I am curious how people actually do it.

There are tons of stories about founders launching SaaS products without an existing audience. No Twitter following, no newsletter, no community, nothing. Yet some still manage to get early traction and even hit real MRR.

If you have started from zero, I would love to hear:

• How you got your first users

• What channels brought the earliest traction

• Whether cold outreach works or not

• If content played a role or if you focused mainly on building

• What you would do differently if you had to start again

I've used ChatGPT and other AI tools while building my startup, and they've made it possible to take on work that would normally require a much larger team. Research, technical problem-solving, planning, and exploring new ideas can happen much faster. But one thing I've learned is that completing more work doesn't necessarily mean the business is moving forward at the same speed. You can build faster, solve technical problems faster, and make improvements faster, while the harder questions about customers, adoption, and business growth still take time to answer. It's changed how I think about productivity as a founder. I'm learning to distinguish between how much work gets completed and whether that work is actually moving the business forward.

For founders building with AI, what's one lesson you've learned about the difference between moving faster and making real business progress?

I never paid much attention to these badges before.
I assume they were part of the original gamification system.

There were several badges to choose from, and you could even earn the same type of badge multiple times.

A few days ago I saw some posts here about:

the number of discussions is decreasing,

sometimes they are approved later,

that there is "other community growth" I don't know what was meant by that and I'm just guessing.

The AI researchers at Andon Labs, the people who gave Anthropic Claude an office vending machine to run, and hilarity ensued, have published the results of a new AI experiment.

They wanted to see if LLMs were technically capable of functioning as a robot s brain, that is, connecting their thinking (textual decision-making) with real sensors and movement.

We built a pricing page with 5 tiers a $9 starter, $29 basic, $49 pro, $99 business, and a custom enterprise plan. Conversion rates dropped by 14%.

Instead of making it easier for buyers to enter, we created a decision matrix. Visitors spent 20 minutes comparing feature cells rather than evaluating if the product solved their problem.

When we collapsed everything into two clean options (a core utility tier and a power-user tier), trial to paid conversion jumped almost overnight.

For those who have radically simplified their pricing: did you see an immediate lift in activation, or did you panic about losing top-of-funnel signups?

As a growth designer, I look at newsletters from two perspectives: how fast they prove their value, and whether they make me feel like I m giving away my inbox for nothing.

Getting an email address is relatively easy. The harder part is designing a sign-up experience that promises genuine value without feeling like a bait-and-switch.

Going through 40+ opt-in pages recently, a few things stood out to me:

Most pages use vague promises like "Join 10,000 readers." A high-performing page tells me exactly what I will learn in the first issue.
The best opt-ins don't ask for a commitment upfront they offer a free sample issue or an archive link so I can test the waters first.
Trust matters: the pages that kept me engaged showed a clear frequency (e.g., "One email every Tuesday") and a visible "unsubscribe anytime" button.

At least for me, when I buy something, I consider:

1. price in relation to time, how long the product will serve me

2. investment whether buying the product will generate money for me

3. benefit solving a problem, saving time, fulfilling a need