Automation

Governments are starting to treat laws like software, storing them in digital formats that track every change (like a 'Git repo' which is a version history for files). This means legal documents are becoming machine-readable, making it possible to automatically monitor and understand complex legal updates without needing a law degree.

“People are really interested in the idea of 'Spanish legislation as a Git repo,' showing a strong desire to track laws like software.”

Traditional web scraping is a nightmare because websites constantly change, forcing builders to rewrite code. While using AI (large language models) seems like an obvious fix, simply throwing raw website data at them often makes things more painful due to messy HTML. Builders desperately need a reliable way to get structured data without constant maintenance, and current tools aren't quite cutting it.

“We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs (large language models, a type of AI) seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: Raw HTML is full of navigation elements and other junk.”

People are absolutely done with endless scrolling through online catalogs and search results, leading to 'fatigue' when trying to buy or discover things. At the same time, AI agents (software that can perform tasks autonomously) are emerging, and the biggest signal is that 'files are the interface' for how humans and these agents will interact. This means there's a huge opportunity to build tools where you give an AI agent a simple 'file' (like a shopping list or criteria) and it acts on it, completely bypassing the frustrating search-and-scroll model.

“Files are the interface humans and agents interact with.”

Solo founders are drowning in repetitive daily tasks like market research and competitor checks. New tech that 'right-sizes' large AI models (making them run efficiently on your personal computer instead of expensive cloud servers) means you can now build powerful, private AI agents to automate this 'grunt work' directly on your own machine, saving time and money.

“There's a new tech that 'right-sizes' large language models (LLMs) to fit your computer's memory, processor, and graphics card, making powerful AI run efficiently on your own hardware.”

Forget building brand new AI products; the real opportunity is using AI to make existing, clunky enterprise software actually bearable. People are fed up with tedious workflows in tools like Jira, and AI agents (software that can interact with web interfaces just like a human, clicking buttons and typing) are now capable enough to automate these frustrating multi-step processes.

“One builder shared: 'I don't need AI to build me a new app. I need it to make Jira bearable.' They used a Claude Chrome extension to build a Jira sidebar showing dependency graphs, which Jira normally buries across multiple clicks and page loads.”

New YC companies from the Winter 2024 batch are starting to hire for key roles, signaling a shift from pure ideation to execution and deployment. While these early hiring posts often fly under the radar with low engagement, they represent valuable, un-hyped indicators of immediate operational needs for these growing startups.

“Trellis AI (YC W24) is hiring a deployment lead to help accelerate medication access.”