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I'm a freelance consultant. Tried Folk, Attio, HubSpot free, Google Sheets. Never stuck with any of them. The problem wasn't the features, it was that I never went back to the tool.

So I built a CRM inside my AI assistant (Claude + MCP server + Supabase). Six contact lists, email drafting, a Chrome extension that scrapes LinkedIn profiles at $0.001 each. Total cost: $10.

The whole thing lives where I already work. That's why I actually use it.

After more than three years of observing this platform (mainly in the forums), I can see which posts have helped you the most. [Yes, I can tell based on their performance.] In addition to updated news from the tech industry, you liked the most:

website roasting and

tagline adjustments/improvements for launch day (mostly from @aaronoleary )

I keep going back and forth on this, so I m curious how others think about it.

At what point do you start taking non-English markets seriously?

• only after you feel solid PMF in English?

• when inbound users from certain regions show up?

• by picking one market early (Japan, LatAm, etc.) and committing?

• or do you just keep pushing it off to stay focused?

As leaders, we spend most of our time pouring into others. Our families, our friends, our teams. We invest our time, energy, and presence in being there for others. But somewhere along the way, it becomes easy to overlook an important question

Who is pouring into you?

Hey PH

We just sold $300k+ in 60 days with @Pretty Prompt through a lifetime deal on AppSumo.

This shows you can build a company your way.

Just wanted to say a quick thank you to everyone who checked out Cue today.

I launched this morning not expecting much. It's a tool I built over the holidays that turned from a side project into the main project I'm working on. Seeing it hit #3 (so far) is honestly surreal.

It s the third week of working on my little side project, SimploMail.com, and to speed things up I ve been doing a lot of vibe coding. It s been fun, but a few things became obvious pretty quickly.
I stopped using the auto model setting in the IDE. When it silently switches models, the quality drops fast. I can feel when the agent all of a sudden looses its intelligence . So now I just pick one model I trust and stick with it.
I also try to keep each AI session focused on one small task. One feature, one change. After it writes the code, I go through everything myself. I check for hard coded config, make sure it didn't quietly delete a unit test to make something compile, and etc. Sometimes it does update unit test just to make it pass .
And I never commit without reviewing. The AI is helpful, but it can also remove something important without telling you. I've seen it happen enough times now .

We won t pretend that the world isn t tense, because relations between countries are increasingly strained. (Coming from a country that never had technological or numerical superiority, we ve mostly become just part of the regime.)

But not everyone is on the same page, and countries are investing in defence.

As users, we all want to try a product before committing. As builders, we want to show real value without over-engineering and investing time 'just for show'. Finding that balance is harder than it looks.

I just shipped my demo for Rewo (https://rewo.app), and intentionally went with a live, real demo:

• Fully functional product (same codebase as prod)

• Uses demo data instead of real integrations

• Some interfacing + sync pieces are disabled

• Auto-resets on a schedule so anyone can jump in fresh

I've been talking to dozens of PMs over the last few weeks who prototype with Lovable, Bolt, Figma Make, V0, etc. Same frustrations keep surfacing.

• Output looks a bit generic: looks like a demo, not your actual product

• Context loss: explain your product in ChatGPT/Claude, then re-explain in Lovable, then again somewhere else

• No edge case thinking: AI executes prompts literally, doesn't challenge or expand on them

The core issue I keep seeing: these tools are interface builders. They're great when you already know exactly what to build. But the hard part, thinking through the flows, the states, the edge cases, where users will actually get stuck, that's still entirely on you.

I work closely with product and growth teams, and one challenge I keep running into is explaining user drop-offs to people who aren t deep into analytics.

The data usually shows where users leave, but turning that into a clear, confident explanation without overloading dashboards or making assumptions can be tough. Especially when the audience is leadership or business stakeholders.

I m curious how others handle this in practice:

I ve been experimenting with a CLI workflow that removes the most annoying part of AI-assisted dev:
re-explaining context every single time.

Instead of prompts like:

Integrate Stripe payment gateway with X, Y, Z

I just run:

This is one of those founder nightmares nobody talks about until it happens.

You've spent 6 months building. Things are moving, but not fast enough for one of you. Your co-founder comes to you with "the new idea" completely different direction.

You believe in the current vision. They're losing faith.

I am seeing this with Lovable, Verdent, Replit: I am clear, RAG my prompts, clean them with Claude Opus 4.6, find that with tough problems, they'll tell me something is fixed or done, and it isn't. Not even close. And I'm burning costly credits, making no progress.
I'd love to learn what others are doing.
I'm building a multi-agent tool that integrates with 25+ LCNC sites and also IDEs, and yes, there are tough problems with the tool's awareness of what a user is doing in a console or fields in a browser window. I'd apprecaite it if the nocode platform simplay told me, "no can do," rather than trying one thing after another, staying stuck, and costling me $100 or more per day to keep failing.
Thanks, in advance, for your suggestions!

I've always been a B2C founder. I've built an app to 100k+ MAU and sold it to a major company. I'm now building a tool called Modu.io to help businesses collect user feedback, taking directly from my own struggles (I got so frustrated with existing tools that I ended up using a single Google form).

I'm not particularly suffering the switch on the building side, I'm actually enjoying it since I'm more interested in using this tool myself, than I was with the B2C one. What I'm finding myself (sort of) uncomfortable at is the distribution/marketing side. I've launched on a bunch of ProductHunt like websites, ended up first on Uneed yesterday (didn't get much traffic-wise honestly), and bought a couple features on some of them as they were relatively cheap.

LinkedIn officially shared the job titles that started appearing more often, and with the rise of AI, the market is restructuring.

The actual top 10 roles that have seen the biggest rise in listings (in the U.S.) are:

1. AI engineers Engineers developing and implementing AI models that perform complex tasks

2. AI consultants and strategists - Helping organisations plan and implement AI technologies to improve operations

3. New home sales specialists Which sounds like a rebranding or real estate agent

4. Data annotators Labelling and reviewing data for AI projects

5. AI/ML researchers Designing new AI models and systems

6. Healthcare reimbursement specialists Ensuring healthcare providers are getting correct and timely payments

7. Strategic advisors and independent consultants Which seems like a pretty broad-ranging segment

8. Advertising sales specialists You re reading a marketing blog, I assume you know this one

9. Founders Not sure this can be listed as a job title in itself, but LinkedIn s keen to highlight how people are shifting to their own businesses

10. Sales executives

For as long as software has existed, the user has been a person. Someone sitting at a desk, poking at a phone, or calling an API. That assumption was so obvious it was never really a design principle, it was just common sense. Every decision about hierarchy, color, button placement, and error messaging was downstream of a single fact: a human being is going to see this.

With agents, that assumption is starting to fail.

When I first set up OpenClaw, I ran into a big problem immediately.

I spent $250 on my first day doing what felt like harmless testing.

Nothing production. No customers. Just me trying things like:

• Summarize this Slack thread

• Give me a morning digest

• Explain this error log

• Pull action items from the last N messages

• A couple Telegram alerts

Hey PH community!

I ve been spending a lot of time thinking about how people actually work with prompts while building a tool in this space, and I realized I have way more questions than answers.

A few I d love to throw out:

So this happened and I'm still processing it lol

We've been launching stuff on Product Hunt since last year, and like everyone else, I hit up old friends asking for support. You know how it goes.

Anyway, I met up with a few of them recently and they started thanking me. I'm sitting there thinking "aw that's sweet, they liked our product!"

But nope. They were thanking me for introducing them to Product Hunt itself. Apparently they've been addicted to it ever since, checking it daily for new AI tools.

Hey Product Hunters!

When my wife Noa and I heard that MTV was officially shutting down, it felt like the end of an era. As 90s kids, we missed that specific "linear" experience the joy of just turning on the TV and being surprised by a music video without an algorithm getting in the way.

We launched a product on Product Hunt today. It didn t go viral, and that s okay. We re treating it as a chance to ask something we all face:

When you ship something and almost nobody seems to care, how do you handle it?

• How do you keep from going down the rabbit hole? And how do you separate the product s not good enough from nobody s seen it yet ?

Over the last year, I ve been experimenting more with local-first patterns , apps that prioritize offline functionality and sync later instead of depending on constant server calls.

What used to feel experimental now feels surprisingly stable. Faster UI, fewer loading states, and a smoother user experience overall.

I rebuilt a small side project recently with a local-first approach, and the difference in responsiveness was noticeable. But it also introduced new challenges around conflict resolution and state consistency.

It makes me wonder:

China's new top paid app doesn't help you find a ride, order food, or socialize with friends. It just asks you whether you're alive.

The app, which translates to "Are You Dead Yet?" the presence of the "yet" suggests the developer probably isn't on the Bryan Johnson "don't die" train...yet) requires you to log in daily and click a button to show you're alive. Miss two days in a row and the app will notify your emergency contact. That's it. That's the app.