Parth

Most crypto projects are burning money on growth and have no idea what's working. Me and @akshit_varsani_ sat down to talk about the brutal reality we kept seeing: founders with "100K wallets connected" who couldn't answer basic questions about their users. No idea why. No idea how to fix it. That feeling of flying blind while burning money? That's why we built @cryptiqueio Here's what we kept hearing from every pre-TGE founder we talked to: → "Spent $10K on campaigns. Users came. But which campaign worked? No clue." → "Day 1: 5,000 wallets. Day 30: 50 active. Where did they go?" → "Can't tell my power users from airdrop farmers. Everyone looks the same." → "VCs ask 'how many real users?' I just... don't know." → "Every marketing decision is a coin flip. Twitter or Discord? Content or events? Just guessing." The brutal truth? Most projects aren't failing because of bad products. They're failing because they know nothing about their users. You can't optimize what you can't measure. And right now? Most teams aren't measuring what actually matters. That's the gap Cryptique.io fills. From "we have wallets" to "we know our users." Source attribution. Retention intelligence. Power user identification. Sybil detection. Real-time behavioral analytics. The difference in TGE outcomes? Night and day. Podcast out soon!

@1Umairshaikh Product discovery?

Distribution used to be the second problem. Now it's the only problem. Anyone can build. Almost nobody knows how to be found.

@tankots Especially when the threshold to build any feature has drastically reduced. - written by @WisprFlow

our NPS dropped from 70 to 35. my entire team panicked. but it was the best thing that happened to our company. when wispr started getting traction, everyone wanted us to build everything. meeting recorder. ai note-taking. voice-controlled app launching. we started working on several at once. the team was excited. users were asking for it. felt like momentum. then our nps crashed. what actually happened: our core product got worse. as we scaled from thousands to millions of users, a 0.1% failure rate meant thousands of people hitting issues daily. we were shipping new features while the foundation was cracking. i looked at dropbox, spotify, airbnb. they all built one singular platform first. only added second products at massive scale. so i made the call: kill every new feature in development. the team pushed back. "but users are asking for these." users ask for a lot of things. our job is to give them one thing that works perfectly, not ten things that work okay. wispr flow can scale to $1B in revenue as one product. if we ever build something new, it cannot come at the cost of our current product and current customers. our nps recovered to 72. customers started to notice the difference. the hardest part about building a company isn't deciding what to build. it's deciding what to kill.

@devops_nk With AI, having the clarity from Day 1 of what my car should look like is super important.

Honestly, this is the most accurate diagram I've seen. Waterfall: You plan for 18 months and deliver exactly what nobody needs anymore. Agile: You deliver something usable at every step, but the CEO keeps asking, "Where's the car?" AI: You get the car on day one. It has six wheels, the doors are on backwards, and it has a rocket launcher. You spend more time making it yours than actually "building"; it's shaping. owning. verifying. That's what the best AI developers do now. They don't build. They shape and own.

@aakashgupta There should be a specialised AI that does this!

The single best way to get better at writing PRDs is to spend a week prompting AI prototyping tools. "Make it look better" returns garbage. "16px gap between cards, 12px border radius, subtle box shadow on hover" returns exactly what you asked for. The feedback loop is instant. Write a vague prompt, get a vague result, rewrite with specifics, get a precise result. Within a few hours you internalize the pattern: every word you leave out is a decision you're delegating to a machine that doesn't know your users. That discipline carries over to every artifact a PM writes. PRDs, design feedback, engineering tickets, stakeholder updates. The PMs I work with who prototype regularly write noticeably tighter specs because they've trained themselves to eliminate ambiguity through thousands of prompt iterations where the cost of vagueness was immediate and visible. The prototyping tools are teaching a generation of PMs to spec like engineers. Nobody planned it. It's a side effect.

@abhinav_g21 Let’s go

Calling all builders in Delhi working on Web3 & AI 🇮🇳 Let’s connect and If you know someone, tag them too Cooking up something interesting, would love to loop in the right people

@thenanyu And why do you think the sales team shouldn’t be a part?

Yes. PMM is a product concern. I see a lot of orgs out there combining design and product management, which I think creates all sorts of poor incentives. But product management and product marketing are a much more natural fit together.

@gregisenberg will we just be interacting with harwdware and actions in software get triggered on their own. just like a user currently interacts only with frontend while backend actions get triggered without a direct input from the user

the way we use the internet is completely different than how we used to use it 5 years ago there was no LLMs, no AI agents, no vibe coding 5 years ago and in 5 years it will be completely different again

@oprydai Be a generalist or a super-specialist in today’s world

become a generalist. specialization makes you efficient. generalization makes you dangerous. what it actually means: • learn across domains → math, physics, software, economics, biology. patterns repeat across fields. • connect ideas → innovation happens at the intersection, not inside silos. • adapt fast → when one field shifts, you don’t collapse, you pivot. • see systems → specialists see parts, generalists see the whole • build end-to-end → from idea → design → implementation → delivery the world rewards specialists in stable environments. it rewards generalists when things are changing. right now, everything is changing. don’t just go deep. go wide, then stack depth where it matters.

@rdominguezibar Covid killed wework

VALUATION MATTERS

@garrytan But climb anywhich ways

If you don't like the climb, choose a different mountain.

@soleio @bhorowitz The “why” should be data-backed and not just a gut feeling

I’ve long held @bhorowitz explained it best: “When a company goes astray, you talk to employees and they say, ‘We have no strategy. We don’t know where we’re going.’ The strategy is the story. They’re not different. The strategy is the story you tell. It’s the why. If you can’t tell that in a massively compelling way, who’s going to follow you? That’s what makes people get up in the morning and do stuff. The story must explain at a fundamental level why you exist. Why does the world need your company? Why do we need to be doing what we’re doing and why is it important?”

@scottbelsky knowing which story to tell >>>

100% products are stories. people don’t just buy aggregated atoms, they buy the narrative that brings it all together,

@tfadell Messaging and features go hand in hand only when there’s product clarity.

Most tech companies break out product management and product marketing into two separate roles: Product management defines the product and gets it built. Product marketing wires the messaging- the facts you want to communicate to customers- and gets the product sold. But from my experience that's a grievous mistake. Those are, and should aways be, one job. There should be no separation between what the product will be and how it will be explained- the story has to be utterly cohesive from the beginning. Your messaging is your product. The story you're telling shapes the thing you're making. I learned story telling from Steve Jobs. I learned product management from Greg Joswiak. Joz, a fellow Wolverine, Michigander, and overall great person, has been at Apple since he left Ann Arbor in 1986 and has run product marketing for decades. And his superpower- the superpower of every truly great product manager- is empathy. He doesn't just understand the customer. He becomes the customer. So when Joz stepped into the world with his next-gen iPod to test it out, he fiddled with it like a beginner. He set aside all the tech specs- except one: battery life. The numbers were empty without customers, the facts meaningless without context. And, that's why product management has to own the messaging. The spec shows the features, the details of how a product will work, but the messaging predicts people's concerns and finds way to mitigate them. - #BUILD Chapter 5.5 The Point of PMs

@gregisenberg The critical question now becomes what to build and why. The how is already solved!

the gap between "i have an idea" and "i shipped a product" just got so small it's basically not a gap anymore for anyone, anywhere

@kunalvg Interest media

Social media is about to split in two. Right now you have Instagram, X, LinkedIn. Platforms built for everyone. What’s coming is the opposite. Tiny platforms. Built around one obsession. Sneakerheads. Indie founders. Anime collectors. Carnivore dieters. Not followers. Not likes. A tight circle of people who live and breathe the same thing you do. And it won’t just be online. The best vertical communities will spill into real life. Meetups, dinners, retreats. Built around the same obsession. Why this is happening now. AI is flooding the internet with content nobody asked for. The noise is only going to get worse. People are already feeling it. More time online. More lonely. The answer isn’t a bigger platform. It’s a much smaller one. The next big social media company won’t look anything like Instagram. It’ll look like a club with a very strict door policy.

@aakashgupta We’re building an AI product analyst that does this!

The fastest way to lose credibility in a product review: present a number you can't explain. Every PM using AI for data analysis has this vulnerability right now. Claude Code can run the queries, segment the data, do statistical analysis. But when your VP asks "where did this number come from," most PMs have nothing to show except "I asked AI." That credibility gap is the real bottleneck. Not the analysis itself. The fix is Jupyter Notebooks inside Claude Code. Every query is visible. Every calculation is traceable. Every result renders with the exact code that produced it, right inside VS Code. Your stakeholder can see the methodology, not just the output. Think about how most PMs do data work today. They wait two weeks to get on an analyst's roadmap for a question they're not even sure is worth asking. Or they ask ChatGPT and paste a number into a slide with no audit trail. This workflow analyzed 213 survey responses, segmented by role, scored by enterprise interest, and visualized the distribution. With full proof of work attached. The irony is that AI analysis with a Jupyter audit trail is now more rigorous than most human analysis delivered over Slack. The PM who can show exactly how a number was calculated will be trusted with the bigger questions. The PM who says "the data shows" without showing the data will stop being asked. Show your work.

@naval Product clarity is the new moat to ship fast!

Vibe coding is more addictive than any video game ever made (if you know what you want to build).

@startupideaspod know what to build before start building

this is the most asymmetric time to start building. the window is 12–24 months. the build cost is basically zero. the only thing missing is you starting.

@sumedha2199 + designer

if you're not becoming some mix of dev + data scientist + PM + researcher + salesperson + writer + etc you're either under-challenged or under-leveraged feels like this is just where things are at now stack your leverage

@startupideaspod > Know what to build before start building it. > Your initial users will tell you what to ship next and why. > Make sure you capture user signals.

how to actually get customers for your vibe coded app: - let AI sell for you (MCP servers) - build 10,000 SEO pages once (programmatic SEO) - vibe code a free tool by lunch (it markets itself) - get cited by ChatGPT (answer engine optimization) - allow your users to create content for you (viral artifacts) - buy a 10K subscriber newsletter for $5K - turn one voice memo into 20 pieces of content Pick two. Start this week. Stop just vibe coding. Start getting customers.