We measured something today that I had never thought to look for, and I suspect most teams are not looking for it either.

Two of our customer sites, one a mechanical keyboard store and one a perfume store, came back after their containers were recreated. For roughly 30 to 60 seconds, both of them served exactly the same page. Not a similar page. Byte for byte identical, 281475 bytes on each. The title tag carried the name of a third brand entirely, and the canonical tag pointed at a localhost address on port 3000.

For two years I forced myself to publish a brand new article every single Tuesday. I was exhausted. My organic traffic was completely flat despite having over a hundred posts on the site.

I looked at our analytics. Noticed that almost all our search traffic came from just five old articles. The rest of the content was sitting on page four of Google entirely ignored because it was outdated and lacked depth. I realized publishing volume was hurting my quality.

I stopped writing content for an entire month and focused only on those underperforming posts. I combined articles into massive guides updated old statistics from 2022 and added fresh screenshots from our current software version.

That simple cleanup effort boosted our site traffic by sixty percent in just forty days. Google clearly prefers an updated highly relevant page over a brand new post with zero domain authority.

I m currently working on a consumer mobile product aimed at a very specific blue-collar audience in the U.S.

One thing I m finding difficult is figuring out which acquisition channels are actually worth testing first.

For niche audiences like trucking, construction, logistics, field services, etc., do you think it s better to start with:

• short-form organic content

• niche communities

• creators/influencers

• referrals

• paid social

• search

Apple is now nudging people still on iOS 26 to move to iOS 27, and the 27.2 betas are already out. Every cycle like this makes me rethink the minimum OS question for a first release. I've found that supporting only the last two major versions keeps testing sane and lets you use newer APIs without workarounds. On Android it's messier, since a lot of real users sit on older devices for years, especially outside the US. If you're shipping a v1 on both platforms soon, where are you drawing the line? Do you check your target audience's device data first, or just pick a floor and adjust after launch?

We once added a new permission to our extension and saw a massive drop in user count afterward. It could have been optional, but we made it required. That s something I d do differently now.

It got me thinking about what people check before giving an extension access to their browser. A useful feature might get your attention, but how much do permissions influence the decision?

Have you ever been ready to install an extension, then changed your mind? What put you off?

Whenever I search for a skill.MD file for a relevant skill there are tons of Github repositories that I find and none of them actually become useful to me because most of them have AI slop and actual hardcoded instruction which is necessary is somewhere buried in line 12 or 13 and the plug-in comes with a bunch of more files which I can swear I have never read.
What is the best way to share a skill that can be plugged to agentic workflows? And is anybody monetising this already?
With most of the skills that I find online, there is no true sense of ownership and most of them lack authenticity!!

In the course of six weeks of the launch i handled all support communications for an invoicing application i developed for freelance photographers personally. No automation, not templates. I was expecting bug reports. Instead I was provided with a blueprint where my product confuses its customers.
Three emails deserve mentioning. One of them was asking about the location of the "send reminder" button it was on a page where users never logged in.Another email made assumptions that deposits and the final payment were interchangeable as my label system had the word to describe these notions.. Finally there was a brief "thank you note" from the wedding photographer, from Cebu stating that the PDF document he received looks exactly like it was generated by his studio. This one was immediately. Hanged to my desk.
The analytical tools showed that users were leaving the dashboard. The emails explained the reasons of doing. As a result I ve repositioned the "reminder" button. Separated these two labels. Repeat questions disappeared within a week.

Now I am curious how far this signal goes. When did you stop answering every communication and what replaced it?

When I started I thought every problem needed an immediate fix. If users complained about something I d jump on it. If growth slowed down I d try something new. If a process felt messy I d try to rebuild it. But sometimes the better move was to leave it alone for a while. A few problems fixed themselves as the product changed while others turned out to be problems I was creating by overthinking them. How do you decide when a problem actually needs your attention and when it s better to just leave it alone?

When we started, our app was super simple. People logged in did what they came for in seconds and signups were high.

Then we tried to make everyone happy by adding tons of settings and custom options. instead of making the app better it just confused new users and brought in endless bugs.

About eighteen months into our product, we hit a wall that wasn't a feature problem. Every new thing we shipped took roughly three times longer than the last comparable one. Bug fixes kept reopening. Two engineers had built quiet, undocumented workarounds around the same broken assumption in our data model, and neither knew the other had done it.

The obvious answer was a rewrite. We didn't do it not immediately. We spent a month arguing about it instead, which in hindsight was the most useful month we spent that year, because it forced us to name the actual problem: it wasn't the codebase. It was one early decision about how we modeled user accounts that everything else had been built to work around.

We ended up doing a partial rebuild. Roughly 40% of the code, the part that touched that assumption. Took four months instead of the fourteen a full rewrite would have taken. Shipping slowed but never stopped.

I still don't know if that was the right call. A full rewrite might have cleared out debt we're still paying for. Or it might have killed us the graveyard of startups that spent a year rebuilding while a competitor shipped is not small.