Had a thought, and I must put it out here:
Over the past year, building with LLMs, I ve noticed that the big change is not necessarily that AI gives us better answers. Change your perspective and think like this: we, humans, are starting to ask better questions. And here's why:
When search engines dominated, we asked:
What is X?
How do I do Y?
Best tools for Z?
With LLMs, the questions are different:
Help me think through this decision.
Challenge my assumptions.
What am I not seeing?
Act as a product strategist and critique this.
Clarify my messy thinking.
That s not getting the information, that s cognitive augmentation.
I feel we re moving from:
Finding knowledge to extending reasoning
And this raises bigger questions for builders:
1. Are we designing AI tools that optimize for answers
or for better thinking?
2. Is the real advantage having a stronger model...
or asking better questions?
3. In a world where everyone has access to GPT-level intelligence,
does leverage come from prompting skill, system design, or taste?
4. What new human skills become valuable when execution becomes cheap?
It feels like we re entering a phase where:
Curiosity > credentials
Clarity > speed
Systems thinking > single outputs
If you re building in AI right now:
What types of questions are your users asking that they couldn t (or wouldn t) ask before?
And are you building for answers or for thinking?
Would love to hear what patterns you're seeing.
______________________
www.zackapp.space
Download Zack from the App Store and soon from Google Play: https://apps.apple.com/us/app/za...

Today we re open-sourcing the core memory engine behind @Mnexium AI: CORE-MNX.

GItHub

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?

We added two Product Hunt badges to starnus.com.
#1 Product of the Day and #4 Product of the Week.

Feels good having them there. Thanks again to everyone who supported the launch.

Most productivity tools assume the problem is organization.

But from what we ve seen while building Zack, the real friction usually happens somewhere else:

• You capture the task but don t prioritize it.

• You prioritize it but don t act.

• You act but context switches kill momentum.

• You plan but real life reshuffles everything.

So I m curious:

Ok, I don t want to brag ( ) buuuuut what if there were an app that creates tasks (like many others), but also uses LLMs to actually execute them through a behavioral, user-oriented approach?

Let me tell you how: it knows your priorities and goals. It knows your tasks and deadlines. It creates the perfect plan to help you prioritize your to-dos and mark them as done, without any headache.

And that s not all. It reads your calendar, your emails; creates tasks from the important ones, writes emails, and sends them out, all in one app.

My proud moment, guys! And shall I say that s still not all?

We built Zack around one core question: importance isn t just a deadline, so what is it?

Sometimes a task is urgent.
Sometimes it s emotionally heavy.
Sometimes it s small but blocking everything else.
Sometimes it s tied to an important email or meeting.

Most productivity tools treat all tasks the same unless you manually organize them.

I m curious, how do you personally decide what deserves attention first?

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.