Early on we built our own internal notifications, document storage and task lists. Post-monetization, churned feedback taught us a harsh lesson: users don't want another siloed app they want our core utility inside Slack, Notionor Chrome.
The hardest decision is stopping work on your own native capabilities to spend cycles building integrations for other platforms.
How do you determine when a workflow issue requires an ecosystem integration rather than an internal UI fix?
I m building a small tool that reads a company s website to find its name, description, and logo. I thought getting those details from the company s own site would be straightforward. It hasn t always been.
Some sites leave fields out or put different information in different places. My instinct is to try a sensible fallback, then be honest when the tool still can t find a reliable answer. A confident-looking guess would be easier to display, but less useful to someone relying on it.
If you build with public web data, how do you handle that moment? Where do you draw the line between a helpful fallback and a guess you shouldn t show?
I run growth for a small AI startup. When we launched a few months ago, we had a massive internal debate: do we build natively inside ChatGPT, or do we build a standalone web app and try to drive our own traffic?
We ultimately chose standalone. We wanted to own the user relationship, control the UI, and not rely on someone else's platform risk. We spent months on SEO and paid ads to get our first 2,000 users.
Then OpenAI had their DevDay announcements. Seeing that ChatGPT can now suggest an app mid-chat, run it natively, and let people sign in with their ChatGPT account completely changed the game. When you look at the stat that 1B+ people open ChatGPT every week, building a standalone app suddenly feels like setting up a lemonade stand in the middle of a desert.
Last night, two PHP security issues were revealed, CVE-2026-109618 and CVE-2026-109619. Both allowed remote code execution with no authentication needed, and they were very serious, with a vulnerability score of 9.2. Due to the extent of the impact, we found ourselves doing emergency work on client sites late that night.
What astonished people most: updating WordPress and its plugins doesn't fix it. The problem is in the PHP language itself, so the PHP on the server is what must be upgraded.
Also note that if a website is running a PHP version that's no longer supported by the PHP development team, there will be no official patch.
On client sites I often hear the same sentence a few weeks later: it worked before, what changed? Without a record, nobody can answer, not even me.
I have seen a short changelog file, a note in the project tool, and a dated list sent to the client after each visit. All of them work only if someone keeps them up to date, which is the hard part.
I review content for my project every week and last month I rejected 12 AI generated drafts. Not because they were bad, but because they were too smooth. Every paragraph was balanced, every sentence polished, nothing left unresolved.
The test I used was simple: I looked for a sentence that trailed off an opinion that might be wrong, a thought that wasn't fully closed. AI doesn't leave loose ends, humans do. That one difference gave away all 12.
So for those who review content regularly: do you have a specific signal that tells you "this is AI" before you finish reading or do you rely on gut feeling? And the harder question: if you can't explain the signal, is it actually a signal or just a bias?
