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Applications for the YC Winter 2027 batch are now open!
Apply by November 2: ycombinator.com/apply
Y Combinator retweeted
Awesome to host @CalBlockchain at @ycombinator last night.
Excited to see the stablecoin, tokenization, agentic finance startups this room is going to build in the next few years.
Y Combinator retweeted
Excited to officially launch @LarkAgents today!
Our first customer is already saving 50 hours a week with Lark, automating ERP data entry and deciding what to reorder.
Lark combines AI with inventory optimization algorithms to recommend what to order, when, and how much, helping teams reduce stockouts and excess inventory.
Teams can review recommendations and set limits on what Lark does automatically.
No one I’d rather be building with than my brother @michael_wxng.
Y Combinator retweeted
OpEra is live.
Custom AI decision engines for operations teams: production schedules, warehouse plans, delivery routes, re-planned when a machine breaks, a truck runs late or an order changes.
38% lower delivery cost for a major retailer in weeks. Build at MIT. YC F26.
Y Combinator retweeted
We're announcing the public beta of datavendor.ai
We spent the last two years building the best solution for people buying and selling data, whether you're a researcher in a lab or a company trying to sell data.
Data is the fundamental bottleneck for AI progress, and DataVendor will be the infra that solves it.
Congrats to @igmarinelli, Gabriel, and @Tractian (W21) on their $130M Series D at a $1.4B valuation!
Tractian builds sensors and AI that predict when industrial machines will fail, before they do.
Most industrial equipment has no instrumentation at all, so factories find out about problems when something breaks. Tractian retrofits machines with a dozen kinds of sensors measuring vibration, temperature, and pressure, and its AI recommends maintenance ahead of the breakdown. They’ve now passed $100 million in ARR, growing 90% year over year.
theinformation.com/briefings…
Y Combinator retweeted
Today we're launching the new standard for how to sell with AI, built with 10 of the most-followed voices in enterprise sales.
For 30 years, we've perfected how sellers run a deal.
We have MEDDPICC, Challenger, Command of the Message. Sales leaders spend months turning them into sales process docs with exit criteria, qualification rules, and forecasting guidance, then ship them to the field.
But nobody shows reps what to put in front of the buyer to win. Aside from a generic pitch deck, everything else is left to interpretation. No templates. No examples. No standard.
So the top 1% of reps build their own: tailored first-call deck, champion enablement doc, mutual action plan. Everyone else guesses.
AI has turned this gap into a crisis by giving every seller the power to create content for buyers without knowing what good looks like.
The end result: buyers are drowning in polished but ineffective content, and they're tuning out.
So we built the missing half. We teamed up with 10 of the sharpest minds in enterprise sales to map what the top 1% do at the ten moments that matter most, and how AI is changing each one.
Introducing the 𝗕𝘂𝘆𝗲𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗚𝘂𝗶𝗱𝗲:
@KnuthJen23597 on building the account POV behind $50M+ closed with C-level buyers
@kylecnorton on building the best outbound and cold call strategy we've ever seen
@aprildunford on the first-call pitch she's built for 200+ companies
@Chris_Orlob on the demo lessons from thousands of recorded calls
@NNasrall on the business case that lets your champion close the deal without you
@samfjacobs on how to connect with execs and pitch the Economic Buyer
Rippling's Ricky Peca on the deal room that helped him hit 300% of quota
@JamesKaikis on scoping pilots that align teams and convert
@NickCeg on the seven-figure pricing proposal a CFO will actually read
@RomeenSheth and @travisjgood on the AI security playbook that answers 90% of buyer questions
Every moment comes with their playbook, where reps go wrong, how to avoid AI slop, and ready-to-use templates.
Who it's for: reps selling AI products, sales leaders chasing a higher win rate, and the enablement and product marketing teams who equip them.
Grab all ten templates, with the expert breakdown behind each:
mutinyhq.com/selling-with-ai
P.S. Mutiny's sales assistant is trained on these templates and sales frameworks. Join the early preview for free on our homepage.
Y Combinator retweeted
Innovations like AlphaFold, Evo2, ESM, Hippocratic, and OpenEvidence have transformed the way drugs are developed and disease is diagnosed. AI is now used in some step to aid in the development of almost every drug coming to market. 81% of US physicians now integrate AI into clinical workflows. We are even seeing this scale to individual therapeutics, curing cancers that were never before possible, such as when GitLab founder Sid Sijbrandij recently generated 25 terabytes of single-cell sequence data to achieve measurable remission for recurrent osteosarcoma (a rare, aggressive type of malignant bone cancer).
For the next YC Paper Club, we invite the authors of these works to discuss the exciting future of AI for Biology.
Please join us in Mountain View on 11/4!
RSVP below:
events.ycombinator.com/yc-pa…
Y Combinator retweeted
3 years ago, our landing page (pre-pivot) got picked apart on yc’s design review show. this week, I was the guest.
@aaron_epstein had me on to talk through @magicpatterns, our history, and then review a couple of live landing pages.
full episode is live now:
Magic Patterns (W23) is one of the fastest-growing design tools in AI, helping product teams turn ideas into interactive, code-backed prototypes in minutes.
@alexdanilowicz and his co-founder, both front-end engineers, built @magicpatterns to solve a problem they had themselves: finding a better way to turn ideas into something visual. They were among the first teams building prompt-to-design tools back in 2023.
In this episode of Design Review, Alex joins YC’s @aaron_epstein to demo Magic Patterns and its new MagicOS canvas, where teams can bring together prompts, images, PRDs, and other context to explore ideas visually.
Then they review a handful of startup websites to break down what makes a site feel “vibe coded,” where founders go wrong, and how to make AI-generated design feel more intentional.
02:11 — From YC Pivot to Product-Market Fit
03:44 — Staying Ahead as AI Design Tools Improve
04:37 — Demo: Designing With Magic Patterns
09:52 — MagicOS
11:23 — Designing With Context on a Canvas
14:50 — How to Get Better Results From AI Design Tools
15:35 — How Far Can AI-Generated Design Go?
18:17 — Website Review 1: Ego
23:59 — Website Review 2: Sentient OS
32:01 — Website Review 3: Cerenovus
36:59 — Website Review 4: Slashy
43:33 — How to Develop Better Design Taste
44:20 — Why Everyone at Magic Patterns Talks to Users
45:07 — Balancing Speed and Design Quality
46:07 — The Future of Design and Magic Patterns
Magic Patterns (W23) is one of the fastest-growing design tools in AI, helping product teams turn ideas into interactive, code-backed prototypes in minutes.
@alexdanilowicz and his co-founder, both front-end engineers, built @magicpatterns to solve a problem they had themselves: finding a better way to turn ideas into something visual. They were among the first teams building prompt-to-design tools back in 2023.
In this episode of Design Review, Alex joins YC’s @aaron_epstein to demo Magic Patterns and its new MagicOS canvas, where teams can bring together prompts, images, PRDs, and other context to explore ideas visually.
Then they review a handful of startup websites to break down what makes a site feel “vibe coded,” where founders go wrong, and how to make AI-generated design feel more intentional.
02:11 — From YC Pivot to Product-Market Fit
03:44 — Staying Ahead as AI Design Tools Improve
04:37 — Demo: Designing With Magic Patterns
09:52 — MagicOS
11:23 — Designing With Context on a Canvas
14:50 — How to Get Better Results From AI Design Tools
15:35 — How Far Can AI-Generated Design Go?
18:17 — Website Review 1: Ego
23:59 — Website Review 2: Sentient OS
32:01 — Website Review 3: Cerenovus
36:59 — Website Review 4: Slashy
43:33 — How to Develop Better Design Taste
44:20 — Why Everyone at Magic Patterns Talks to Users
45:07 — Balancing Speed and Design Quality
46:07 — The Future of Design and Magic Patterns
Y Combinator retweeted
Today we're announcing @with_kiwi_ai: your GTM agent's data engineer.
Kiwi syncs your GTM stack into a data lake, shows the SQL behind every agent step, and turns every approval, edit, or decline into an eval. Backed by @ycombinator.
Learn more at withkiwi.ai
Y Combinator retweeted
Introducing @aucert_official (YC F26): AI agents that test your iOS and Android app on every build.
Functional QA, accessibility, Google Play and App Store policy. No test scripts to write.
Get your first scan on us. 👇
Y Combinator retweeted
We built a $150M ARR business twice.
The first time took 8 years. The second took 2.5.
Today, Podium crossed $150M in AI annual recurring revenue.
Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building.
And we decided to start over.
The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete.
As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it.
When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow.
But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers.
Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers.
We massively underestimated what we'd signed up for.
We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium.
Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated.
When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business.
We effectively started a second startup inside an already successful company. And we're still at the very beginning.
Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them.
And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades.
Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big.
In the age of AI, you can either disrupt your own company or wait for somebody else to do it.
I'd rather do it ourselves.
Y Combinator retweeted
I’m excited to share that Mach9 has closed a $34M Series A co-led by @firstround and @BessemerVP , with participation from @Prudence_VC and @QuietCapital .
During the first week of my freshman year at Carnegie Mellon, I walked into Red Whittaker’s office wanting to build field robots. Red handed me blueprints of a nuclear waste storage tunnel and told me to turn them into a CAD model, simulate it, and then build a robot to actually inspect it.
Our robots and software helped infrastructure owners and engineers understand what was there and plan what came next. The problems we worked on had real consequences for people and their communities.
That experience shaped why we’re building Mach9.
So many of the smartest people in the world are building software to serve better ads or AI to optimize a sales process, while entire industries that keep the world running still rely on tools from a generation ago.
Civil engineering is one of them. While civil engineering teams are using tools like LIDAR that make collecting data on their projects super fast, turning that raw data into usable CAD drawings and designs still takes months of manual drafting. And there are simply not enough people to do the work.
At Mach9, we’re building AI CAD software to expand the world’s capacity to build and maintain the infrastructure people depend on. Our software turns reality capture data into centimeter-accurate CAD drawings, helping surveyors and civil engineers deliver projects faster.
We’ve brought together an exceptional team from SpaceX, Tesla, Apple, and NASA to tackle hard technical problems in an industry where better tools can have a lasting impact. We’ve already helped nearly 100 organizations deliver over 2,500 projects spanning 100,000 miles of infrastructure in all 50 states. Behind those numbers are real problems we’re helping customers solve:
- On I-8 near San Diego, Caltrans is using Mach9 to turn scans into an accurate inventory of road safety assets, helping their team plan upgrades to make California’s roads safer.
- Fibersmith is using Mach9 to help design fiber networks that bring high-speed internet to more than 120,000 homes and businesses in some of Louisiana’s most underserved communities.
I’m so proud of what our team has built, and grateful to the customers and partners who have shaped Mach9 along the way.
Whether you’re looking for better tools for your next project or want to help us build them, we’d love to hear from you. Join us in bringing civil engineering into the AI era
Y Combinator retweeted
My agents sent me 355 hours of reading this week. I can't read that fast.
We're launching Spacesheep (YC F26) to fix that: agents' work lands in a space your team can actually understand and work on together.
Try it: tell any agent "share this to spacesheep.dev"
Y Combinator retweeted
Today we're launching Astor 2.0: your personal investing agent.
Horizontal agents are cool. But my take is that vertical agents are the next big thing. Your investments deserve an agent that's tailor-made, fully regulated and built to last.
Free to start on iPhone, both app and iMessage: astor.app
Y Combinator retweeted
Most agent demos stop working when you close the chat. Ours accumulates knowledge even when we sleep.
@venkatGoku used our OSS autoresearch harness to research a better C++ factory scheduler. It beat an expert-designed solver on 29/30 fresh problems and runs with no LLM.

























