Just yesterday I prevented my team from adding an exotic feature to our product.

My hypothesis is that people don't like many features in a product as that complicates the product adoption e.g. many sales guys hate CRMs for this reason. In that sense, more features might equate to no features as users don't adopt/use the product. So, minimalistic products that solve 1 big problem (80% of the problem pie) is what people like.

That's what I think.

I am so guilty of this. Whenever I hit a roadblock with user outreach or sales, my immediate reflex is to open up my design tool, redesign the logo for the third time, or reorganize my code structure. It feels like real work because you're busy at the keyboard but it's really just a clever way to procrastinate on the things that actually matter. It took me a while to realize that shuffling pixels doesn't bring in users.

When you catch yourself hiding behind busywork like this, how do you force yourself to close the editor and finally talk to people?

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.

Before I start, let me start: without a doubt, children should be children and enjoy their childhood.

However, many makers here already have families, and the role of founders also affects how their children perceive them (they probably see their parents as role models).

When you're running a small project, every single user feels precious so saying no to a request feels like you're actively pushing them away. I remember keeping a user waiting for ages on a custom integration because I didn't want to admit I wasn't going to build it.

They eventually stopped replying and moved to another tool. Once I started giving fast, blunt answers even when it meant losing someone my workflow got so much cleaner.

Do you try to please every early user or do you draw a hard line early on?

Currently playing around with @bolt.new after being inspired by @gabe and building a bunch of mini apps, mainly for fun. Haven't pushed any to production yet but so far I'm enjoying it bar the odd hiccup where I have to roll back a few times to fix a stubborn error.

I've also looked into @Lovable and it seems pretty cool but wanted to see what people had to say about it. Is there any reason to pick one over the other and which one have you settled on?

As a product designer, I usually start by thinking through the main user flow first.

Vibe coding makes that flow surprisingly easy to turn into something that works.

The harder part starts right after.

What happens when there s no data? What if an action fails? What should happen while something is loading? Can the user undo what they just did?

I've been having a lot of fun exploring AI and using tools like @Cursor, @bolt.new, @Lovable, and @Warp to learn how to build and make some apps for myself! I'm also noticing a tremendous amount of growth in folks creating their own apps using these same tools which has me wondering... if a company wanted to acquire someone's app or tool that was built via vibe coding, would it matter how it was built? Does the method of how it was built impact the valuation?
In my idealistic eyes, I'd like to think it doesn't. As an acquisition is often much more than just the tech but also the user base, brand, and even team behind the product. If anything I think that acquiring a product that has been "vibe coded" and putting them into capable engineering hands would only enhance the product...or a least make the code base cleaner.
I also believe that talent that is able to create stunning products with AI is currently a small percentage of folks, and that companies should be investing in acquiring that talent (either independently or via product acquisition) so that they can stay ahead in innovation while learning how to implement AI tools more efficiently in their orgs.
Very curious to hear what you all think!