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).

Genuinely curious what the community does here.

We've been talking to hundreds of teams building with Cursor, Claude Code, and other agentic tools and the honest answer from most of them is: "We just run it and hope."

Some do a quick manual click-through. Some write a few spot checks. Some just ship and wait for users to find the bugs.

We built TestSprite to solve exactly this autonomous testing that runs from your PRD and codebase but I'm curious what your actual workflow looks like before you merge.

Are there any topics you wouldn't ask AI for advice on?

We've literally put our entire lives in the hands of artificial intelligence.

From work responsibilities to relationship issues, to advice on philosophy and our bodies.

Over the past few days I ve been quietly studying launches scrolling through pages, looking at upvotes, comments, follower counts, and trying to spot patterns.

And honestly the pattern isn t always obvious.

While building a product, I ve also been trying to run content on social media to bring in more traffic. I experimented with creating AI-generated characters and producing UGC-style videos around them.

During this process, I realized something interesting: there are hundreds of tools that can generate virtual characters and UGC-style videos. But what actually makes a video engaging isn t the tool - it s the authenticity of the person creating the content.

AI workflow automation tools help you design, run, and evolve workflows that actually take action not just suggest what to do next. Some use AI to make workflows easier to build. Others embed AI directly into execution so workflows can handle ambiguity, make decisions, and adapt as they run. The strongest tools do both.

This definition excludes tools where AI only generates static workflows and then steps aside. It also excludes general assistants that never meaningfully participate in end-to-end execution.

Genuine question for makers here - what s actually worked for you to get useful feedback fast?

• live demos?

• onboarding calls?

• shipping daily + letting users yell at you?

• communities like PH?

Are you in favour of banning social media for users under 16?

Recently, there has been a surge of laws and restrictions targeting social media platforms for young users.

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:

It s almost here for me. In three days, I ll be relaunching a major update for the app I have been collaborating with, and I ve set clear boundaries for myself about what I will and won t do before the launch. I guess these are some general, unwritten rules I try to follow

Definitely DON T:

• Accept offers from charlatans promising votes or engagement for money

• Send unsolicited messages begging for votes or support

• Spam other people s posts with launch announcements