Product & Growth for AI-Native SaaS
Building products that grow themselves.
I build activation, monetization, and measurement systems for AI-native and agentic B2B SaaS. Across fintech and cybersecurity, from early-stage to 10M+ daily active users.
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11+ years in product growth across AI SaaS, fintech, cybersecurity, and AdTech. Based in Tel Aviv. I build growth engines for products that scale through self-serve adoption, not sales headcount.
My focus is the space between product and revenue, end to end: acquisition, activation, retention, and monetization, plus the analytics stack underneath. Lately that means agentic products: systems that act for the user, not just answer them. My work spans B2B SaaS and B2C at consumer scale, from Chargeflow and Workiz to ReasonLabs, where the product protected 10M+ daily active users across 180 countries.
From seed-stage startups to enterprise platforms at scale. I chase what moves metrics, not what fills slide decks.
AI products have longer paths to value, higher trust barriers, and complex activation flows. I build the systems that solve that.
AI & Agentic Products
Taking AI products from concept to production. I define the use-case portfolio, design agentic architectures on MCP, and validate every scenario against live production data before release, so the model's answers stay grounded in what is actually true for each user. The evaluation suite is part of the product, not an afterthought. I build hands-on with LLMs and multi-agent systems.
Activation & Onboarding
Diagnosing and fixing the gap between signup and first value. AI products face unique activation challenges: trust in automation, time-to-value for ML-driven features, and complex setup flows. I map the entire journey from install to activation, identify where users drop off and why, then design and ship the flows that move them forward, whether the evaluator is a person or an agent.
Growth Architecture
Designing end-to-end PLG systems from metrics definition through execution. I build the infrastructure that connects product analytics, lifecycle emails, billing optimization, and attribution into one growth engine, so what acquisition spends and what the product does are measured against the same definitions instead of 2 disconnected systems that disagree at the end of the quarter.
Monetization & Billing
Billing is where growth meets revenue, and most product teams treat it as plumbing. I treat it as a product surface. I have owned billing and payments end to end across Stripe, Shopify Payments, and WooCommerce, restructured billing flows as activation levers, and built self-serve monetization tooling for SMB and enterprise motions alike. In the usage-pricing era the meter needs product thinking, and that is the work.
Product-Led Strategy
Translating business targets into product-driven growth plans. I define OKRs, build roadmaps, and align cross-functional teams around a single North Star metric. The goal is making the product the primary growth driver. Including the handoff most PLG companies get wrong: routing product-qualified accounts into a sales motion without breaking self-serve.
What I've built and shipped across AI-native B2B SaaS, fintech, cybersecurity, and AdTech.
Every step leaks a little. Lift one and everything after it grows.
Start 10,000 people at the top. At 50% a step, 313 reach the far end still paying.
Writing about what I've learned building growth systems for AI products and agentic systems.
The Free Tier Meets the Inference Bill
Free was a marketing expense that rounded to zero, until every action acquired a model call behind it. Free moved from duration to quantity, and now it needs a budget and a conversion job.
Pricing After Seats: What Growth Teams Own Now
The human seat was the unit of SaaS pricing for 2 decades. Agents broke it. When the unit of work detaches from the unit of pricing, the pricing page becomes a product surface.
Evals Are the New QA
Every AI product works in the demo. Production is a stranger asking about their own data. The scenario library is the new PRD, production data is the only honest test set, and the eval suite belongs in the release path.
The Agentic Growth Team
Agents already run the middle of the experiment loop. What breaks when they do, what humans keep, and why the metric definition is now the highest-leverage artifact on the team.
AI-Led Growth: The Motion After Product-Led
Half the industry says PLG is dead because the next user is an agent. Both sides argue about the wrong layer. The economics survive, the funnel's assumptions die, and the build list is the same either way.
When Your Next User Is an Agent
A person who hits friction retries tomorrow. An agent fails silently and takes the next tool in the registry. 3 kinds of users now move through the funnel, and each needs its own definition of activated.
Production Is an Org Problem
Almost every company has an agent pilot. Far fewer have one in production. The surveys disagree on the spread and agree on the causes, and model quality is not among them.
Friction Was Doing a Job
In-assistant buying removed every step between intent and purchase, and converted worse than sending the shopper to the merchant. The steps that got deleted were carrying the decision.
When Resolved Becomes a Price
Bill per resolved outcome and the rubric deciding what counts as resolved stops being a quality artifact. It becomes the billing engine, and an eval failure becomes an invoice that never goes out.
The AI Trust Gap: Why Traditional Onboarding Fails AI Products
AI automation asks users to trust a black box with real business outcomes. That trust gap creates activation friction traditional SaaS onboarding patterns cannot solve. What works instead.
The Transparency Tax
Disclosing chatbot identity before a sales conversation cut purchase rates by 79.7% in a field experiment. The timing fix that recovered it is what Article 50 of the EU AI Act removed on 2 August 2026.
The Moat That Exported Itself
Every deck calls memory the last AI moat. Then the 3 companies with the most of it to protect all shipped memory portability inside a month. Whatever survives a plain-language export was never a switching cost.
Time to First Dollar
A marketplace has 2 activation problems running on different clocks. Supply activates on first earning, demand on first satisfying transaction, and referral loops built before either one works amplify churn.
Attribution After the Click
Discovery moved inside LLM answers, where the click never fires. Share of answer replaces share of shelf, branded search becomes the shadow of invisible recommendations, and some influence is now honestly unmeasurable.
Distribution Is a Product Skill Now
The best product no longer wins by default. Building got cheap, discovery compressed into AI answers, and owned audience became an asset a product team has to build on purpose.
Growth Runs on the Warehouse Now
Every tool in the old growth stack kept its own copy of the customer, with its own definitions. The copies are dying, and the team that runs on the warehouse owns definitions instead of tools.
Going Enterprise Without Killing Self-Serve
Moving upmarket is usually framed as outgrowing self-serve. Backwards. Self-serve is the qualification engine the enterprise motion runs on, and the handoff decides whether you capture the deal.
The Buyer, the Admin, and the User
The flow is designed for 1 person and 3 different people show up, each with a different definition of value. Detect the persona at entry, branch the first session, treat activation as a chain.
Metrics That Move Teams, Not Just Dashboards
Most product dashboards measure what is easy to count. The metrics that change behavior are the ones a PM, designer, and R&D lead can argue about in the same room.
Building Retention Before You Need It
Churn is a receipt, not an event. Retention is an instrumentation problem long before it is an analysis problem, and the cancellation flow is the highest-signal surface most products waste.
The Compound Effect of Small Funnel Fixes
Growth teams chase 10% wins and miss the ones that compound. A 5% lift in 3 places does more for ARR than a single redesign, and it ships in a week.
Let's connect.
If you're working on PLG, activation, or growth for an AI product, I'd like to hear what you're building. I also take on a small number of advisory engagements with founders working on activation and PLG.