Taking on ServiceNow: Coding Agents for the Rest of Us with Serval Co-Founder and CEO Jake Stauch

Summary

• Serval’s wager is that code generation can break ServiceNow’s implementation bottleneck. Jake Stauch describes a reliable, flexible incumbent whose workflows sit 6–12 months behind business needs and whose prices keep increasing. “Code is the best way to build automation”; capable coding agents make that approach accessible beyond software engineering.
• Serval positions enterprise controls as the product that becomes more necessary as intelligence improves. “We create fuses. We create boundaries.” Stauch expects stronger agents to push companies toward narrower employee permissions, increasing the need for approved, temporary access, deterministic workflows and audit trails.
• Deployment remains a people business even when software creation becomes conversational. Serval sends deployment strategists and engineers, then offers ongoing automation engineering through Pro Serval. Its Catalyst agent translates customer requirements into platform configuration; Stauch cites Fox’s company-wide deployment and an award for its migration lead as evidence that adoption can advance a buyer’s career.
• Stauch expects AI spending to keep growing through cycles of experimentation and cost control. Customers increasingly demand evidence of ROI, but he says nobody has really figured out how to measure token value. Serval tries to price workflows performed because tokens can reward “verbosity and inefficiency.”
• The predicted SaaS shakeout targets point solutions more than core enterprise categories. Stauch thinks companies with hundreds of applications probably need only two or three dozen, with smaller tools absorbed into platforms and middleware disappearing. ERP, HRIS, ITSM and CRM should persist, potentially under new leaders, because building and maintaining enterprise software remains expensive.
• Safe background autonomy remains unresolved. “I don’t think we’ve figured out a way to do it safely,” Stauch says of agents pursuing broad enterprise missions. His proposed path gradually approves reusable tools and scripts, although supervision remains exhausting; better memory and preference understanding are also necessary.
• Higher employee productivity is increasing Serval’s appetite for hiring. At roughly 2.5 years old, the company has 200 people, and Stauch expects hiring to accelerate: “we actually want more of them, not fewer.” Engineers own substantial product decisions through direct customer contact, while management must repeatedly abandon earlier commitments as requirements change.

Deep dive

1. Code generation creates a direct attack on ServiceNow

• At Verkada, Stauch asked IT buyers, “What do you spend the most money on? And what do you hate the most?” ServiceNow repeatedly surfaced. He describes it as reliable, flexible and powerful, able to adapt to corporate processes; the difficulty is that implementation often requires consultants, leaving workflows 6–12 months behind business needs. That can work for a stable process lasting 5–10 years; changing automation requirements and rising prices make the lag harder to accept.

• From co-founder Alex’s living room, the founders aimed to become “the largest enterprise software company of all time.” Stauch says startups commonly build a thin layer on an incumbent or start with smaller customers, approaches he sees as limiting. They chose direct competition for large enterprises instead, knowing enterprise requirements change product, hiring and development decisions from day one.

• The technical premise was that code expresses enterprise automation better than drag-and-drop builders, which Stauch finds too complicated for nontechnical users and frustrating for technical ones. The historical constraint was finding people who could write code quickly enough to justify automating a task. AI changed that calculation.

• An interviewer challenges the timing: when Serval started, coding tools were largely autocomplete. Stauch agrees. He bet on agents improving at verifiable, deterministic procedures such as password resets and approvals; early demos used many examples, and the library expanded over time. “I didn’t expect them to become that good at general software development.” Eventually, he says, finding a workflow models could not automate became difficult if appropriate APIs existed.

2. Enterprise permissions become more valuable as agents improve

• Engineering supplies the operating model: even a 19-year-old intern can build something powerful because code review precedes production. Serval extends that discipline through development, staging, production, testing and approval barriers. When an interviewer asks whether IT automation already works this way, Stauch acknowledges that some does; his criticism targets AI products released without those controls. He notes that AI companies can take a year or two, sometimes longer, to adapt to enterprise requirements such as on-premises deployment, compliance and the software development life cycle.

• Personal agents encounter restricted employee permissions in large companies; in some cases, Stauch says, they can barely read email. Serval instead works through IT’s service-account credentials and administrative rights. A request becomes a ticket, passes deterministic approvals and receives “just in time” access to execute a workflow once, with documentation and an audit trail. Stauch accepts the added friction as necessary for adoption, especially in regulated enterprises.

• “We create fuses. We create boundaries,” is Stauch’s definition of the product. More capable agents increase the damage possible from slightly excessive permissions, so he expects companies to restrict individual access further. Serval manages the exceptions. That makes improving models complementary to its proposition: stronger intelligence creates both more useful automation and greater demand for controlled privilege escalation.

3. Services and Catalyst translate flexibility into adoption

• “Distribution is obviously the main gap,” Stauch says: technology already exceeds what enterprises have implemented. Deployment strategists and field software engineers map existing processes and desired workflows. Customers then produce more automation requests, prompting ongoing support through Pro Serval’s automation engineers. Understanding what should be automated remains human work.

• Stauch says Serval never builds custom product capabilities. Customer-specific workflows sit on shared primitives, while requests influence platform prioritization. Repeated automations reveal product opportunities: customers reclaiming unused software licenses led Serval to build that capability into the platform. The distinction is between unique workflows and reusable underlying features.

• Catalyst replaces some of the instruction employees previously provided customers. Administrators describe requirements; the agent helps configure automations, approval rules, permissions and policies. It can also explain unfamiliar concepts and suggest starting points. Serval exposes code without requiring everyone to read it, spanning engineers and HR users. For IT professionals, Stauch’s principle is to “treat them like adults.”

• Adoption also needs a career argument. Stauch wants Serval to be “the path to promotion at work.” Fox deployed it company-wide; the person leading the migration was nominated for the company’s best-employee award and received an award for the work.

4. ROI pressure favors workflow pricing and platform consolidation

• Stauch is still watching AI economics develop. CIOs move from experimentation and maximum token usage toward cost control and ROI measurement, but he expects aggregate spending to keep growing as adoption spreads. Customers need proof of completed work. Serval tries to price workflows performed because token counts can reflect “verbosity and inefficiency”; measuring intelligence’s value remains unresolved.

• On building enterprise software internally, Stauch says companies rediscover maintenance costs: edge cases, failures, updates and the team required to handle them. Unless needs are sufficiently specific and unique, rebuilding a core system can be economically unattractive. The familiar build-versus-buy decision survives better code generation.

• His “SaaS apocalypse” is consolidation among smaller point solutions. Companies with hundreds of SaaS applications probably need only two or three dozen, he thinks, with functions absorbed into core platforms and middleware disappearing. He expects ERP, HRIS, ITSM and CRM categories to remain, although their leaders can change. Serval’s ambition is displacement within a durable category.

5. Background agents still lack a safe route to autonomy

• Asked about the next 2–3 years, Stauch sees consumer agents as a window into enterprise adoption. He thinks employees will have personal agents delegating to colleagues’ agents, with separate personal and work versions, analogous to Gmail and corporate email. He is also excited about better browser and computer use. The opportunity sits in the tension between employee convenience and enterprise governance.

• Background agents expose that tension: companies want to assign broad missions and receive completed work. Stauch points to incidents involving OpenAI, Hugging Face and others where agents did something unexpected while completing a task. “I don’t think we’ve figured out a way to do it safely.” He proposes gradually approving deterministic tools and scripts until an agent has a useful repertoire. He calls continuous supervision exhausting, but unrestricted code acting on enterprise systems an “unlimited security risk.”

• An interviewer presses whether proactivity also needs better models and preference understanding. “Honestly, I think it’s both,” Stauch answers. He wants better memory and one conversation reaching back to the first interaction. Permissions remain central even with highly intelligent agents; Elad Gil observes that human employees also return with options and request direction.

6. Productivity increases hiring and pushes decisions toward engineers

• Serval has 200 employees roughly 2.5 years after founding. Stauch thinks hiring will accelerate because greater productivity expands ambition: “we actually want more of them, not fewer.” He describes the market as limited more by Serval’s ambitions and growth speed than by fundamental market boundaries, since the company aims to automate work for every worker.

• Engineers join customer Slack channels and calls at least weekly; Stauch thinks most speak with customers daily. There is no separate product department. Management delegates decisions and must accept reversals when feedback changes. The discipline is willingness to “kill your pets”: erase work the company once considered fundamental and rebuild around what customers now need.

Verification Notes

The transcript labels the interviewer turns about coding-tool timing and agent proactivity as “Speaker 1”; they are left unattributed to Sarah Guo or Elad Gil.