TL;DR: Wire AI is live and early access is open. It's an AI-native growth engineer for mobile apps: your React Native app embeds an SDK, a LangGraph backend decides what to ask each user next, and deterministic code owns the routing while the model only generates content. On one live app, activation went from 69% to 93%. 15 early-access seats, 3 taken, free and installed by hand.
This article is part of my Code Meet AI newsletter: https://codemeetai.substack.com
Wire AI is live today, and early access is open.
It's the AI-native growth engineer for mobile apps: AI that replaces your growth team. It runs four versions of every step of your users' journey, live at once, and keeps what makes them stay.
On the first app it ran on, activation went from 69% to 93%.
15 seats. 3 are already gone. Free, installed by me personally, and there's no price attached because I haven't set one yet.
Below: what it does, what already shipped, what's still rough, and how to claim one of the 12 that are left.
How it works
Your users' journey has stages. They onboard, they get a plan, they hit their first real win, they get asked for a review. Wire AI runs four versions of each of those stages, live, at the same time. Users are assigned to a version and stay in it, the funnel says which version keeps more of them, and the winner gets promoted.
Then the part a testing tool doesn't do. Every finished journey feeds back in: Wire reads what happened and writes a sharper variant for the next round.
It isn't a dashboard that tells you to go run a test. It's the loop, already running.
What that looks like in your codebase
Your React Native app embeds a small SDK. When a user opens the app, the SDK talks to a backend I run, and that backend decides, one screen at a time, what to ask that specific person next. It renders as native cards. Not a webview, not a chat window bolted onto your product.
At the end it hands your app a structured plan you can save and act on, and every step streams into a funnel you can read.
So instead of writing an onboarding once and guessing for the next two years, you write a config and the AI runs it.
The part that makes it work is boring on purpose. Deterministic code controls the flow and the model only generates content. Routing is a pure function of where the session is, how many questions are left, whether the user is bailing, so the whole flow is testable without a model in the loop.
The AI writes the next question, grounded in every answer the person already gave, and writes the final plan. Everything it emits gets validated against a fixed vocabulary of components before it's allowed anywhere near a screen.
That's the difference between a generative UI demo and something you can put in front of paying users. Most AI UI demos let the model draw whatever it wants and hope. This one gives the model a small, checked job and keeps the state machine in code where it belongs.
What that gets you
A journey that adapts per user. The static onboarding asks everybody the same seven questions in the same order. Wire AI asks what follows from what the person just said, stops when it has enough, and skips what it can already infer.
Experiments that run without you. A/B/C/D variants across the journey, five stages, four arms, twenty combinations, without anybody sitting in a meeting deciding which to try next. This is the direction the product is built toward and I'll be straight about where it sits today, further down.
A funnel you can actually read. Completion, drop by step, time per screen, and the transcript of any individual session so you can read exactly what the AI asked and what the person answered. Most apps at this stage are guessing about where users give up.
You find out who your users actually are. Wire AI reads every session and hands you the patterns: what people came for, which question makes them hesitate, which wording converts. Most founders are still running on a persona doc written before launch.
Our pilot client, and what actually happened
I can't name the app, that's a client boundary I hold. What I can tell you is what it does: it helps people find spots to hang out. Live React Native app, real users, and an onboarding people were quietly dropping out of.
Here's the run, in the order it happened.
We started with an experiment, not a redesign. Three versions of the onboarding running live at the same time, users assigned stickily so nobody got a different flow on their second open, every version chasing the same goal event. Nobody sat in a room deciding which one was better.
The first read was wrong, and the loop is what caught it. One arm came back looking like a 17 point winner. At around fifty sessions that feels like a result, and it's exactly the moment a human growth team ships it and builds the next quarter on top. At scale it was worth about three and a half points. Mostly noise wearing a nice hat.
The version that actually won was the short one. The deep, thorough discovery flow lost to a fast one of about eight screens. On a flow with no real leak in it, where every individual question converts in the high nineties, length turned out to be the only lever that moved anything.
Then the part I didn't expect: we found out who the users actually were. The product context we had written assumed one kind of person, someone new to the city looking for places. The answers said something else. Younger, local, born there, social, budget conscious. My actual reaction, reading the answers: wait, these people already live here. We had spent months onboarding a user who didn't exist.
So we rewrote the messaging to the real one. New product context, questions rewritten for the person who actually shows up, one question cut completely because it was seasonal noise nobody cared about, and a guard added so the AI stops asking the same thing twice in different words.
Three learning loops in, activation had gone from 69% to 93%, and the first movement showed up inside the first week of running live.
Two honest caveats on that number, because it's the one people will quote. It's activation on one app, in one category, over one window, so it isn't a portfolio of case studies and I won't dress it up as one.
And the winning arm's completion rate moved by about thirteen points between generations of the experiment, which is a reminder that you read these numbers per run, never all-time. That lesson cost me a re-read of my own dashboard.
What already shipped
Not a landing page and a waitlist. These pieces exist and run.
The SDK is open source.
wireai-rnon npm, MIT licensed, eleven built in components with validated schemas, six adapters for different model providers. Swapping providers is one environment variable, so you're not married to whoever is winning this quarter.The transport is an open standard. The device and the backend speak Google's A2A over JSON-RPC 2.0, the same contract implemented on both ends. That's how a Python agent graph ends up driving a native React Native screen. One call, one turn, one card.
The backend is a real service. Python, FastAPI, LangGraph. Multi tenant, per app keys with scoped access, session state living outside the process so it scales sideways, data in
eu-central-1because GDPR isn't a Q3 problem.There's a console. Register an app, edit the config without cutting a release, read the funnel, open any session and read the transcript.
It's tested like something people depend on. The drop in kit runs 630 tests on every merge, and the agent routing has its own eval suite with an accuracy gate, so "the agent got worse" shows up as a failing build instead of a feeling.
First card lands in about 130 milliseconds, against roughly three and a half seconds when I started. Onboarding is the one screen where a spinner costs you the user permanently.
What a seat gets you
If Wire AI doesn't lift your activation, you've paid nothing and you still keep the teardown.
That's the deal in one sentence. Here's everything inside it.
The Activation Teardown, before you commit to anything. I put your existing onboarding through the analysis and send you a report: where people drop, which step leaks, what I would change first and why. It's yours whether you take a seat or walk away, and you don't need to install a single line of code to get it.
The install, done by me, by hand. Up to four hours on a call, in your codebase, together. Not a docs link and good luck. This is the part that doesn't scale, and it's exactly why there are 15 seats and not 500.
Your bugs jump the queue. When you hit something broken, and you will, it gets fixed that day instead of queueing behind everything else. That stops being possible the moment this cohort is full.
A direct line to the roadmap. What gets built next is what early-access apps need next. At this stage that isn't landing-page language, it's just how the queue works, because there is nobody in front of you.
Analytics free to 1 million events a month. Any app, not only early access, and it doesn't expire when the beta does.
No price, and that's deliberate. I'm not deciding what Wire AI costs until early access tells me what it's worth, so nobody in these 15 seats gets priced by a guess.
What I want back
One thing: the truth, while you use it.
When a question the AI asks is stupid, say so. When the console confuses you, say so. When a number looks wrong, say so, and that one is worth more to me than any testimonial you could write.
That's the whole trade. You get the teardown, the install, the queue and the roadmap line. I get the thing I can't buy, which is honest reactions from a real app with real users in it.
If it isn't you, it might be someone you know
All three seats that are gone came warm. Somebody knew somebody. Not one came from a cold email, and I have sent a lot of cold emails, so I've stopped pretending that's the channel.
So if your own app doesn't fit but a name came to mind while you were reading, that's the ask. Forward this to them, or drop the name in a comment and I'll reach out and tell them you sent me.
Anyone arriving through a referral skips the queue and goes straight to a call. And I'll run the Activation Teardown on your app too, even if you never install anything.
Before you say yes, two things you should know
Only the onboarding stage is live and proven. The journey wide experimentation I described up there is the roadmap, not a shipped feature. I'd rather you hear that now than find it out in week two.
I have an open number I can't explain yet. This week my own dashboard read 23% completion on an app that had been finishing north of ninety. I spent a morning on it and I still don't have a clean answer. Best guess is the dashboard, there are two honest ways to compute a completion rate and my headline tile looks like it's reading the wrong one, but I haven't proven it and I'm not going to pretend I have.
Both of those are in a launch post on purpose. The product is deliberately incomplete at this stage, and the fastest way to harden it is with a few real apps inside it rather than a year of me polishing it alone. If that reads as a red flag, this isn't the right moment for you and that's a fair call.
Who this is for
You're a fit if you have a React Native or Expo app that's live, with real users going through an onboarding right now, and you're a solo founder or a tiny team where the person who feels the activation problem is also the person who decides.
It helps if your app already has AI or personalization in it, because then I don't have to sell you the idea and we can go straight to the mechanics.
You're not a fit if you already have a growth team running experiments every week. Genuinely. A larger company passed on this recently for exactly that reason and they were right to. The value here is removing a person from a loop you don't have. If you have the person, you don't need me.
Pre launch is also a bad fit, and I say that with some regret because those are usually the most fun conversations. Without traffic there's nothing for the loop to learn from.
How to claim a seat
Reply to this email. That's the whole process, there's no form and no demo request.
Tell me what your app does and roughly how many people go through onboarding in a week. Two sentences is plenty. If it's a fit I'll send you a time this week. If it isn't, I'll tell you straight instead of quietly moving you into a nurture sequence.
Not sure you qualify? Ask for the teardown anyway. Worst case, you get a report on your own funnel and we both move on.
12 seats left of 15. The cap is real, because the install is manual and I'm the one doing it.
How I make this
I draft with AI. I've written about my workflow more than once and it'd be strange to hide it here. The receipts, the numbers, the decisions and the opinions are mine, the sentences get a drafting partner and then a lot of editing from me. If that disqualifies me for you, fair enough. If it interests you, that's most of what this newsletter is about.
I'm Malik, 9 years building mobile apps, React Native and Expo. I write Code Meet AI, where I show what I'm building with AI and what it costs me. Wire AI lives at getwireai.com, and the SDK is open source.
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