A few years ago, getting a VC check was the ultimate shortcut. The fastest way to scale. The signal that you'd "made it." But with AI is a little bit different.
Global VC funding declined 30% in Q1 2024. One of the lowest quarters since 2018. And bootstrapped startups are quietly catching up. Recent data shows bootstrapped businesses are growing as fast as VC-backed startups, while spending only about one-quarter as much on customer acquisition.
I launched my first product here cold, with no audience and no pre-launch community.
It got real feedback, which I'm grateful for. But once launch day ended, traffic dropped to almost nothing, even though I've kept posting consistently.
My takeaway: solving a problem gets people to try your product, but it doesn't bring them to you. That part is distribution, and I skipped it.
For makers who've launched a second time: what did you do differently before relaunching?
I am Janis, working on a project to improve the healthy working culture for the companies and for the employees. I would love to hear your thoughts about this topic. Questions regarding this topic https://janisrozenfelds.typeform...
Startups are hard & can be stressful; it's an emotional roller coaster. I am looking forward to hearing back what are you doing to keep your mental health & inner peace. Share your experience.
Product Hunt just added a new leaderboard and it finally answers a big question: who s actually contributing to the platform?
For a long time, Streaks were the main signal of activity on Product Hunt. But streaks only showed who visited every day. Opening the site or app daily doesn t necessarily mean someone is adding enough value.
I've been going deep on Telegram as a prospecting channel and I'm curious how others handle it.
The problem I keep hitting: Telegram communities are full of buying signals people asking for tool recommendations, complaining about a workflow, looking to switch vendors but reading every thread manually doesn't scale, and scraping members is spammy and mostly useless.
An agent can have permission to use a tool without having enough context to make the business decision behind it. That's the boundary I'd want to define before giving it write access.
For me, drafting a customer email and sending it are separate permissions. Recommending a budget change and applying it are separate decisions. The useful question is what the agent can commit you to, and who carries the consequence if it gets that wrong.
I'd define the allowed action, the affected people or systems, the spending limit where relevant, and the point at which a named person must approve. I'd also want that person to see what will change before agreeing.
Rollback helps, but it doesn't erase every consequence. You can restore a price after someone has bought at it. You can correct an email after someone has acted on it. Neither returns you neatly to the starting position.
