Method builds autonomous cyber systems that help government and critical enterprise security teams map their environments, test defenses, and operate within defined rules of engagement.
In November 2025, a16z’s David Ulevitch described a need for autonomous cyber systems as adversaries adopt AI. His case for Method centered on helping critical institutions continuously test and strengthen their defenses.
The company combines offensive and defensive capabilities around a digital model of a customer’s systems. Operators can use that context to test weaknesses under defined rules of engagement. a16z and General Catalyst led the Seed and Series A financings disclosed together in November 2025.
Sam Jones, Sean Hacker, and Daniel Kelly founded Method. The company brings offensive and defensive capabilities into one platform for government and critical enterprise security teams.
Kelly LombardHead of Federal GTMJoined Method to bring its cyber capabilities to government and critical infrastructure teams. Previously worked at Anduril Industries and Gecko Robotics.LinkedIn ↗
Method describes a working model where individuals and teams own outcomes and choose how to execute. Its careers page connects that autonomy to high expectations.
The company says it pays medical, dental, and vision premiums in full for employees and their families.
Method’s careers page describes growth opportunities within a flat organization, with individual contributions central to how it builds a lean team.
Sean Hacker describes engineers and AI developing compiled tools with human review before they run against live systems. The design separates model reasoning from the actions software is allowed to take.
Method’s engineering approach emphasizes replaying what the system perceived and the rules in force. That gives engineers a concrete failure they can debug, fix, and cover with regression tests.
In Datadog’s case study, Method describes engineering and security teams using common observability tools. Engineers trace requests across services, queues, and databases in an architecture spanning Java, Python, Go, and Node.js.
Method uses real user monitoring to examine feature-flagged releases in development. The case study describes engineers working closely with customers and using instrumentation to understand behavior before changes reach production.