In the beginning, we focused heavily on smoothing out our signup flow, and activation rates looked great. But a few weeks in, we realized users were dropping off right after completing onboarding.

Getting users to see the initial value is one thing, but keeping them coming back to perform managing early retention: what onboarding or product changes made the biggest difference in turning initial activation into a daily or weekly habit?

I was one of those people who actually used the Touch Bar When I switched Macs, I missed having volume and brightness right under my fingers, so I tried a few trackpad shortcut apps.

That got me thinking about which gestures I d actually want to change from app to app. I d want volume to work the same way everywhere. But I could see myself using the same swipe to switch tabs in my browser and skip a song in Music.
I m curious whether that would feel natural after a few days or whether I d keep mixing them up.

If you ve set up gestures or shortcuts that change depending on the app, which ones actually stuck? Anything you ended up changing back?

This all goes back a bit to the era of NFT, virtual reality, when, during COVID, we went to virtual events, had VR glasses and promised ourselves that we would spend more time in some digital parallel reality online.

Well. So Facebook, with a growing portfolio and a new vision, renamed itself Meta.

That it would be the Metaverse.

To make our mid-tier plan appealing we included generous usage limits thinking people would upgrade once they felt the value.

Instead power users optimized their workflow just to stay right under the threshold. Once we switched to feature gated tiers instead of usage-based limits users upgraded much faster because they actually hit functional walls instead of artificial caps.

Do you find feature-gating or usage limits work better to drive tier upgrades?

We spent months building an automated product tour so users could sign up and set everything up themselves.
Drop-off rates were still brutal at step three.

Out of desperation, we removed self-serve onboarding for new accounts and forced a quick 10-minute strategy call before setup. Conversions from signup to paid went up, and churn dropped by half.

Are self-serve flows overhyped for complex tools, or is manual onboarding just a temporary bridge?

a16z published a piece last week arguing that everything at work is being recorded, and that companies who build AI on top of that context layer will win.

Compelling thesis. But it mostly frames recordings as a memory and retrieval problem. I think the more interesting question is what people are actually doing with them beyond transcripts, summaries, and action items.

I've seen teams use recordings for onboarding, async decision reviews, even as a source of truth when things go sideways. But I'm curious what's happening in practice.

A few things I'd love to discuss with the community:

It s funny how all our automated tests can pass with 100% green checks and yet a simple user action like hitting the browser's Back arrow completely breaks the app experience.

I spent hours debugging why an onboarding wizard kept dragging finished users backward because of how router pushes stack up in Next.js. Unit tests just don't catch browser level history states unless you're running heavy end-to-end browser tests.

For UI flows with multiple steps do you rely on tools like Playwright to test history behavior or is this just one of those things you catch manually by testing it yourself?

We pull job posts from a few dozen boards and company career pages, and each one is keyed on its source plus that source's own id. That works inside one source and does nothing across them: the same opening can arrive from the company's own page, an aggregator and a recruiter repost, each with a slightly different title and location line. Matching on company plus title looks obvious until you meet one company with two genuinely separate Backend Developer openings in two cities, next to one opening titled three different ways. We still haven't found a rule we trust, so for now we let duplicates leak through rather than risk merging real jobs away. If you run anything that aggregates listings, products or events from many places, which signal ended up being the one you trust for deciding two records are the same?

I would like to warn you in advance that I do not want to offend any culture or country with this post. It only demonstrates observations from my own experience.

6 months ago, I had a conversation with a friend and we got to the topic of money.

early on every request feels urgent because there are so few users. one person asks for something twice and it starts to feel like the roadmap. but a loud user and a common need look the same when you only have a handful of people talking to you. my view is the request matters less than the problem under it, and if three people describe the same problem in different words thats worth more than one person asking for the exact feature five times. curious how others draw the line. do you have a number, a rule, or is it mostly gut until you have enough users to see patterns?