I've been thinking about this a lot lately while building.

So many tools we use daily feel like they should be one product, but they're scattered across 5 different subscriptions.

I have been thinking about situations where clients specifically ask for AI agents to simplify a process. On the surface, it sounds reasonable. They want something intelligent to classify, route, or decide. But when we go deeper into the actual workflow, we often find that the logic is completely structured. It might just be routing leads based on budget, geography, or service type. In those cases, a simple if-else condition or a fetch record from a table would solve the problem cleanly.

Another common case is using AI to analyze structured form submissions. If the inputs are predefined dropdowns and checkboxes, there is nothing to interpret. A fetch record or rule-based filter is cleaner, cheaper, and easier to maintain.

So the real question is this: are we adding AI agents because they actually do the job better, faster, or more efficiently? Or are we just throwing AI into the mix because it sounds cool and everyone else is doing it?

I recently saw a marketer with 10k+ followers launch and finish 6th with 348 upvotes. They followed a proper pre-launch and post-launch plan, did everything right, and still the outcome felt unpredictable.

Now I m launching @Curatora next week.

I m not a marketer. I have a little over 1k followers. Of course, asking for support helps. But I also keep hearing that a large part of the Product Hunt community shows up mainly for their own launch, then goes quiet until the next one.

That makes me wonder: how much of success here is strategy, and how much is timing and network effect?

Lately it feels like every week there s a new AI-powered SaaS launching.

Same landing page formula.
Same promises.
Same 10x productivity pitch.

And what s interesting is the number of products keeps increasing but I m not sure demand is increasing at the same rate. It feels like we re repackaging the same value just slightly different positioning.

New UI.
Different niche angle.
Built for X .

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).

Today, I read in Techcrunch that India has an ambition to "compete" with the US and China in the startup scene:

India has updated its startup rules to better support deep tech companies in sectors like space, semiconductors, and biotech, which take longer to mature.

With the advent of clawdbots, it's as if we've all lost our inhibitions and "put our lives completely in their hands."

I'm all for delegating work, but not giving them too much personal/sensitive stuff to handle.

AI is everywhere right now - from copilots and chat assistants to analytics, research, and planning tools. But beyond the hype, I m curious about what s truly useful in day-to-day product work.

From a PM or founder perspective:

• Where has AI genuinely saved you time?

• What tasks do you trust AI with - and what do you never delegate?

• Has AI changed how you write specs, manage roadmaps, or talk to users?

• What AI use cases sounded great in theory but failed in practice?

Personally, I see a lot of potential, but also a lot of noise. I believe that in the future, AI should help us much more. Create good roadmaps, convert product specs into concrete tasks, prioritise them, assign people, push for realisation, and much more.

We ve worked in two other eco-systems (India & France), and each has clear strengths and trade-offs in terms of talent density, cost of building, access to capital, speed of decision-making, and openness to risk all vary a lot.

Curious to hear from founders and operators who ve built outside the US:

• Which ecosystem punches the most above its weight today?

• Where do you see the best balance between talent, capital, and customer access?

• Are there cities/countries that are especially strong for specific stages (0 1 vs scaling) or specific verticals (AI, fintech, climate, SaaS, deep tech)?

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:

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

Not really much, and it annoys me a bit. In exactly 14 days (28. 1.) we will launch the product, and the only thing I do is talk about it.

But yes, there are points that I still want to master by then, e.g.:

• Create an informational newsletter inviting people to follow our product page

• Create a list of people who could support us and ask them for help

• Announcements on social networks

• Inform Kickstarter backers who supported us with updates this is also an audience

• Publishing a Product Hunt badge on the landing page

• Continually grow and maintain a personal brand which should be a long-term goal, not just for launch purposes.

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?

If your launch does not go as planned, do not judge it too quickly.
Avoid the instinct to immediately add more features or pivot the product.

Instead, pause and evaluate what already exists.
Check whether the core features are clearly communicated, fully polished, and genuinely solve the intended problem.
Often, the issue is not the idea, but the execution, positioning, or user experience.

Refine what you have. Improve clarity, usability, onboarding, and messaging.
Then relaunch with focus and confidence.

Many products fail not because they were wrong, but because they were unfinished, unclear, or rushed.

Let's play a bit of Nostradamus! What are your thoughts on 2026 changes in vibecoding tools capabilities, market dominance etc?
Here is mine:
From prompt app to ideate define plan build.
The winners won t start with a random prompt. They ll start with structure: clarity, scope, flows, acceptance criteria then build.
A whole services ecosystem will form around vibecoding.
Two obvious categories:
= Make it release-ready (engineers finishing the last 20%: architecture, edge cases, compliance etc)
= GTM for the masses (hundreds of thousands of apps shipped and most builders won t know what to do next)
Also: hackathons + internal workshops inside enterprises will become the new sexy way to learn AI. The best vibecoding companies will run these as growth loops.
Enterprise will enter heavily the chat.
Big players will optimize for ENT prototyping + internal tooling, where budgets exist and good enough fast is a real superpower.
Pricing will drop (or evolve).
A real reason people leave vibecoding tools for Cursor is simple: cost (even 20/month is a friction point at scale). Expect pricing to shift in favor of users and monetization to get more creative.
Influencer-educators will become distribution.
The value of an army of consultants/influencers who teach AI via workshops will compound. A strong professional ecosystem can 100 your reach.
Micro-SaaS stories will explode.
We ll hear hundreds of mom & pop businesses doing $1 5k/month not unicorns, but real freedom businesses from non-tech people.
Mobile becomes a priority for almost everyone.
The next wave won t stop at web prototypes. People will want real mobile products.
Niche wins again.
As broad tools saturate, builders will go specialized: video-only landing pages with AI type products or what I m personally obsessed with: native iOS apps and building modaal.dev
Meanwhile, AI companies will keep shifting upmarket to bigger deals and stickier customers.
Curious what you re seeing what would you add / disagree with?

On June 14, 2023, the European Parliament officially voted to ban unpaid internships.

This honestly made me happy, because I remember how, during college, I was expected to spend a full 2 months working full-time at an advertising agency as an unpaid intern (Spoiler alert: I fought for and got some pay ), but that wasn t the norm.

Yesterday was a big day for us, and we re still processing all of it.
TinyCommand finished as #2 Product of the Day, and for a small team that s been quietly building for months, it genuinely meant a lot.
We started TinyCommand because we kept seeing the same problem everywhere, people spending more time stitching tools together than actually doing their work.
Workflows breaking silently, data scattered across apps, forms living in one place and automation in another it never felt as simple as it should be.
That s the gap we wanted to close.
Seeing so many of you understand that instantly and even share the exact struggles you face made the launch feel meaningful beyond the ranking.
Thank you for the comments, the feedback, the upvotes, and the honest conversations throughout the day.
It helped more than you know.
There s a lot ahead for TinyCommand, and yesterday gave us even more clarity on what matters next.
#AllItTakesIsATinyCommand

I just upgraded my meme generator agent on @MindPal from Nano Banana to Nano Banana Pro and the results were INSANE

Crazy how these memes were generated WITHOUT any reference images.
What have you been using Nano Banana Pro for? Share your use cases below Let's see what its limits are.

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 been building full-stack applications for about 14 years mostly with Python, a few with Node, PHP, and Ruby.

Lately, my workflow has changed drastically.

With tools like Cursor, Claude Code, Codex, and Gemini CLI, generating reliable, production-ready code has become incredibly fast. These AI coding agents don t just accelerate development they often remove the friction entirely.