The state has become the first U.S. state to regulate AI companion chatbots. Governor Gavin Newsom signed SB 243, a new law requiring companies like OpenAI, Meta, Character AI, and Replika to implement safety protocols protecting children and vulnerable users.
Notion, Obsidian, and Roam are great, but they re not for everyone. Maybe you found something simpler, faster, or just less overwhelming. What s the one productivity tool you actually stick with the one that makes life easier instead of adding more work?
We use AI to improve something in the process (mostly to speed up the process).
But whenever I see and suspect that something is generated by LLMs, I feel that the person on the other side has slopped it a bit (and subconsciously I perceive it as "something less").
Credits look like a solution to variable cost. They're really a way of moving the variance onto the user without telling them.
In Arteza a quick edit and a full multi shot render are about 12x apart in what they cost us to run. Both are priced in the same unit. So someone learns an exchange rate from the cheap action, builds a mental model, then spends a third of their balance in one click and feels robbed. That isn't a pricing bug. We asked them to hold a cost model in their head that we never showed them.
What's worked is putting the credit cost on the button before the click instead of in a docs table. Boring fix, and it cut the where did my credits go messages more than any price change we made.
The part I haven't solved is failures. A bad output still burned the compute. Refund it and people retry until they like the result. Don't refund and credits feel like a slot machine. We refund and eat it, which won't scale.
For 3 months I shared weekly progress updates publicly. Numbers, learnings, screenshots, full transparency. Then I noticed something: I was choosing what to build based on what would look good in the update not what users needed. "Impressive" features got priority over "useful" ones and a dashboard screenshot performed better than a boring fix that actually mattered.
I stopped posting metrics publicly after that. The transparency didn't keep me honest it made me perform.
So for those who build in public: have you caught yourself optimizing for the audience instead of the user? And the harder question: if you removed the audience tomorrow would you still build the same things?
Our first Product Hunt launch didn t go well. We put something out there, pushed for votes, and hoped for the best. It didn t work.
For our relaunch, we took a completely different approach. Here s what changed:
Engage, don t just post. We spent weeks commenting on other launches, supporting makers, and building trust. This time, people recognized us, not just the product.
Conversations > upvotes. What made the difference were detailed comments and feedback. The algorithm rewards authentic engagement.
Storytelling > specs. Instead of listing features, we shared why we built it and the problem it solved.
Timing is everything. Launching at midnight PST gave us momentum when the U.S. audience woke up.
Expectation reset. PH is less a sales channel, more a credibility engine. The real ROI shows up later, in awareness, trust, and partnerships.
What stood out the most: The community. The honest feedback, encouragement, and tough questions shaped our roadmap more than any internal discussion could.
Nico s thread this week (green tests, 5.5 hours down) reminded me of a smaller version of the same problem on the B2B AI product I manage.
The scene: a data preparation job finishes and the row turns green with Completed . The customer reads that as checked and safe to use . It means ran without errors . Weeks later someone asks why a model was trained on a version nobody signed off on, and the status page says everything was fine.
