Clio CEO on the Shift to 'AI-Native' SaaS
The CEO of Clio, a vertical SaaS company with $400M in ARR, argues the future isn't just bolting on AI features, but completely reimagining workflows to be 'AI-native'. He says the focus must shift from selling features to selling outcomes, like closing a legal case 50% faster, driven by agents working behind the scenes.
Clio's strategic shift is mirrored in the NYC startup scene, where enterprise AI is a major focus for investors. VCs like Lux Capital and Insight Partners are heavily backing AI companies that can demonstrate revenue and customer deployment, with AI startups raising 22% of the $42.3B in total NYC venture funding in 2025. This has created a hiring surge for ML and AI engineers at companies like Hebbia, which builds AI for financial document analysis, and EliseAI, which focuses on conversational AI for real estate. For engineers looking to build, the 'AI-native' approach involves leveraging frameworks designed for creating autonomous agents and complex workflows. Open-source tools like LangChain are widely used for chaining LLM calls, managing memory, and integrating with other data sources. Newer frameworks like CrewAI and Microsoft's AutoGen are gaining traction for orchestrating multiple AI agents that can collaborate on complex tasks, moving beyond simple chatbots to systems that can execute multi-step processes. The transition from a large enterprise to a startup, or building a side project, requires a significant shift in mindset and process. Engineers who have made the leap emphasize the increased speed of execution at startups but also note the absence of sophisticated in-house tools common in big tech. Successful indie hackers stress the importance of shipping fast with familiar tech stacks—one founder built an MVP in two days—and focusing on marketing as much as on the product itself. This focus on outcomes over features extends to vertical SaaS, where AI is enabling a new wave of disruption. Companies like Procore in construction and Toast in the restaurant industry are moving beyond basic management software to offer end-to-end platforms that automate core industry workflows. This "Vertical SaaS 2.0" trend uses AI to provide deep, industry-specific solutions, from managing compliance to optimizing complex supply chains. In the consumer and social space, user acquisition has also become AI-native. The most effective strategies in 2026 are powered by AI platforms that optimize for high-lifetime-value users, not just installs. This retention-first approach is crucial, as is leveraging social commerce integrations like TikTok Shop and Instagram Shops, which allow for instant, in-app checkouts, reducing friction and capturing impulse buys directly within the feed. For engineers balancing a full-time job with a side project, ruthless productivity is key. Proven tactics include creating strict time boundaries for both roles, setting small, achievable weekly targets for the side project, and understanding your personal "why" to maintain motivation. Even 15 minutes of consistent daily effort on a side project can create significant momentum over time. The NYC funding landscape for early-stage AI is robust but pragmatic. Seed rounds for AI startups in New York are typically in the $2-5M range, reflecting the high compute costs. Firms like Union Square Ventures and Lerer Hippeau are active at the early stages, but founders need to show more than a demo; investors want to see a clear path to customer revenue within a year of raising capital. Founders building AI in New York are often solving problems for the city's dominant industries. For example, Sarah Nagy, founder of Seek AI, is building tools for data engagement, while Nami Baral's company, Niural, is an AI-driven global payments platform. This proximity to large enterprise customers in finance, media, and healthcare gives NYC startups a distinct advantage in deploying and scaling their AI solutions.
