Upvotes are great, but what other metrics or outcomes do you consider when evaluating your Product Hunt launch? Let s discuss different ways to gauge success.
I shipped something last month. Worked on it for weeks. Launched it. Felt the relief of being done.
And then I completely forgot about it. Not on purpose. It just stopped occupying space in my head. Someone asked about it a few days later and I had to remember what they were talking about.
As Makers, we're constantly juggling product builds, user feedback, marketing, and bug fixes. Time seems to vanish in an instant. Over the past year, I ve found that sometimes it's not a grand strategy or overhaul that makes the difference, but rather one game-changing tool that quietly handles the busywork.
For me, a standout has been Fathom, an AI-powered tool that transcribes meetings and automatically delivers highlight summaries. No more scrambling for bullets during calls, no more post-call backlog. It s saved me hours each week. In fact, users combining tools like Fathom, ChatGPT, Asana, and Zapier have reported reclaiming 20+ hours per week by streamlining writing, research, and task automation.
I keep getting feature requests from people who want to use the product in a way I never intended. Not better versions of what it does completely different jobs. They want it to be more configurable, more customizable, more "just give me the building blocks and I'll figure it out."
Part of me wants to say yes to all of it. Flexibility widens the market, makes the product valuable to more people, and means I never have to turn a customer away. The more it can do, the harder it is to outgrow.
Some product categories are naturally fun to talk about (AI video, dev tools, design tools, consumer apps). People understand the product and get excited pretty quickly.
But then there are categories that are important, useful, and valuable, but historically kind of boring. Things like analytics, internal tools, compliance, finance, HR software, etc.
We keep a human in the loop for safety. It s the standard line during demos, and on paper, it makes total sense.
But in practice, human review quickly becomes the bottleneck. If someone has to check every step or approve every small update, the speed advantage vanishes. Worse, alert fatigue sets in people stop reading traces and just start blindly clicking "Approve."
When evaluating HITL setups now, my test is simple: Can someone make a confident decision in under 3 seconds?
If reviewing takes as long as doing the task manually, the agent isn't saving time it s just turning real work into an auditing job.
Dashboards, analytics, CRMs, most of what I use is great at reporting on the past. Very few actually tell me what needs doing today. Anyone found or built something that closes that gap?
Imagine an AI that doesn t rely on giants like Google or Facebook. Decentralized AI could change the way we interact with technology, making it more private, accessible, and secure. But, is it really possible or just a crazy idea?
During the year of our business I answered all the support emails myself. It was hard. I did not like it. Looking back it was the important thing we did and I almost handed it over too soon.
Analytics showed which buttons were pressed. The inbox showed which actions users wanted. These are two types of information. One day a user wrote: "I expected the export button to send the report to my accountant." Our button saved a file. No one would have ever noticed this difference in the funnel chart;. In the next month three other users had the same issue. We added an email button. The problem went away.
Now I keep a spreadsheet with four columns. The words that the person uses the screen they were on what they were hoping for and what actually happened. Patterns start to appear after forty entries. It is important to write down the words since they will become your landing page copy and button labels.
There is a risk. Support emails are more likely to come from customers and less likely from happy quiet ones. That feature no one ever asks about could be the thing that keeps everyone coming which is why I look at the email box along with the retention numbers not instead of them.