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Nothing felt like a real hangout, so I built Couch
Tried everything for long-distance hangouts and nothing felt right.
Google Meet and Zoom felt like meetings. Discord felt cluttered and not built for just hanging out.
So I built Couch.
It s a simple space where you can watch movies, play games, and hang out with friends in real time without switching apps or dealing with setup.
We spent 6 months building for enterprise. Nobody bought it.
We thought we were ready.
Bigger deals. Fewer customers. Better margins. That was the dream.
So we built enterprise features. SSO. Advanced permissions. Audit logs. A whole new pricing tier starting at $2,000/month.
We spent 6 months. Three engineers. One dedicated product manager. Endless meetings about "enterprise readiness."
VertoX update — getting very close to launch
Hey everyone
Quick update on VertoX.
We ve made a lot of progress on the backend and core systems. We re building our own open-source ASR NMT TTS pipeline and aiming for ~1 second real-time translation.
Right now, we support 17 output languages and 10 input languages, with plans to expand further.
How do investors value an MVP you built in 2 weeks with AI?
There used to be at least some clear logic behind startup valuation.
You d take:
hours rate MVP cost.
That gave you a rough valuation floor.
Not perfect. But it was an anchor.
That anchor is now gone.
AI made MVPs almost free.
~$300. Two weeks. One person.
And if a product costs almost nothing to build
what is valuation based on now?
The answer is uncomfortable:
your product itself is no longer inherently valuable.
Investors no longer look at:
how long you ve been building
how many developers you have
how much money you ve invested into the product
Because none of that proves anything anymore.
Now there s only one question:
who is paying?
If no one is
then in their eyes, your startup is worth roughly what your MVP cost.
Here s what actually changed:
why pre-seed is now about MRR, not MVP
how investor requirements shifted
why solo founders suddenly became viable
and where moat actually lives when your product can be cloned in two weeks
Full breakdown here
https://substack.com/home/post/p...
And I have a qustion to you:
Did AI kill innovative startups and turn venture into short-term revenue games?
What do you think?
How do you decide what features should be free and what should be paid?
Let me start from the creator s perspective:
I personally don t have a product (apart from hiring people for creative work or offering personal consultations).
But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).
We paid $25k for our website. I vibe-coded a new one in 2 days.
Last year we hired a design agency to build our marketing site for @Basedash. They did an incredible job. The headline makes it sound like I'm dunking on them, but I'm not. The site was genuinely great. They built it in Framer so we could manage content ourselves, which was a completely reasonable bet at the time (and something we explicitly asked for).

Is usage-based pricing becoming the norm for AI tools?
Hey everyone,
I've built my product around traditional SaaS pricing (monthly tiers), but I m starting to wonder if that model is getting outdated, especially with more AI-powered and compute-heavy tools entering the market.
That shift requires real architectural changes, instrumentation, metering, billing logic, and UI changes, not just pricing tweaks. It s something I m starting to seriously think about for my own product.
In particular, AI usage has real COGs (every prompt costs money), and I m seeing more platforms experimenting with usage-based models, or hybrids like SaaS base + usage + overage.
For those of you building AI or compute-intensive tools:
Ohh boy! I'm building 10 startups in 100 days.
Six years ago at a funeral (all good stories start at a funeral right?), a close family friend told me his tenth company was the one that worked. The first nine failed or went nowhere.
For years he thought something was wrong with him. Then he became an early-stage investor. Same math. Only one in eight to eleven companies ever returned anything most eventually went out of business.


