Ops leaders must embrace DoubleO’s agentic-by-default approach

While enterprises cautiously tiptoe into automation, Bay Area start-ups such as DoubleO are sprinting into an agentic-first model that’s not just client-facing—it’s at the core of how they run their businesses.

DoubleO is an example of a redefinition of operational scale—not through headcount but by how many agents can be deployed to perform work. And that’s not a metaphor: managing AI agents is now baked into their job descriptions.

DoubleO isn’t just building agentic tools—it is one

At its core, DoubleO is a horizontal no-code platform for building autonomous workflows—enabling users to string together AI agents that act across sales, marketing, BPO, and operations. It turns SOPs and internal knowledge bases into agentic systems, replacing human process execution with autonomous execution at scale.

A typical DoubleO agent might review a sales calendar, research every prospect, draft pre-call briefs using frameworks such as SPICED (Situation, Pain, Impact, Critical Event, Decision), update the CRM, and email the rep—all autonomously. This isn’t about productivity assistance; it’s about end-to-end ownership of workflows, with humans stepping in only to orchestrate.

Six people, hundreds of workflows, and a company that looks 10x its size

Internally, DoubleO walks the talk. With a six-person team, they’re pushing toward $1.5–$2.5M in revenue by year-end. Customers include major online gaming platform RunYourPool and nationwide tailor Hall Madden.

What makes this rapid revenue growth plausible is a foundational belief that agents can manage most operational tasks—with human staff serving as agent orchestrators.

That philosophy is evident in the company’s hiring: Future job descriptions at DoubleO will explicitly expect the ability to ‘manage a team of agents.’ The company’s go-to-market engineer, for example, won’t be building landing pages or writing campaigns—they’ll be directing agents that do all of that, ensuring the machine runs smoothly.

This is the Sam Altman one-person unicorn dream (almost) coming to life—built with actual software and customers.

Lessons enterprise leaders can’t ignore

This is where enterprise decision-makers need to sit up. DoubleO is not some theoretical proof of concept. It’s already operating, generating real revenue, onboarding customers up to and including mid-sized BPOs, and replacing internal human operations.

Meanwhile, most enterprises are still figuring out where GenAI fits into their ops stack. They are concerned with prompting skills, orchestration challenges, and integration overhead. DoubleO’s early and rapid success exposes a painful truth: Enterprises’ sloth-like response to new AI opportunities is a symptom of overengineered legacy complexity. If a six-person startup can operationalize agentic workflows across functions, you must work out how you can too.

Great managers must recognize their teams now comprise both humans and AI

The challenge goes beyond tech. It’s mindset, leadership, and process flexibility. You must design roles around AI orchestration now. Not as a side skill but as a core competency.

As HFS called out in March last year: “Great managers must recognize that their teams now comprise both humans and AI and that getting them all to work effectively together is where the magic will happen.” Read that initial report here: Rethink enterprise ops as AI-human collaboration.

Scaling up while scaling down

With $8M in funding from their prior company, Ignition, the DoubleO team has had years to refine the backend technology. Now, they’re scaling access to it. Self-service is weeks away, broader customer expansion is already underway, and a new funding round is planned for mid-2025. Demand is high. The bottleneck hasn’t been interest—it’s been how fast the team can onboard new users.

DoubleO’s model is simple: reduce the need for human hires by scaling agentic capacity. Every function—sales, customer success, marketing, onboarding—has workflows run by agents. Internal onboarding is handled by an agent that researches each user, maps their profile to use cases, and emails a tailored onboarding plan. There’s no hand-holding. There’s no room for headcount bloat.

This is Services-as-Software in action.

The Bottom Line: Stop thinking of agentic ops as the future. Start reimagining roles, processes, and KPIs—now.

DoubleO shows that agentic operations aren’t a future state—they’re already real, lean, and revenue-generating. Enterprise leaders must stop thinking about GenAI as a productivity tool and start thinking of it as a workforce. That requires reimagining roles, processes, and KPIs around orchestration.

If your next marketing hire isn’t expected to manage AI agents, you’re already behind.