The W23 cohort represented the first wave of founders building in the immediate wake of the ChatGPT explosion, shifting from experimental prompts to durable AI infrastructure and deep vertical integrations. These startups targeted the chaos of model fragmentation and high-value, manual workflows in legacy industries like healthcare and corporate training. Their buyers were enterprises desperate to operationalize LLMs without the overhead of building custom middleware or managing dozens of disparate APIs.
Traction in this cohort was driven by the urgent demand for standardization in a fragmented model landscape and the automation of high-friction administrative tasks. Startups like LiteLLM capitalized on the enterprise shift toward multi-model strategies, while vertical players proved that AI could finally penetrate unstructured data silos—such as medical billing and video documentation—where traditional software had previously failed to provide a complete solution.
Many W23 startups struggled when they built thin wrappers that were quickly commoditized by rapid improvements in base model capabilities or native feature releases from OpenAI and Google. The primary failure was underestimating the velocity of model evolution, which rendered custom-built middleware or basic content generators redundant. Today's builders must focus on proprietary data loops and deep workflow integration rather than features that can be solved by a better system prompt.
The 2026 opportunity lies in agentic, self-healing workflows that move beyond generation to autonomous execution of complex business logic. A solo builder can now leverage multi-modal agents to replace the "human-in-the-loop" requirements that W23 founders still relied on for quality control. The wedge today is building outcome-oriented agents for niche regulated industries that require high precision and verifiable audit trails.
AI-powered revenue cycle management platform automating end-to-end processes from eligibility verification to collections with specialized AI agents.
Chrome extension that creates support, training, and marketing assets 10x faster from screen and audio recordings using AI.
Open-source LLM Gateway that standardizes access to 100+ large language models using the OpenAI API format.
Deterministic inference API for large language models ensuring consistent, reproducible outputs without random variance.