters and clear criteria. When he left the Chinese New Year party early to check on their status, the gesture said a lot about how this generation reorganizes its priorities in a way that might seem strange to anyone who grew up in a different work culture.
But this dedication has a literal cost. Keeping AI agents processing code constantly costs money, and errors can pile up. Sky increased his monthly subscription for the tools from 20 to 200 dollars to support the heavier usage. Will Laverty took a different approach: he simply decided not to check how much he was spending. 💸
The Coral team and the era of voice as interface
John Kim, Ashton Teng, and Quinn Leng launched their cloud computing startup, Coral, the previous month, based in Menlo Park, California. The company’s focus is serving exactly the people who want to use OpenClaw with more computing power and less friction.
Quinn Leng, 31, exemplifies an important behavioral shift that OpenClaw accelerated. No longer tethered to a computer screen, he finds himself compulsively sending text messages or voice notes to his AI agents for several hours a day. Whether at the gym or on a walk with his girlfriend, he simply tells his ideas to the agent.
For him, the experience is genuinely magical. And, being honest, he admits it gets a little addictive.
Quinn is among the engineers who shifted from typing commands to using voice-to-text apps. This transition is significant because it changes the nature of human-machine interaction. When you speak instead of type, the flow of thought is different. Ideas come faster, iterations happen with less friction, and the feeling of talking to someone — even if that someone is an AI agent — becomes more natural.
His co-founder Ashton Teng, 28, took this dynamic to another level. He started talking so much in the office that he got embarrassed about potentially bothering his colleagues. The solution he considered? Buying a special microphone — like the ones used by race car drivers — to whisper commands to his AI agent. Teng also worries that his attention span is getting shorter, since he jumps from one programming idea to the next with increasing frequency.
The comparison he made sums up the feeling perfectly: it’s like TikTok, but for work.
Automation as a mindset, not just a tool
What separates OpenClaw users from other professionals who also use automation tools is the mindset behind the choices. For this group, the question is no longer whether a task can be automated, but why it hasn’t been yet. This inversion of logic changes everything. Every manual process starts being seen as a temporary inefficiency waiting for a solution, not as something normal or acceptable.
Tejas Bhakta is perhaps the most honest example of this dynamic. By admitting he feels anxiety when he doesn’t have agents running, he exposes something many think but few say out loud. Automation has stopped being an optional resource and has become a functional dependency. His mental model for work has been completely rebuilt around the idea that machines should be doing things while he sleeps, while he’s in meetings, while he breathes. Removing that from the equation isn’t just inconvenient. It’s disorienting.
This mindset has implications that go far beyond individual productivity. When an entire generation of programmers starts operating this way, the job market around them changes too. Expectations for what a single person can deliver rise considerably. Projects become more ambitious because the cost of executing repetitive tasks drops dramatically. And companies hiring these professionals start realizing they need to rethink team structures, what productivity actually means, and which skills truly make a difference on a team where much of the operational work is already being done by agents. 🚀
Have Silicon Valley programmers always been like this?
It’s worth remembering that young programmers in the tech industry have built a reputation over the years for extreme behavior when they commit to something. Coding through the night, biohacking their own bodies with technology, diving headfirst into trends that come and go. The industry’s future leaders frequently throw themselves completely into movements that, occasionally, genuinely change the world.
There’s an important difference this time around, though. Mixed in with the ambition is a concern that they’re building something they don’t entirely control. And that, even so, they could still be doing more. This combination of excitement and restlessness is new. In previous waves of tech hype, confidence was usually the dominant feeling. Now, there’s a self-awareness about the limits of human control that permeates the conversations, even when the people involved are clearly thrilled with what they’ve built.
When these AI agent wranglers talk about what they’re doing, the anxiety of missing out on the next big thing is palpable. But it also comes with surprising admissions about how their interactions with the humans around them have changed. The technology isn’t just optimizing work. It’s reconfiguring relationships, communication habits, and the very notion of presence.
The human side of all this
It would be very easy to look at these stories and conclude that we’re facing a cold, disconnected generation obsessed with technology to the point of losing touch with what’s essential. But that reading would be lazy and reductive.
What the stories around OpenClaw reveal is a deeply human tension between the desire to be present everywhere at once and the physical reality that it’s impossible. AI agents emerge, in this context, not as substitutes for humanity, but as an attempt to stretch the limits of what one person can manage alone in a world that demands ever more simultaneous attention.
The question that remains — and that no platform can answer on its own — is about where to draw the line. When automation starts replacing connections that should be genuine, something gets lost in the process. An agent that answers messages for your family might solve a logistical problem, but it also creates a layer of distance that, over time, can change the nature of those relationships in ways that are hard to measure or reverse.
There’s no right answer here. And the people using OpenClaw probably know that better than anyone. What’s curious is that they keep using it anyway — which says a lot about the tradeoffs this generation is willing to make in the name of efficiency and competitiveness.
At the end of the day, OpenClaw works like a mirror. It shows what happens when you give highly technically capable people a tool powerful enough to externalize parts of their own lives. The result is fascinating, sometimes unsettling, and quite revealing about where artificial intelligence has already arrived — and where it can still go. If Silicon Valley programmers are the canary in the coal mine, the rest of the world will be facing these same questions very soon. ⚡
