We built OpenClaw Ultron to replace 20 people at our company | E2246

The operational philosophy at venture firms and production studios is undergoing a radical shift. The objective is no longer just to hire more staff to handle increasing workloads; rather, the goal is to build "replicants"—AI agents capable of handling the repetitive, high-volume tasks that consume valuable employee hours. In a recent deep dive into internal operations at Launch, the team unveiled "OpenClaw Ultron," an ambitious project designed to automate the workload of 20 people. This initiative isn't about reducing headcount, but about elevating human talent to focus on high-leverage activities like founder relationships and creative strategy.

Alongside this software revolution is a hardware paradigm shift led by companies like Exo Labs, which are proving that running frontier AI models locally on consumer hardware is not only possible but preferable for data sovereignty. Below is an exploration of how custom AI agents, "cron jobs," and local compute clusters are redefining the modern workplace.

Key Takeaways

• The "Replicant" Strategy: The goal of OpenClaw Ultron is to consolidate 100 to 200 distinct skills into a single agent, effectively handling the chores of 20 employees to free them up for higher-level strategic work.
• Data Sovereignty vs. Renting Intelligence: Running AI locally prevents vendor lock-in and protects proprietary data (like venture capital secrets) from accruing to closed-source model providers.
• The Power of Cron Jobs: Moving beyond simple chat interfaces, the real power of AI lies in "cron jobs"—scheduled, autonomous tasks that handle accountability, optimization, and research without human prompting.
• Consumer Hardware Clustering: New software allows commodity hardware, such as Mac Studios, to be daisy-chained via Thunderbolt to run massive models, offering a cost-effective alternative to enterprise data centers.
• Vibe Coding the Interface: Building custom dashboards is now accessible to non-engineers through "vibe coding," allowing teams to visually manage AI memory, skills, and files.

The OpenClaw Experiment: Replacing Chores, Not People

The internal project, dubbed "OpenClaw Ultron," represents a significant pivot in how organizations view productivity. The premise is straightforward: identify every chore performed by the staff—from scheduling to guest research—and build a specific "skill" for an AI agent to handle it. The intended outcome is that a single instance of OpenClaw will eventually possess hundreds of skills, effectively performing the drudgery of 20 jobs.

Critically, the leadership at Launch emphasizes that this is not a replacement strategy but an elevation strategy. By removing the "chores," employees can focus on the primary functions of a venture firm: spending time with founders, courting Limited Partners (LPs), and producing high-quality content.

From Black Box to Dashboard

One of the immediate hurdles in deploying open-source AI agents is the lack of a user interface. Typically, users interact with these bots via command lines or chat windows, leaving the bot's "memory" and internal logic as a black box. To solve this, the team utilized "vibe coding"—feeding video demonstrations of desired interfaces into the AI to generate code—to build a comprehensive dashboard in under two weeks.

This dashboard visualizes the agent's brain, broken down into critical components:

• Memory & Files: Stores permanent preferences (e.g., "never use em-dashes in emails," "do not book competitors together").
• Skills: Executable workflows, such as researching a guest or scraping YouTube transcripts.
• Cron Jobs: Time-based autonomous tasks.

"The goal isn't to replace everybody. It's to take away everybody's chores and to make everybody better at the primary functions."

The Mechanics of Automation: Cron Jobs and Skills

The true differentiation between a standard chatbot and an "agent" is the implementation of cron jobs. These are tasks that run on a schedule, independent of human interaction. In the context of OpenClaw, these jobs act as both administrative assistants and managers.

Automated Accountability

One deployed skill is the "Attendance Bot." Previously, a human manager would spend 20 minutes daily reviewing Slack to ensure team members posted their start-of-day goals. Now, a cron job scans the general channel at a set time. If a team member hasn't posted their update, the bot automatically tags them and leadership, ensuring accountability without human friction or micromanagement.

Self-Optimization and Revenue Generation

Perhaps the most advanced application is the "Self-Optimization" job. Every morning between 3:00 AM and 5:00 AM, the agent reviews its own code, logs, and error rates. By 8:00 AM, it presents a report of potential fixes—such as identifying time zone bugs in calendar invites—and suggests code repairs. This creates a loop where the software is actively participating in its own maintenance.

On the revenue side, the agent scans competitor podcasts to identify sponsors. It references internal CRMs (like Pipedrive) to check if those sponsors are already in the sales pipeline. If a new lead is found, it alerts the sales team, effectively automating the top-of-funnel lead generation process.

Exo Labs and the Case for Local Compute

While software agents like OpenClaw manage workflows, the infrastructure powering them is equally critical. Alex Chim, founder of Exo Labs, argues that the future of AI is local. The reliance on centralized model providers (like OpenAI or Anthropic) creates two significant risks: lack of control (lock-in) and loss of data sovereignty.

The "Exocortex" and Ownership

As AI shifts from a tool we use to an extension of our minds—an "exocortex"—ownership of the underlying weights becomes a philosophical and practical imperative. If a firm trains a model on its proprietary investment memos and strategy, and that model resides on a closed server, the intelligence effectively accrues to the provider, not the firm.

"Not your weights, Not your brain. Do you really want a profit-seeking company running your brain?"

Clustering Consumer Hardware

Historically, running frontier-level models locally required expensive enterprise GPUs. However, advancements in hardware efficiency, particularly Apple Silicon (M-series chips), have changed the equation. Exo Labs has developed software that allows users to cluster multiple Mac Studios together using Thunderbolt connections.

By utilizing technologies similar to RDMA (Remote Direct Memory Access), these clusters share memory with extremely low latency. This allows a stack of consumer Macs to behave like a massive GPU, capable of running enormous models (like Llama 3 or DeepSeek) locally. For roughly $20,000 in hardware, a firm can run a frontier-class model with no token costs, total privacy, and zero risk of the model behavior changing overnight due to a vendor update.

Spotlight: Next Visit AI

The shift toward automated documentation is also transforming healthcare. Winning the recent Gamma pitch competition, Next Visit AI demonstrated how agentic workflows are solving clinician burnout. Specifically targeting psychiatrists, the platform listens to patient sessions and automates the charting process in real-time.

The metrics presented illustrate the massive leverage AI provides in service industries:

• Efficiency: Increasing patient capacity from 16 to 24 per day.
• Revenue: Driving a 30% increase in provider revenue.
• Retention: Near-zero churn due to the high stickiness of the product.

This reinforces the broader narrative: whether in venture capital or healthcare, the integration of AI agents is not about displacing professionals, but about removing the administrative burden that limits their capacity to deliver care and value.

Conclusion

We are currently witnessing the transition from "Software as a Service" to "Service as Software." The distinction is subtle but profound. It is no longer about buying a tool to help a human work faster; it is about deploying an agent to do the work entirely.

Whether it is through custom-built "replicants" like OpenClaw or localized compute clusters powered by Exo Labs, the barrier to entry for building sovereign, high-leverage AI infrastructure is collapsing. For founders and firms, the ability to automate "chores" is becoming the defining factor in operational efficiency and competitive advantage.