I want to tell you about a YC program called Early Decision. It's designed for graduating seniors who want to do a startup but also want to finish school first. Here's how it works.You apply to YC now while you're still in school. The application is the same as always. If you're accepted, we'll fund you right away and hold your spot in a future batch for after you graduate.That means you don't have to interview for jobs this fall to have a backup option. You can get guaranteed funding for next summer now. S ...

Crypto Industry Overview - The crypto industry has entered a golden age of building, with infrastructure and tools like stablecoins and chains in place, enabling entrepreneurs to create impactful businesses and consumer experiences [1][4] - Fintech is evolving from 1.0 (online payments) to 2.0 (friendlier consumer experiences) to 3.0, which aims to rewrite the financial system using crypto as a programmable software platform [1] - The industry is exploring different paths in layer 1 and layer 2 blockchains, converging learnings to build infrastructure for the next wave of adoption [2] Regulatory Environment - Regulatory uncertainty has hindered crypto innovation, with startups spending more on legal fees than engineering [3] - Increased regulatory clarity, such as with stablecoins and the Genius Act, is lowering the barrier to entry for entrepreneurs and fostering innovation [4] Stablecoins and Tokenization - Stablecoins enable programmable money to enter the existing financial system, providing access to dollars for individuals and businesses worldwide [4] - There are almost $200 billion of stablecoins in the market [4] - Tokenization involves moving asset classes from legacy systems to programmable environments, creating new opportunities for value creation [9] - New asset classes, such as content and creators, are emerging in the on-chain world, enabling creators to monetize their work [10][11][12] Building and Investment Opportunities - Opportunities exist in building interfaces for interacting with AMMs (Automated Market Makers) or exchanges, enabling seamless asset swaps [2] - US-centric builders can focus on rewriting legacy financial systems into programmable smart contracts, as demonstrated by the Shopify commerce payments protocol [6][7][8] - Founders should identify scaled network effects around intermediaries and use the open crypto platform to mediate transactions more efficiently [9] - Y Combinator is actively seeking to fund crypto startups with strong technical teams focused on solving real-world problems [35][36] AI and Crypto Intersection - Crypto can address AI's challenges by providing verification and authentication for AI-generated content [24] - Crypto serves as a native platform for AI agents to transact, enabling them to send and receive money through smart contracts [25][26]

Founders are often very afraid to have a willingness to pay conversation. They feel like if they bring a dollar amount up, it might scare the customer off. But honestly, that's almost always not true.It's so so important to have the conversation with a customer. If I can solve this problem for you and deliver these metrics we've talked about, how much would that be worth to you. You really need to disqualify customers who just aren't ready, able, or willing to buy your. ...

Startup Focus - Startups should prioritize achieving product-market fit above all else [1] - Every dollar and effort in a funded startup should be directed towards finding product-market fit [2] - The core team, consisting of founders, their computers, and potentially one engineer, is often sufficient in the early stages [2] Avoiding Big Company Traps - Startups should not emulate big companies by replicating their functions prematurely [1] - Investing in unnecessary resources like offices or excessive departments can be a distraction and detrimental to progress [3] - Focusing on appearing "grown up" like bigger companies can be counterproductive if it diverts attention from core objectives [3] Resource Allocation - Unlike big companies, startups should avoid spending on functions that are not essential for achieving product-market fit [1] - Prematurely hiring for roles that are not yet needed can create management overhead and hinder focus [3]

It's pretty clear now in the AI world that like the AI is very good at following instructions and it's probably going to be hard for humans to compete with the AI on just like following instructions reliably. In which case people here need to think about what are they going to get out of their college experience. That goes beyond just kind of showing up passing the test following the instructions really really well.like it's going to require how do you know to do things yourself and how do you have like age ...

Industry Trend - The industry believes that discouraging people from learning to code due to AI automation is poor career advice [1] - The industry suggests that advancements in software engineering tools should encourage more people to learn to code, not fewer [1] - The industry draws parallels to the past, noting that arguments against programming due to higher-level languages like COBOL proved incorrect, as these languages made coding easier and more accessible [2] Company Strategy - The company advocates for coding skills across all job roles [2] - The company emphasizes that employees in various roles, such as CFO, head of talent, and recruiters, benefit from coding skills, leading to improved job performance [3] - The company envisions a future where everyone is empowered to code [3]

Legora's Core Business & AI Integration - Legora is building an AI-powered workspace for lawyers, transforming how they review, draft, and research legal documents [3][4] - The company leverages generative AI to solve various legal use cases, such as summarizing court cases, reading stock option contracts, and building end-to-end systems for legal professionals [7][8] - Legora integrates directly into Microsoft Word, bringing generative AI into the existing work environment of legal professionals [16][23] - Key features include chat over documents, tabular review for large document sets, and playbooks for automated contract negotiation [16][20][42] Market Dynamics & Competitive Advantage - The legal tech industry has historically been fragmented with unsexy point solutions, but generative AI has disrupted this landscape [4][6][7] - Legora differentiates itself by offering a compliant system for law firms, addressing data processing requirements in Europe [9] - The company's velocity and ability to out-deliver larger competitors with a smaller team (100 people vs thousands) is a key advantage [57] - Law firms are increasingly open to adopting AI solutions due to client price pressure and the need to maintain competitiveness [32][34] Growth & Strategy - Legora raised $80 million in a Series B round led by iconic and general catalyst [15] - The company is expanding across Europe and into the US, with hubs in New York, London, and Stockholm [88] - A key strategy is to align incentives with law firms, positioning Legora as a long-term partner in their AI adoption [33][34] - Legora emphasizes hiring entrepreneurs and fostering a culture of ambition and problem-solving [91][97] Future of Legal Work - The role of lawyers is evolving towards reviewing work and managing AI agents, rather than solely performing tasks manually [100] - AI is enabling lawyers to perform tasks that were previously impossible, such as redlining files against playbooks and conducting deep research across large volumes of judgments [28] - The company aims to be the category leader in AI law, serving as a strategic partner to large firms in their transition to AI-driven workflows [110][112]

Now I think what we're seeing is with AI there's this promise of hey like this is more than software like this can do like the work of people it's like magic but like it's actually quite hard to do that reliably and so there's been this flip of where the technical expertise is now actually really like the missing piece and we consistently see at least from YC that college students are actually at the forefront of this stuff like actually understanding how to use the models and how to squeeze the performance ...

I look for intellectual fearlessness. I think it doesn't matter where you come from. It doesn't matter what problem we're trying to solve.That courage, that fearlessness of embracing something hard and go about it and be all in and trying to solve that in however way you you want is really a core characteristic of people who succeed. I learned this from them and I really look for young people who have that and then that as a CEO at World Labs in my hiring I look for that quality. ...

Anthropic's Early Days and Mission - Anthropic started with seven co-founders, facing initial uncertainty about product development and success, especially compared to OpenAI's $1 billion funding [1][46][50] - The company's core mission is to ensure AI alignment with humanity, focusing on responsible AI development and deployment [45][49] - A key aspect of Anthropic's culture is open communication and transparency, with "everything on Slack" and "all public channels" [44] Product Development and Strategy - Anthropic initially focused on building training infrastructure and securing compute resources [50] - The company launched a Slackbot version of Claude one nine months before ChatGPT, but hesitated to release it as a product due to uncertainties about its impact and lack of serving infrastructure [51][52] - Anthropic's Claude 35 Sonnet model gained significant traction, particularly for coding tasks, becoming a preferred choice for startups in YC batches [55] - Anthropic invested in making its models good at code, leading to emergent behavior and high market share in coding-related tasks [56] - Claude Code was developed as an internal tool to assist Anthropic's engineers, later becoming a successful product for agentic use cases [68][69] - Anthropic emphasizes building the best possible API platform for developers, encouraging external innovation on top of its models [70][77] Compute Infrastructure and Scaling - The AI industry is experiencing a massive infrastructure buildout, with spending on AGI compute increasing roughly 3x per year [83] - Power is identified as a major bottleneck for data center construction, especially in the US, highlighting the need for increased data center permitting and construction [85] - Anthropic utilizes GPUs, TPUs, and Tranium from multiple manufacturers to optimize performance and capacity [86][87] Advice for Aspiring AI Professionals - Taking more risks and working on projects that excite and impress oneself are crucial for success in the AI field [92] - Extrinsic credentials like degrees and working at established tech companies are becoming less relevant compared to intrinsic motivation and impactful work [92]