It did for us.
3 customers came to @Flexprice last week. No ads, no cold DMs. Just conversations.

Most people treat Product Hunt as a one-day spike.
I treat it like a community of builders.

We launched Flexprice last year and learned (the hard way) what works here and what doesn t.
So now I keep it simple:

I support makers launching on Product Hunt for free
I give honest product feedback as a real user
I help with launch strategy when useful

What s worked for us looks very different from spray-and-pray.

We ve learned that outbound works when it s intentional at every step.

A few things that made the biggest difference for us:

Getting the ICP really right. Sometimes the first outreach isn t to the buyer, but to someone who can open the door.
Personalization isn t optional. Company context, role, recent updates. Generic gets ignored fast.
Channels are chosen by output, not comfort. We double down on what actually converts.
The first message rarely works. Conversations usually start around the third or fourth touch, if there s value each time.
Timing matters more than volume. Funding news, hiring, social posts. Showing up when the problem is top of mind changes everything.
We focus on relationships, not just pipeline. Some buy later. Some refer. All conversations compound.
Context before calls helps. If someone engages multiple times, the conversation feels very different.
Signals matter. Engagement often tells you when to reach out, not just who.

Over time, I ve realized how much effort we put into our websites on landing pages, pricing, testimonials, product tours and yet, most visitors only ever deeply interact with one or two sections depending on your ICP.

• For developer-first products, that s usually docs.

• For consumer apps, maybe it s onboarding or pricing.

• For enterprise tools, perhaps case studies or ROI calculators.

The rest is mostly noise or at least secondary.

It made me wonder:

I realized I was stuck in AI FOMO.
Bought multiple courses. Knew every tool by name.
Hadn t built a single working automation.

So I stopped and asked one question:
"What repetitive task can I hand off to AI today?"

Not after another course. Not after learning more. Today.

That shift mattered.

We kept hearing get your ICP right.
But what we learned is that who you reach out to first matters just as much as who eventually decides.

In most companies, there isn t one ICP. There s a sequence.

• Someone experiences the problem daily.

• Someone else prioritizes it.

• Another person signs off on it.

If you jump straight to the top, you often lack context.
If you stay too low, momentum dies.

A lot of people read YC RFS Spring 2026 as a trend list.
It s not. It s a signal of where work inside companies is quietly breaking.

Here s how this shows up in real teams:

Product teams
YC references @Cursor , but the opportunity isn t coding faster.
It s helping PMs synthesize interviews, metrics, and feedback to decide what to build next.

Finance and hedge funds
Firms like Renaissance, Bridgewater, and D.E. Shaw won by systematising decisions.
AI-native hedge funds push this further with continuous, machine-driven strategies.

As more teams build AI agents, search, and personalized feeds, one problem keeps surfacing.
Not generation.
Not model quality.

It s retrieval and ranking. Deciding what information should show up and in what order.

Most teams solve this by stitching together systems. Vector search for meaning. Keyword search for precision. Custom logic for business rules. Over time, relevance logic spreads everywhere and becomes hard to change.

@Shaped approaches this differently.

I looked into a few of their launches and what stood out wasn t a secret hack.
It was how little they tried to launch.

Their tagline isn t hype.
It s literal. Write, edit, and chat about your code with AI.

No buzzwords. No promises. Just what it does.

The pattern is simple:

This debate often gets framed as Should researchers use AI for literature reviews?

I think the real question is different.

Is it ethical to spend hundreds of researcher hours on mechanical work when that time could be spent advancing actual knowledge?

Think about a researcher spending an entire weekend searching papers, skimming irrelevant abstracts, copying citations, and fixing references. That s not insight or discovery. That s overhead.

Watched a launch yesterday. By morning, the founder's DMs were full of pitches from other builders. No questions about the product. Just "here's what I'm working on."

Look, networking is part of this. We all need it. But we're skipping a step.
Launch day used to mean something. Try the product. Ask real questions. Then connect.

Now we've optimized so hard for efficiency that we skip straight to pitching.
@Mastra a hit #3 yesterday despite this. But think about what that says quality products have to fight through noise just to get noticed.

Here's my take: we're not wrong to network. We're just moving too fast.