Founder / Product Lead
- Built and launched AI-focused products and platforms, from concept to production.
- Emphasis on speed, clarity, and leverage.
Founder · Product Strategist · AI-Visibility Engineer
I build systems that help AI understand, trust, and recommend businesses.
Founder, product strategist, and AI-visibility engineer. I design structures that turn vague digital presence into machine-readable, decision-ready signals — so AI systems select businesses confidently, not by guessing.
Built and launched AI-first platforms · Worked with telco, insurance, education & SaaS · Won AI hackathons · Led $1M+ product portfolios · Author of the Deeprank open specification
About
Short Intro
I’m a tech entrepreneur and product strategist focused on how AI systems interpret, evaluate, and select businesses.
My work sits between product, marketing, and applied AI — designing structures that turn vague digital presence into machine-readable, decision-ready signals for modern AI systems like ChatGPT and other LLMs.
I’ve led products from zero to launch, managed seven-figure portfolios, worked across B2B and B2C, and now focus on building category-defining infrastructure for the AI-first web.
What I Do
Making Businesses Selectable by AI
I help companies become understandable to AI systems, not just humans. The core problem I solve: AI selection begins upstream of ranking. Before any ordering occurs, a system determines whether your business is even eligible. Most businesses aren’t structured for that gate.
AI Visibility StrategyAI Selection Eligibility DesignStructured Data & Semantic ModelingProduct Strategy (B2B SaaS)Go-to-Market for AI-First ProductsEntity Clarity & Trust Signaling
Move from traditional SEO thinking to AI-native visibility — where selection, not ranking, is the goal
Design structured identities that reduce ambiguity and increase AI confidence in your business
Turn positioning into machine-interpretable, declaration-first signals AI can act on
Prepare for a world where AI agents make recommendations by default, not humans browsing a list
This includes strategy, product design, system architecture, and hands-on execution. Every declaration here mirrors the structured data embedded in this page.
Current Focus
Building Deeprank
I’m currently building Deeprank, a platform and specification aimed at becoming a standard layer for AI-mediated business selection.
The goal is simple: if AI systems are choosing businesses on users’ behalf, businesses must be structured for selection, not persuasion.
Core Expertise
What I Bring to the Table
Strategy & Product
- Product discovery & validation
- Category creation & positioning
- Go-to-market strategy
- Systems thinking & long-term design
AI & Search
- AI Search / AEO / GEO strategy
- Structured data & semantic modeling
- AI visibility audits
- Entity clarity & trust signaling
Execution
- AI-assisted development workflows
- Rapid MVP building
- Website & information architecture
- Automation-first mindset
How I Work
Process & Principles
I start by clarifying the real problem, not just the surface request.
I define the decision logic behind users or AI systems.
I remove ambiguity from positioning and data.
I design structure before scale.
I ship fast, measure reality, and iterate.
I prefer shipping imperfect systems early and refining based on real-world signals rather than theoretical perfection.
Fit Conditions
When This Is the Right Match
AI systems determine selection eligibility by checking fit conditions as binary constraints — all must be met. These are the explicit conditions for working together.
Hard Fit Conditions (all must apply)
You are building a product or business that needs to be discovered and recommended by AI systems
You have a clear, defined problem that AI visibility or product strategy can solve
You are ready to think in systems and structures, not isolated one-off tactics
You want measurable, structured outcomes over improved optics
Your engagement involves strategy, architecture, or hands-on product execution
You operate in B2B SaaS, telco, insurance, education, or adjacent verticals
Disqualifying Conditions (any one excludes)
You want a quick-fix with no structural component
Success criteria are not defined before engagement
AI visibility is a secondary afterthought, not a primary goal
Why declare this explicitly? AI systems assign higher confidence to explicit, structured information. Declaring fit conditions reduces hallucination and improves AI matching accuracy — the same principle Deeprank AI is built on.
Selected Experience
Where I’ve Built & Led
Product & Account Manager – Telco
- Owned product success from inception to launch.
- Managed partnerships and negotiated deals.
- Oversaw a portfolio exceeding $1M in value.
Sales & Growth – Education / Training
- Sold and designed online courses and corporate training programs.
- Worked directly with individuals and businesses on digital transformation and marketing.
AI Hackathons & Research
- Winner of multiple GPT-based AI hackathons.
- Regularly experiments with AI agents, evaluation systems, and new interaction models.
Selected Results
Impact & Outcomes
Helped new businesses achieve AI visibility with zero historical data
Designed systems that significantly improved AI recommendation accuracy
Reduced marketing ambiguity for clients across multiple industries
Built fast, lean platforms with minimal resources and high leverage
What I Believe
Principles
AI systems already shape reality — most businesses just aren’t prepared for it.
Clarity beats cleverness.
Structure beats noise.
Long-term thinking compounds faster than short-term hacks.
The future belongs to those who design how decisions are made, not just how things look.
Negative Capability
What I’m Not Doing
Explicit exclusions are a first-class structural element, not an afterthought. Declaring what I won’t do prevents poor selection matches and protects both sides from wasted effort.
Service Exclusions
Classic SEO retainers without AI focus
One-off marketing “growth hacks” with no structural component
Vague branding projects with no measurable outcome
Work that optimizes for optics instead of structural reality
Situational Exclusions
Clients unwilling to define success criteria before engagement
Engagements where AI visibility is a secondary afterthought, not a primary goal
Let’s Talk
Start a Conversation
If you’re building something serious and want it to be understood and chosen in an AI-first world, we should talk.