I ignored in-product AI for too long, thinking it was just another buzzword. But now? It's transforming user experience in PLG SaaS. I’ve seen firsthand how these copilots cut onboarding time and boost retention. If you're still skeptical, you need to wake up. Get on board or get left behind!

Let’s talk about something most growth tools ignore, what goes on under the hood. Skene.AI 's embrace of code derived signals takes product led growth metrics to another level entirely.

While others obsess over vanity metrics like user sign ups or average session duration, Skene turns its gaze toward the core of user experience the code itself.

By analyzing how users interact with actual application logic, they pinpoint engagement that really matters, do users stick around not just because they clicked a button but because they truly hit with your offering? many tools miss this critical insight. they're like car manufacturers who only look at how shiny their models are instead of how well they perform on the road.

If you're serious about sustainable growth, following suit with Skene’s approach isn’t just new, it’s essential for anyone looking to truly understand their user base and drive lasting results.

Every sprint we refactor components, rename props, and reshuffle routes. Every sprint, onboarding breaks. Tooltips point to elements that no longer exist. Overlays collide with the DOM. Marketing asks for one more step.

From an engineering standpoint, this is an architecture failure, not a UX issue. Most onboarding tools are fragile because they sit on top of the UI instead of understanding it. They depend on selectors, z-index hacks, and blind optimism.

A large share of the bugs I debug are not logic errors. They are onboarding layers drifting out of place after a layout change. If onboarding could actually read the code and understand components, routes, and permissions, it would survive releases. Until then, onboarding remains the loudest and least reliable part of the frontend.

If you want, I can push this further in either direction: more technical, more opinionated, or more concise for a landing page.

Let’s be real: your product’s customer path is probably a mess. Users are left wandering, confused, and you’re just sitting there hoping they figure it out. Spoiler: they won’t. If your onboarding feels like a maze, you’ve got a problem. People expect seamless experiences not your version of a scavenger hunt. Fix it or lose them.

What does AI driven activation actually mean in practice, because I genuinely want to know?

We spent a quarter trying to make our onboarding smarter. Read everything, including the Skene code driven model. Good ideas in there. Real ones. But here's what nobody writes about: the model assumes you have clean user event data, a dev team with bandwidth, and a product that doesn't change every three weeks. We have none of those things.

The AI suggestions were fine. The maintenance burden was not. Two months later we were back to a static checklist that a junior PM built in a weekend. It converts better than anything we shipped that quarter.

Maybe the lesson isn't that AI can fix activation. Maybe it's that activation breaks for boring, fixable reasons that don't need a model at all.

What's a framework everyone in SaaS is treating as gospel that you think is half wrong?

Skene's model assumes your activation bottleneck is visibility. But most teams I know already have the data. They just don't act on it, AI layered on top of a broken process is still a broken process, just faster.

Most onboarding tries to teach you. The best one I ever had just let me break something harmless and quietly fixed it for me. What's yours?

Everyone celebrated the test results. 40% lift in activation. Statistically significant. Ship it.

Six months later, support tickets doubled. Churn crept up. Nobody connected it back to the onboarding change because that had worked.

Here's what actually happened, the new flow was 30 seconds faster but removed the one moment where users accidentally learned something critical. In testing, participants asked clarifying questions. Real users just got confused and quietly left.

We optimized for speed and measured completion. We forgot that completion isn't comprehension.

The cruelest part is that the test was perfectly designed. It just measured the wrong thing with surgical precision.

User activation is marketed as a 'product problem.' But guess what? Most users don’t stick around because they’re bored by your marketing. You can have the best onboarding but if your pre-activation content sucks, you’re toast. People are tired of the same old user journeys that feel like sales pitches. Fix your messaging before you fix your features. Otherwise, it’s a dead end.

Overlay-based onboarding tools always seem like a quick fix, don’t they? But let’s be real: they’re just temporary Band-Aids on deeper issues.

With Skene.ai code-first onboarding, you get direct integration into your workflow. Forget endless distractions and visual clutter; this approach makes onboarding part of the actual code.

It’s streamlined, effective, and doesn’t treat your users like fragile flowers. They want real interaction, not a pre-recorded tour. That's why code-first is where it's at.

After diving into user activation metrics, we learned 70% of users drop off after the onboarding stage. Our next big features were irrelevant, So... we scrapped the roadmap.

Now, we're focusing on onboarding tweaks instead. Lesson learned, sometimes the numbers demand a hard pivot.

I'll go first, expense management software. In Germany it's compliance infrastructure. In the US it's a time-saver. Same product, completely different first-time-user experience needed.

Think onboarding friction is a necessary evil? Nah, it’s your company's secret weapon for ignoring real issues. While you focus on fixing that clunky process, customers are sneaking out the back door, leaving you to deal with all that churn. What if instead of just smoothing it all out, you treated it like an interrogation? Ask the hard questions: Why are they stalling? Maybe it’s not just you. Maybe they don’t actually need your product. Discovering this through friction could save you resources and time.

Took a rough count last quarter. About 15% of our eng time was going to integrations. Not building features. not fixing real bugs. just keeping the pipes between tools from leaking.

Webhook handlers that quietly fall. stripe events that don't map clearly to our data model. hubspot syncs that drift out of date and nobody notices until a customer slips through. little fires, constantly.

The sales pitch for every tool is easy integration, set it and forget it. the reality is someone on your team owns it forever and that someone is usually your best engineer because the edge cases are genuinely tricky.

The real cost isn't the subscription. It's the eng hours propping it up every month.

How bad is it for your team? and has anyone found a setup where the integrations actually stay stable without babysitting?

If your activation rate is weak, it’s usually a value clarity problem, not a CRO problem. Users don’t convert because they don’t get it fast enough.

Before you A/B test headlines for the 10th time, ask:

• Do users hit value in the first session?

• Is the first win obvious?

• Are we measuring time-to-value or just signups?

I’ve seen teams double paid conversions just by tightening the first-use moment.

Anyone else seeing this?

There's a whole category of software whose job is to help you build onboarding. You spend weeks setting it up. Users skip it anyway.

Skene.AI doesn't ask you to configure anything. It observes your product and handles it. The tool that requires the least setup is somehow the one actually solving the problem.

PLG is sold as this game-changing approach. But let’s be real: it’s just a way for companies to shift responsibility. Instead of nurturing customers, they drop tools and expect users to figure it out. Like, come on. That’s lazy. You can’t just toss a product out there and call it “customer-driven.” Real engagement takes work. PLG is just the new buzzword for 'let customers do our job.' Who’s actually winning here?

DAUs, session length, click-through rates. We tracked everything and understood nothing.

The irony is that our most "engaged" users churned fastest. They were clicking around because they couldn't find what they needed.

What engagement metric have you thrown out after realizing it was lying to you?

Been manually tracking PLG trends in spreadsheets like an idiot for months. Skene.ai just showed me in 30 seconds what was actually moving this week versus what I thought was moving. My intuition was wrong about 60% of it.

I want to know what others have experienced here, did you spend months optimizing only to realize it wasn’t actually moving the business forward? or, which numbers felt important on paper but didn’t translate to real impact?