Inside Artemis' "AI vs AI" war | Shachar Hirshberg & Dan Shiebler (Co-founders, Artemis)

Artemis is a platform that uses AI to detect and stop security threats across a company's entire stack, including cloud, identity, and network information. Co-founders Shahar Hersburg and Dan Sheebler started Artemis seven months ago and have since grown the team to 30 people, built an AI-native product, and secured their first enterprise customers. They recently emerged from stealth, announcing their seed and Series A funding rounds. Shahar and Dan emphasize that their rapid growth and ability to iterate quickly are due to building the company with AI-native tooling and processes from the ground up. This approach allows them to move from concept to prototype and to customer feedback much faster than traditional methods, as there is no manual work involved in these stages. Shahar's 15 years in cybersecurity, particularly in security operations at AWS and Palo Alto, provided him with a deep understanding of customer needs and an intuitive sense of future requirements. This experience, while advantageous for product roadmap and customer trust, also presented the challenge of reimagining possibilities with AI rather than being constrained by past solutions. Dan's background as an ML engineer at Twitter and Abnormal Security, where he focused on behavioral understanding to detect cyberattacks, directly informs Artemis's approach to utilizing AI for high-precision threat detection that is resilient to changes in attacker behavior and minimizes manual customer effort. The founders dedicated significant time to ideation, focusing on customer problems and anticipating how AI would transform the security landscape. They engaged with hundreds of security professionals and participated in programs like First Round's PMF method to refine their approach. Their decision to focus on security operations stemmed from their combined deep expertise and a shared understanding of the growing problem in this sector. They identified a critical need for a differentiated solution, confident that with the right team and foundational standards, they could tackle it effectively. Shahar and Dan's co-founder relationship began through a mutual acquaintance in New York, where an initial 30-minute coffee turned into a four-and-a-half-hour discussion about the future of security. Their shared commitment and complementary skills were evident from the start. They decided to take the leap into entrepreneurship when they recognized a significant market pull and customer excitement for their solution. They felt the timing was crucial, as waiting longer might have meant missing the opportunity given the rapid pace of AI development. Hiring top talent is a major priority, with Shahar and Dan dedicating over 60% of their time to it. Their hiring process is designed to be extremely fast and efficient, often concluding with an offer within two days. They place heavy emphasis on references, finding them to be a strong predictor of a candidate's future performance. Work projects, particularly for interns, are used to assess building capabilities, focusing on the output rather than the code itself, to see if candidates can create something from scratch. Regarding AI fluency, the founders look for builders who are open-minded and eager to utilize the best tools, regardless of their prior AI experience. They actively cultivate an AI-native mindset within the team, where engineers are encouraged to use AI coding tools as their first line of approach for problem-solving. The technical architecture is designed to maximize the effectiveness of AI tools, making them more likely to produce correct answers in a complex codebase. The company ensures a positive candidate experience, including in-person meetings and lunch with the team to foster connection. Every team member is equipped with multiple cloud code instances, enabling them to work on several features simultaneously, a testament to their intensive and thoughtful use of AI. Beyond engineering, AI is used to automate various workflows and monitor business and operational metrics. This allows Artemis, despite its rapid growth, to remain streamlined and efficient without requiring extensive manual tracking. They use AI for product analytics, understanding customer struggles, and identifying opportunities to reduce friction and enhance features, which was previously a labor-intensive process. Artemis's ideal customer profile (ICP) consists of large enterprises, typically with over 1,500-2,000 employees, that are struggling with traditional Security Information and Event Management (SIEM) systems. These companies experience significant pain points, such as chasing thousands of alerts daily and lacking clear detection coverage. While they received interest from smaller companies, Artemis prioritized those with a clear, urgent problem that their AI-native solution could directly address. About 50% of their customer base comes from highly regulated industries like financial services, who have a high impact from security breaches but prefer to buy solutions rather than build in-house. The first few customers were secured simultaneously, with a key factor being the high level of trust and satisfaction that led these customers to proactively request to purchase the product. These "design partners" helped shape the product and became core to their security operations, prompting them to seek enterprise-level SLAs and reliability. Non-obvious early signals of product-market fit included an "inflection in utilization" where customers, after connecting initial data sources and seeing insights, immediately added more team members and data sources. This demonstrated that Artemis earned the trust needed for customers to invest political capital in deeper integrations. Initially, Shahar and Dan led sales efforts, learning the importance of "making the ask" while building trust and providing value. They maintain direct, often text-based, relationships with their customers, viewing this deep engagement as crucial for understanding needs and ensuring customer happiness. As they scale, they are building a repeatable go-to-market motion, distilling their founder intuition into sales scripts and clear benefit enumerations. They expect to maintain a high level of accessibility and ownership for all customers, believing that direct communication fosters trust and ensures continuous product improvement. Artemis decided to emerge from stealth relatively quickly, believing their differentiated product was ready to educate the market and help customers defend against accelerating AI-driven attacks. They had already seen organic customer outreach, a rare occurrence in cybersecurity, which reinforced their decision. Their advice for other founders is to ensure product readiness, be slightly uncomfortable but confident in the product's ability to deliver, and ideally have customer endorsements to build public trust in a noisy market. While they hired 30+ people in stealth by offering a fast interview process, communicating rapid growth, and connecting with candidates who resonated with their mission, they acknowledge that most small companies cannot do this. Artemis fosters an in-person culture in New York, which they believe has been a net positive for recruiting by attracting individuals who crave human interaction and collaboration. Their company values—customer obsession, ownership (including autonomy and intentionality), velocity, and high standards—are central to their culture. They regularly reinforce these values through shout-outs in weekly meetings. Shahar and Dan largely agree on core values and decision-making, attributing this to shared principles and mutual trust. When disagreements arise, the person who has thought most deeply about an issue typically guides the decision. They also prioritize two-way door decisions, allowing for quick action and iterative adjustments. The founders believe that AI is rapidly changing the market and risk landscape, with adversaries using AI to accelerate and sophisticate attacks. This necessitates an AI-native defense like Artemis, capable of detecting and stopping attacks within seconds, replacing traditional human-heavy workflows. They see AI-native solutions as fundamentally superior to AI-enabled legacy systems because they build the core control and reasoning layers with AI from the ground up, avoiding bottlenecks and enabling seamless interaction between AI components. Legacy systems, even with AI layers, are constrained by their foundational architecture and organizational structures. As first-time founders, Shahar and Dan were surprised by how natural the 0-20 employee phase felt, contrary to their initial expectations. They describe the experience as the most rewarding and fun of their careers, despite working long hours. They advise aspiring founders to pursue their dreams when they feel ready, regardless of career stage. Both are committed to continuous personal and professional growth as leaders, particularly in navigating the evolving landscape of AI-native company building. Shahar credits his brother's entrepreneurial success for inspiring him, while Dan attributes much of his foundational learning to the founders of Deemsto, his previous startup, who invested in his vision.