Skene gives vibe coders a direct line from product to purchase – no sales team, no PLG delays, just automated conversion built in.
ENTRY ANGLES
AI-powered product recommendation layer added to existing fulfillment platforms · Automatic sample product insertion into orders to drive repeat purchases · Revenue growth feature integrated into order fulfillment workflows
VERTICALS
CAPABILITIES
AI/ML for purchase history analysis and product recommendation, Integration with fulfillment and order management systems, Customer behavior prediction and analytics
Skene argues that this classic PLG recipe is already going stale – because today, a product can take users all the way to purchase without any human salespeople involved at all. If you plug Skene's platform in, that is.
Skene is also targeting a new audience: "vibe coders" – solo founders and tiny teams building products with AI-native coding platforms like Bolt, v0, Cursor, and their ilk.
The distinction matters. Enterprise software companies will always have dedicated engineers and a sales team working a CRM, converting every contact through sheer persistence. But indie founders aren't doing PLG because they've read the playbook – they're doing it because they have no other choice. They can't afford a sales team. They just need to convert whoever stumbles across their product.
These builders need not just a vibe-coding platform but a "vibe PLG" platform – a lightweight, no-salesperson version of PLG that doesn't require headcount.
That's exactly what Skene is building. The platform works as follows:
- Skene's AI engine reads the product's codebase and documentation, identifying the code sections that relate to user behavior.
- It treats those sections as signals, then auto-generates new code – growth loops – designed to improve onboarding, automate user activation, and surface timely upgrade or upsell prompts.
- As developers ship new versions, the AI keeps the growth loops updated, so they stay relevant to each new iteration of the product.
Skene is still early. The full v1 platform is slated for release this spring. Right now the product includes:
- An onboarding widget that walks users step-by-step from registration to first meaningful action.
- An analytics module showing how users move through onboarding – both in aggregate and at the individual level.
- An AI assistant that answers specific questions about onboarding, activation, and retention – not in the abstract, but for your actual product, since it has read your code and usage data.
The platform ships in two flavors: a self-hosted open-source version the developer installs and maintains, and a cloud version hosted by Skene that scales with load.
The paid cloud plan is nominally €10 per month per product – but that's somewhat misleading, because AI feature usage requires purchasing additional tokens from Skene on top of the base fee.
Skene is based in Finland. The startup just raised its first €800K – funding it will use to ship v1 and push toward €1M in annualized revenue by mid-year.
Every developer dreams of building a product that sells itself. In its most naive form, that dream imagines a product so brilliant it needs no marketing, no sales team, no outreach at all.
That version of the dream is almost certainly unachievable. But there's a more realistic path: building the product itself into the front end of the sales funnel – so that selling starts with using.
This is the idea behind Product-Led Growth (PLG). The model works in three stages:
The model works in three stages. Developers release a free trial or limited version as broadly as possible – getting the product into as many hands as it can reach. During that free period, the platform collects behavioral data: who used what, how often, what they were trying to accomplish. Then the sales team reaches out selectively – pitching the paid version or add-on modules to the segments that showed the strongest intent.
The real play here is that users effectively self-identify as buyers. They show you who needs the product and what problem they're trying to solve – which makes every downstream sales conversation faster and far more targeted.
For this to work, developers need to instrument their product with behavioral signals upfront, so that by the time the sales team reaches out, they're working from actual evidence rather than guesswork.
In short: the product does the first few steps of selling itself, delivering a warm, pre-qualified pipeline. But a human sales team still has to close the deal.
Skene's current tagline is: "Stop adding features. Start adding growth."
At its core, that's the PLG pitch in general. What's worth noting is how broadly that concept can apply across very different industries. Here's one example.
Swish ([related review](/review/otlichnaja-fishka-v-interesnoj-nishe-na-rastushhem-rynke)) built a revenue-growth layer on top of standard grocery fulfillment platforms.
Swish's AI analyzes each customer's purchase history and automatically adds unordered items to new deliveries – so the customer can try them and, ideally, start buying them regularly. The AI first predicts which products are likely to land well, then refines its recommendations based on whether those items actually get re-ordered.
The result: every order shipped contains a built-in driver of future revenue, in the form of sample products. And it all happens automatically – no extra work required from store staff.
What could you add to your product or platform – not just as a feature that expands functionality, but as a direct, immediate driver of revenue growth?