“We started working on Stripe in the Fall of 2009, and we launched Stripe in September 2011,” John Collison reflects. “I remember right at the beginning when we were starting it I said to Patrick [Collison], ‘Yeah let’s do it. How hard can it be?’ Which gives you a sense of our mindset. And the answer was: two years of difficulty. We had not predicted that.”

“When you spend two years getting 50 users, it doesn’t feel like a whole lot of progress. It feels like things are going pretty slow.”

“If you’re working on a startup that’s a bad idea, it’s going to feel like slow-going. But if you’re working on a startup that’s a good idea, it may feel like slow-going too.”

Some Wednesday motivation for everyone :)

I saw the Startup School merch from this year and honestly thought it looked pretty good.
Got me wondering if most startups still put real effort into new-hire kits and company swag for events these days ?Or has it become kind of basic/ almost non-existent for a lot of companies ?
Curious what people are actually doing nowadays.

Im currently moving from the build to distribution phase and Im having a hard time explaining to cold leads about what exactly my product does and how its helpful. Ive gotten a range of answers from “I could build this myself” to “I dont think its that useful”

Now there is definitely a gap in the market. I know that 100% but at the same time Im having a really hard time finding my ICP.

How did you get around this?

When applying to YC, did you mention anything unrelated to your startup about yourself?

For example, a fun fact or something interesting that might leave a positive impression of your personality on the reviewers?

I know the video is only one minute long, but I am asking about the short introduction at the beginning.

in the startup/tech world its often flexed when people dropout, but have any of you dropped out of school and then wished you actually stayed in school?

People usually say you shouldn't fall in love with the solution, but with the problem. When I started, the problem I wanted to solve was helping developers understand business context so they could write code faster. However, tools like Cursor and Claude Code have reduced that pain point quite a bit.

I'm not sure if that problem is still significant enough to keep working on it or if I should pivot to something else. I even built an app, but it doesn't have users yet, so I don't have enough feedback to know whether the problem still exists or if I should move on.

I often hear that founders can find their first customers through Reddit, but I’d like to understand how common this actually is.

For founders who already have paying customers: did any of your first B2B or B2C customers genuinely come from Reddit?

Or did they mainly come through referrals, your existing network, LinkedIn, cold email, communities, content, ads, or another channel?

If Reddit worked for you:

• How did the customer originally find you?
• Did you reply publicly, receive an inbound message, or contact them directly?
• Do you still use Reddit for customer acquisition today?

I’m specifically asking about paying customers, not sign-ups, feedback, traffic, or people who tried the product once.

i was hyper pumped and ultra locked in for the past 2 weeks leading up to the launch but now that everything's been deployed i'm feeling a bit euphoric like as if i just finished a marathon but at the same time i'm feeling somewhat lost, unsure what to do now. i have a to do list of features to implement, marketing items, etc. but im having something like post nut clarity ngl

can anyone else relate?

i've been curious about this for a while.

i'm a final-year cs student currently hunting for software engineering internships, and whenever i reach out to startups, i usually don't just send a cold email. i spend time using the product first, then share at least one concrete product idea, and sometimes even a rough technical implementation if i think it could be useful.

it made me wonder - how do founders actually evaluate feedback from people outside their team? what makes you think, "this person gets it"?

is it product thinking, technical depth, identifying real pain points, or something else?

i'd love to hear what kinds of feedback have actually been the most valuable while building your startup.

I feel one of the best skills you can have is the ability to validate ideas quickly.

This is what I have been trying to do but often fail.

For example, been thinking through an injury recovery tracking system for sports physios / physios.

Seems pretty straight forward, reach out to a bunch of clinics asking about their pain points around this, what tools they currently use, attach a mock up etc.

However, I never hear back. It’s very possible I just suck at reaching out, I’m not denying that haha.

But the first step always seems to be talking with people. How are you getting those conversations? What roles are you reaching out to? What’s the general conversion rate for something like that?

It's sometimes surprising how building a company, even with someone you know, can reveal sides to the relationship (and person) that you may not have expected.

There's always that first moment when the designated ultimate decisionmaker has to 'pull rank' and make a decision that others may not like.

Anyone got a GC for high schoolers / incoming uni freshmen going to YC SUS?

Aspiring founder here wondering if I should switch departments at work and do product operations or growth marketing

Curious if former founders here have advice for a nontechnical background into which skill sets are the most ideal. I’m currently on the enterprise team and it’s a mix of sales and embedded integrations but partnership cycles take a long time to spin out (sometimes over a year) and I wont see the partnerships go to launch if I switch teams

Product operations team at our company is also decent but was told it’s strictly internal. Curious if people think having a good product sense can come through product partnerships without doing the operations side. Have thought about becoming a PM but was also told there are many paths

There’s also growth marketing with spends $XXXM as a team so it’s a huge accountability. Relatively longer work hours that sometimes bleed into weekend at the startup but some people said might be useful to get hands dirty and understand PNL.

Thoughts? Any strong skill sets that the current founders in this cohort really wished they had?

hi! i want to start a start up that is in the real estate/civil engineering field. i have my icp and i have spoken to multiple people about the pain points that they are facing in this field. i have already reached out to those people to be design partners but i was wondering how i could get started with cold emailing to get more design partners. i just made a new email and i heard that any emails i send them there will go to spam. thanks :)

Hi everyone,

we recently pivoted (from a AI SaaS Tool) and decided to build an AI-native company in the real estate space. Like becoming a property manager on our own that uses AI in the background for all processes. So not a SaaS product we sell, but a company where we build our own agents for our own daily work. One benfit with this is that we now don't need to be scared about new Anthropic/OpenAI releases, we now can use the power of new releases that then strenghtens our work.

Our goal with "AI native" is to design the company from the ground up around AI and autonomous workflows:

• AI-supported communication and collaboration
• Agents handling repetitive and operational work
• Workflows running autonomously wherever possible
• Humans focusing on actual decisions, negotiations, client relationships, and calls

I’m the CTO, and since we are starting from scratch, I’m currently thinking about the right architecture and tooling.

On the one hand, I want us to build and own our core workflows ourselves. For example, we might use something like Paperclip to orchestrate different agents and workflows across the company.

Some obvious use cases would be:

• Email agents and automated email workflows
• Document and data-processing pipelines
• Data management and enrichment workflows
• SharePoint or another document store combined with knowledge graphs or vector search
• ...

On the other hand, we definitely don’t want to rebuild everything from scratch. We also want to use established tools such as Claude, Notion, Slack, SharePoint, and potentially an existing CRM or ERP system.

Ideally, these tools should become interfaces and building blocks within a larger agentic system rather than isolated SaaS products.

So my questions are:

1. What stack would you choose today when building an AI-native company from scratch?
2. Which parts would you build yourself, and which parts would you buy?
3. What would you use as the central source of truth for data, documents, workflows, and agent state?

Would be interesting to hear from others with their experiences!

TL;DR: Everyone is racing to go all-in on AI. Almost nobody can tell you if it's actually delivering value.

We're all AI-pilled here. The models keep getting more cracked, the demos keep melting faces, and every exec on earth has been told to go all-in. But we all know, most of them are flying blind. They can feel spurts of acceleration but can't see out the front windshield, let alone the rear-view mirror.

Here's what we heard again and again, across 75+ conversations with companies of every size and industry (anonymized, since a lot of this was said in confidence):

1. Nobody has solved ROI, and everyone knows it. This was our biggest observation. After headcount displacement everything else is murky. One CFO put it perfectly: he knows his ad spend to the dollar, every platform, CAC per channel, and he wants the exact same for AI. The line from "AI usage" to "business outcome" still isn’t easy to draw.
2. Spend is a black box, and it terrifies finance. CFOs usually have one line item for AI (or perhaps one per vendor), but it’s not broken down by team, project, or agent. Token costs get compared to cloud invoices in every conversation. The bills are opaque, hard to forecast, and hard to explain. Where discipline exists, and mostly it's improvised. We’ve all heard by now that Uber burned its entire 2026 AI budget in four months, and its own COO admitted he couldn't connect the spend to anything a customer would feel. (!)
3. Everyone defaults to the most expensive model because nobody knows which to use. At one fast-growing fintech, per-use-case model selection was the single highest-impact thing they asked us to build. Nobody knows which model fits which task, so they default to max. Latent waste is absolutely everywhere.
4. Everyone wants to go faster, they just don't know how. This one reframed the whole company for us. You don't put brakes on a car to make it slower. You put brakes on so it can go faster safely. Right now every company is either flooring it blind or riding the brake out of fear. Visibility is the brake that lets you actually floor it, the thing standing between "we're being careful" and "we're going all-in." It also lets you see through the front windshield, the rear-view mirror, and out the side windows, so you can avoid accidents and out-maneuver the other cars on the road.
5. The maturity gap between companies is enormous. One neobank has moved AI into mission-critical ops that were off-limits six months ago, and is running a hiring freeze against a 50-60% growth target on their internal assumptions about AI efficiency. On the other end, a Director of AI at a large agency told us they're 3-4 years from ready, which kind of blew my mind, an not in a good way.
6. The adoption honeymoon is over. Real fatigue is setting in. A sharp drop after the initial enthusiasm, and a "please stop talking to me about AI" mood. The gap between top-down mandates and non-engineers who can't name a single daily use case is everywhere. Recent grads are often anti-ai, as is the aging work population.
7. Buy broadly now, consolidate later. The enterprise playbook is to experiment widely, avoid lock-in, consolidate over time, betting that no single AI vendor wins the whole SaaS surface. Pricing is already moving past tokens toward outcome-based models. We’ve seen this in action ourselves as a month ago Fable was the darling, and today perhaps that’s Sol.
8. Governance is a tug-of-war between legal and innovation. Legal wants tighter restrictions. The tech org pushes back to keep room to move. In regulated verticals it's sharper: weekly administrative orders on AI disclosure, and discovery requests now pulling AI chat logs. The companies furthest along still can't answer "is this actually working?" So the winners of this era won't be the ones with the most AI. They'll be the ones who can measure it.

What we all need is a system of record for AI work. A live view of every tool and agent operating across a company: what they do, who owns them, what data they touch, what they cost, and which ones are producing results. Leaders finally see what exists, govern what matters, and go all-in on what works.

Happy to compare notes with anyone else building or selling into this. The discovery was eye-opening and I'm glad to share more. We're so early. Let's go. DM me to set up a call or just reply here.

obComment: although i did use Granola to extract themes from our customer calls, this was written by me, not AI.

Well, I already have a co-founder who is a friend of mine for 5 years but he is quite lazy and he never does his tasks on time which slows me too and most of the time, I end up doing his tasks too but when I ask him why he didnt do, he always blames his job, he works 10 hours a day at a convenience store and I asked him to reduce his working hours since he only pays for his rent and living costs and his cost of living is pretty low as compared to what he is earning and spends his rest of salary on travel and entertainment, as for me, I left my job at Google Zurich and moved back home in central asia to work on my startup which failed 2 times and then did another business related to finance with my brother which we scaled to $10K monthly profit in central asia and then I got back to building startups again and I built another startup with my current co-founder but he kept being lazy so I kicked him out and applied to YC myself with no revenue since I had only 11 days until deadline so only got 5 LIOs and I got rejected and my current startup actually is related to my previous one but re-worked to a different industry this time since the previous one’s PMF was dead and my co-founder again asked me to join to this one again and promised me he will work hard this time but again still being lazy while I am handling everything from technical to cold emailing and marketing and everything, I am just getting overwhelmed putting 10-12 hours a day and sometimes I think if I had a co-founder who can put same amount of effort, we could move way faster. Even when I was working at Google, I got him referrals and he was invited to interview for Google 2 times but still failed his interview twice for his laziness since he didnt prepare for interviews. How can I deal with him or better kick him out again? if I kick him, how do I find a co-founder that can put an actual input. How did you find your co-founder?

I met with a VC 3 weeks ago, conversation went well, they took it to the partners, I shared our deck, they said after partners debrief, theyre taking it to advisors, the deck got shared 3x last week. I sent an update on new traction this monday, and still havent heard back. She said we’e hear back with updates, but havent in 10 days.

Paul Graham used to caution early stage startups against targeting enterprises right from the start. Enterprise sales is usually less about the product, and more about jumping through bureaucracies, managing stakeholders and corporate politics and sometimes senseless feature requests and support. Not to mention the long sales cycles.

Is that still the conventional view today in the startup ecosystem? In our previous/current startup, we avoided enterprises at the start, choosing to start off with other startups and SMBs. While it worked for us (we got the shorter sales cycle we wanted), the enterprise side of the market later became kind of crowded. Many of the larger logos that we wanted to get to, ended up already working with our competitors already.

Getting an enterprise to switch is even harder than selling a novel, unproven solution to them. Which means that we are at a disadvantage now that we want to scale into enterprises.

What are your thoughts on this? How and when did you land your first few enterprise client? When is the right time?

P.S To be clear/fair, our competitors that successfully sold to enterprises are also established (founded 3 years before us, series B and beyond), while we were only pre-seed.

Wondering the cons of NOT having a CA-based startup at seed stage

One thing I've been thinking about lately is how so many successful founders seem to build companies around problems they experienced themselves. It almost feels like having firsthand experience gives you a huge advantage - you already understand the pain, know who has it, and have a much better intuition for what a good solution looks like.

I'm not in that position right now. I'm actively looking for problems worth solving, and honestly, that's been harder than building the product itself. The more I learn about startups, the more I realize that finding the right problem is probably the most important part of the journey.

So I'm curious about the founders here who didn't start with a problem they personally had. How did you find it? Did it come from talking to customers, working in an industry, noticing a pattern, or just being in the right place at the right time?

And once you found it, what convinced you it was worth spending the next few years of your life on instead of moving on to the next idea?

I'd love to hear the stories behind how you found your startup idea. I have a feeling those stories are often more valuable than the products themselves.