01
AI Product Strategy
Decide where AI belongs in your product or business—and where it does not.
- AI opportunity map and prioritization
- Product thesis and target customer
- Build, buy, partner, or wait recommendation
- Roadmap and investment sequence
AI Product · Strategy · GTM
Turn AI ambition into a product customers will adopt and pay for.
I help B2B SaaS founders and enterprise leaders identify where AI creates real business value, define the right product, and build a practical path from opportunity to market.
25+ years product leadership$210M+ attributed impact0→1 to scale across enterprise AI and SaaS
Alon
AI opportunity assessment
3 high-value bets
↗
Strongest opportunity
Exception-heavy workflow with measurable delay and clear approval rules.
Exception-heavy workflow with measurable delay and clear approval rules.
✓
Recommended motion
Design-partner pilot before platform investment.
Design-partner pilot before platform investment.
Product decision
Feature, product, service—or no build?
ValueFeasibilityGTM
Senior product judgment, grounded in enterprise execution.
25+years in product
10–30+teams led
Fortune 100customers served
AI + SaaSstrategy through delivery
The situations I help resolve
AI is rarely blocked by ideas. It is blocked by unclear decisions.
The most expensive mistakes happen before development: choosing the wrong problem, building too broadly, or taking a product to market without a credible buyer and adoption path.
01
“We know we need AI—but where?”
Separate high-value opportunities from attractive demos, internal experiments, and low-impact features.
02
“We built it. Why is nobody buying?”
Revisit the customer, problem, positioning, packaging, and pilot motion before adding more features.
03
“Everyone has a different roadmap.”
Align executives, product, engineering, security, and GTM around one product thesis and decision framework.
Services
Focused consulting for the decisions that shape the product.
Engagements can be a single assessment, an intensive strategy sprint, or fractional leadership through validation and launch.
02
Product Definition & Review
Challenge an idea, prototype, architecture, or roadmap before the next major investment.
- Value proposition and product review
- Scope, UX, architecture, and trust model
- Risks, gaps, and weak assumptions
- Clear next-step recommendation
03
AI Go-to-Market Strategy
Translate technical capability into a proposition buyers understand and a motion they can adopt.
- ICP, buyer, user, and urgent problem
- Positioning and messaging
- Design-partner and validation plan
- Pilot, packaging, and pricing direction
04
Fractional Product & AI Leadership
Add senior product judgment during transformation, validation, or an important 0→1 initiative.
- Fractional CPO / Head of AI support
- Cross-functional alignment
- Product operating model and governance
- Executive, customer, and board communication
How I work
A direct path from ambiguity to a decision you can execute.
01 · Understand
Find the real problem
Clarify the business outcome, user, context, constraints, evidence, and existing alternatives.
02 · Challenge
Test the assumptions
Expose weak logic, hidden dependencies, product risk, and places where AI adds novelty but not value.
03 · Define
Make the choices
Shape the product thesis, priority use cases, boundaries, roadmap, and go-to-market direction.
04 · Activate
Move into the market
Turn the strategy into customer discovery, a design-partner offer, a pilot, or a delivery plan.
What collaborators value
Strategic clarity without the polite agreement.
Rather than publish unapproved testimonial quotes, this section captures the qualities repeatedly valued by founders, executives, architects, engineers, and product teams who work with me.
“
Clarity in complex systems
I connect technology, customer reality, operating constraints, and commercial logic into a direction teams can understand.
“
Frank, independent judgment
I do not validate an idea to keep a meeting comfortable. I identify what is weak, what is missing, and what should happen next.
“
Strategy that reaches execution
I can work from executive choices down to product scope, architecture boundaries, pilot design, and GTM sequencing.
Use cases
Products and transformations that show how I think.
These are not just portfolio entries. Each one demonstrates a product decision, a market thesis, and a path from ambiguity toward adoption.
Current venture · Enterprise agentic AI
Controlled AI Workers
The challenge: companies want AI agents to execute operational work, but open-ended autonomy creates security, governance, and accountability risk.
Product directionControlled workers for one exception-heavy workflow, with scoped identity, approval gates, short-lived access, workflow memory, and an execution ledger.
My roleProblem framing, product thesis, trust model, workflow architecture, early use cases, and design-partner GTM.
Enterprise AIAgentic workflowsGovernanceCategory design
CONTROLLED AI WORKERS
AI workers for workflows you cannot automate blindly.
Paused for approval
Invoice Exception Worker
Vendor verified · PO matched · Amount exceeds policy threshold.
Trust boundary
Approved tools, one-time action permission, human escalation, complete ledger.
0→1 product exploration · Executive intelligence
Enterprise AI Chief of Staff
The challenge: leaders have access to more information than ever, yet still discover operational risk, customer escalation, and execution problems too late.
Product directionA proactive intelligence layer that monitors signals across business systems and surfaces decisions before leaders need to ask.
My roleConcept definition, ICP, proactive behaviors, product experience, multi-agent model, positioning, and GTM hypotheses.
0→1 productExecutive workflowsMulti-agent UXGTM validation
MORNING BRIEF · 07:30
Know what matters before you have to ask.
Pipeline coverage at 1.1×
Below target and down versus last month. Recommended action: inspect two stalled enterprise opportunities.
Execution signal
Four engineering tickets are blocked by the same external dependency.
Enterprise transformation · HARMAN
Building an AI/ML product domain from zero
Founded the AI/ML domain for an automotive OTA platform serving global OEMs. Built the team, product direction, MLOps foundations, governance, and a pipeline of production use cases.
AI platform strategyMLOpsEnterprise governanceFortune 100
TRANSFORMATION OUTCOME
AI became a platform capability—not a collection of demos.
Delivered
Predictive maintenance, OTA optimization, RAG-based knowledge access, and ML-assisted analysis.
Business-model transformation · mPrest
From project-based defense software to commercial AI/IoT SaaS
Led the product and strategic shift toward cloud-native commercial offerings for utilities and smart cities, aligning architecture, product, partnerships, and market entry.
SaaS transitionAI/IoTNew markets$10M contracted value
COMMERCIAL PIVOT
Productize the capability. Open the market.
Strategic result
A repeatable SaaS proposition for utilities and smart-city use cases, supported by partnerships and enterprise validation.
About
I work where product, technology, and business transformation meet.
I have spent more than 25 years creating new product domains, turning complex technology into commercial platforms, and leading products from early definition through enterprise adoption.
My experience spans HARMAN/Samsung, mPrest, Tyco/Visonic, Kramer, independent ventures, AI/ML platforms, IoT, cloud SaaS, agentic systems, and founder-led 0→1 products.
Today I work with founders and enterprise leaders who need experienced, independent judgment before committing significant time, money, and organizational energy to an AI initiative.
I challenge assumptions.Agreement is not the service. Better decisions are.
I connect product to revenue.Technology matters only when a customer, user, and adoption path exist.
I work across levels.From executive strategy to product scope, architecture, and market experiments.
I optimize for evidence.Validate the riskiest assumption before scaling the investment.
Choose the right conversation
Bring one important AI product decision.
Start with a general introduction, or choose a focused session based on the question you need to resolve.
Expand any meeting to see the questions it is designed to answer. Cal.com URLs are configured in one block near the bottom of the HTML. Until a URL is added, the booking button opens an email request.
Intro CallUnderstand the situation and decide whether there is a fit.+
Best for an initial conversation about your company, product, and current challenge.
- What are you building, changing, or trying to decide?
- Where are product, AI, or GTM efforts currently stuck?
- What outcome would make an advisory engagement valuable?
- Is this the right problem for my experience and working style?
AI Product ReviewReview an AI idea, prototype, product, architecture, or roadmap.+
Best when you already have a product direction and need an experienced external review.
- Are we solving a painful and valuable customer problem?
- Is the value proposition clear enough for users and buyers?
- Are we building the right product, in the right way?
- Which features belong in the first credible version?
- Is AI genuinely required, or is conventional automation better?
- Are the architecture, trust boundaries, and human controls appropriate?
Strategic AI Decision SessionChallenge the options and identify the most credible next step.+
Best when a specific decision is already on the table and you need to choose a direction.
- Should we build this feature or initiative now?
- Should this become a product, service, feature, or internal tool?
- Should we use an AI agent, bounded automation, or a conventional workflow?
- Should we continue, pivot, narrow the scope, or stop?
- What is the strongest next step after the prototype or pilot?
- Which assumption should we validate before investing further?
AI Go-to-Market AssessmentReview ICP, positioning, validation, pilot, packaging, and sales motion.+
Best when the product is credible but the path to adoption and revenue is unclear.
- Who is the ideal customer, buyer, user, and internal champion?
- Why should they buy this product now rather than wait?
- Is the positioning specific and differentiated enough?
- How should we recruit and structure design partnerships?
- What should a pilot prove, and how does it convert to production?
- How should we package, price, and sell the offering?
AI Opportunity & Best-Fit AssessmentFind where AI can create the strongest measurable business value.+
Best when your organization wants to use AI but has not yet identified the strongest opportunity.
- Which customer or employee workflows create the most pain?
- Where are delays, errors, repetitive work, or decision bottlenecks costly?
- Which AI use cases have meaningful value and realistic feasibility?
- What data, systems, controls, and organizational capabilities are available?
- Which opportunities are too risky, immature, or poorly defined?
- Which single use case should be explored first?