Nadi Hassan

This is very true. The valuation trap is real. But I don’t think this is a YC story. It’s a market story. We’re seeing the exact same thing here in Israel. Seed rounds at 30–40M for companies with no product, no real validation, sometimes barely a prototype. Not second-time founders. First-timers. I’ve personally seen more than 20 rounds like this just last year. This isn’t about YC “pushing” companies. The system as a whole hasn’t adapted. The cost of building collapsed. The speed of iteration exploded. But pricing logic stayed anchored in 2021. When capital doesn’t recalibrate to reality, it doesn’t just create paper risk. It creates structural fragility. Good companies get boxed into impossible expectations. They are forced to grow into valuations instead of growing into product-market fit. That’s how promising businesses die early. The tragedy isn’t overvaluation. The tragedy is killing companies that could have become durable, profitable, meaningful businesses. This isn’t a YC issue. It’s a venture industry inertia issue. And the longer it takes to adjust, the more collateral damage we’ll keep seeing.

5

Over the last 7 years I’ve helped startups hire software engineers. During that time I’ve looked for software, tools, and solutions (really anything) that could help make recruiting faster. And tbh after all that time I never really found anything great. Most recruiting tech is disappointingly average. If you’ve ever hired, I'm pretty sure you can emphasize. So now I’m working on solving recruiting now from a software angle (higher leverage, software is OP) I believe inbound recruiting in part is a poor experience for both employers and candidates because there is way too much friction in reviewing resumes which results in high opportunity cost for recruiters, ignored resumes and what feels like a black hole for applicants. My thesis is pretty simple - build a system that surfaces everyone who is a great fit who shows interest with zero false positives / negatives. If you build this well, hiring teams are incentivized to increase the top of the funnel / reach 100% of the people who could be interested in working with them instead of cold messaging the same pool of linkedin candidates that are also ignoring everyone else's messages. There’s a lot to fix in recruiting but starting w/ job ads (making them frictionless + more interesting) & screening (semantic + keyword but good + filtering against additional data nobody has because our job ads capture more) p.s. I dont say job posting because I'm trying to reframe the entire idea of an applicant / application. Beyond the point that a lot of people (unfortunately) perceive applicants as less qualified it’s more about making the form itself less of an application and more of a “hey I’m interested in what you guys are doing” which reduces unnecessary friction in requiring some structured document in order to send a signal. Reduce friction, increase top of funnel, improve how to deduce signal from noise = faster hiring.

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5 Comments

Default to AI. Doesn’t mean it does everything - it means you use it for everything it can do well as a utilization filter for the work you do.

5

Everyone in the mobile app space should be paying attention. The road to launch on new ventures is getting shorter and shorter…

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1 Comment

Love this memo—it's bold, unapologetic, and exactly the kind of leadership needed to truly embed AI into any company’s DNA. Defaulting to AI isn't just a policy; it's a mindset shift that will separate the innovators from the laggards. I couldn't agree more that measuring adoption in reviews is the accountability hack we've all been waiting for.

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Last month, in Y Combinator's call for startups for their Spring 2026 cohort, they called for "AI Native Agencies." YCs frames this opportunity simply: "agencies of the future will look more like software companies, with software margins. And they'll scale far bigger than any agencies that exist in these fragmented markets today.” We believe YC is right. We differ, though, with YC in our belief in where the value will accrue. More on this here 👇👇 https://lnkd.in/g6iNtTUh

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If you're building with LLMs, watch out for this hidden cost... LLMs are evolving faster than your prompt stack can keep up. What breaks isn't always visible. Until it is. Every model shift carries silent regressions that chip away at velocity. The more LLM logic you ship, the more fragile your system becomes. Here's where the real cost shows up.

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