Harj Taggar
Managing Partner at Y Combinator and a Lightcone Podcast host. Previously founded and led Triplebyte, co-founded Auctomatic, and became a YC partner in 2010 before returning in 2020.
Orbital Data Centers Bet on Falling Launch Costs
StarCloud co-founder and CEO Philip Johnston argues that falling launch costs could make orbital data centers a practical alternative to terrestrial facilities constrained by power, permitting and local opposition. The company’s first satellite demonstrated that an NVIDIA H100 can operate in orbit; its next systems are meant to sell processing capacity to satellite operators before pursuing larger deployments for hyperscale customers. Johnston’s case remains conditional on cheap, high-cadence launch capacity and on StarCloud solving heat rejection, radiation tolerance and connectivity at infrastructure scale.
Stripe Data Shows AI Is Improving Early Startup Outcomes
Patrick Collison argues that founders should scrutinize success as seriously as failure: before raising money, they should ask whether they want to spend the next decade or more running the company they hope to build. Drawing on Stripe’s nearly two-year path to public launch, he says the essential discipline is not launching quickly but reaching production users early and letting their needs shape the product. In the AI era, Collison sees more opportunity rather than a closing window, though he says founders may need to pursue less crowded starting positions while staying anchored to real customer demand.
Gusto Cofounder Automates Recurring Small-Business Work Through SMS and Slack
Gusto co-founder and head of technology Eddie Kim argues that AI for small businesses should automate recurring work, not present owners with another blank chat box. In a conversation with YC’s Harj Taggar, Kim explains how a missed-flight prototype evolved into Gusto Cofounder, an AI product that uses Gusto’s business context to run tasks such as payroll prep, approvals, reminders, and customer communications through SMS or Slack. He also uses the project to make a broader case for AI-assisted product development: smaller teams can build faster by testing working implementations instead of debating abstractions, but need more discipline as the cost of trying ideas falls.
YC Says Internal Agents Need Shared Context, Tools, and Trust
YC’s Pete Koomen argues that building “superintelligence” inside a company requires more than adding AI features to existing software: agents need access to the organization’s shared context, tools and accumulated work. In a Lightcone discussion with Garry Tan, Jared Friedman, Diana Hu and Harj Taggar, Koomen describes how YC’s internal agent system became useful once it could query a unified company database, reuse hundreds of internal tools and turn repeated judgment into improving skills. The broader claim is that AI-native organizations will depend as much on trust, transparency and broad access as on model capability.
Personal AI Lets One Builder Do the Work of Teams
Y Combinator CEO Garry Tan argues that personal AI is reaching a stage comparable to the early personal computer: powerful enough to let one person build software that once required a team, but still brittle enough to demand technical ownership. Drawing on his work with Claude Code, OpenClaw and his GStack workflow, Tan makes the case for heavy token use, Markdown-encoded “skills” and multiple coding agents under one accountable human operator. The larger question, he says, is whether users will control their own AI tools, data and prompts, or work inside opaque systems controlled by others.