When everything routes through the founder, your product work doesn’t scale
I help technical founders step out of execution mode by making product judgment explicit and shared, so you can step back into strategy while your team makes confident decisions without you.
You've Hit the Judgment Bottleneck
Your team is growing. Your product is working. You have active users. And the pressure to ship the right thing, to learn fast, get wins and prove traction has never been higher. And you're stuck heads down in execution.
You need to be thinking strategically about what bets to make. Instead, you're spending your days unblocking, clarifying, course-correcting. Instead, you're caught in patterns you can't quite escape.
You're the product and process glue: decisions route through you, engineers need constant direction, customer signals create decision paralysis. You spend days firefighting instead of thinking clearly about what moves the needle.
The pattern: Product judgment is trapped in your head. As complexity and pressure increase, judgment doesn't scale. You get pulled deeper into execution exactly when you need to operate strategically.
This is when most founders consider hiring a PM or someone to take over the backlog and project management. But that won’t fix it, since your judgement is not made explicit yet. You will have the same problems with an additional person to manage.
Does this sound familiar?
What You're Experiencing:
→ Decisions route through you constantly
→ Engineers need direction on every decision
→ You spend 60%+ time in execution, not strategy
→ Customer signals create decision paralysis
→ Roadmap exists but confidence is shaky
→ Work gets done but not in the direction you expected
→ You're pulled into meetings as "tie-breaker" constantly
→ Strategic thinking happens late at night (if at all)
→ You review work: "fine, but not what I would have done"
Your Stage & Context:
→ Seed to Series A, 5-20 people
→ Active users, proving PMF or traction
→ Under pressure to show clear progress
→ Considered hiring PM, unsure it helps
→ Past "process" attempts didn't stick
You've Become the Product Glue
Decisions route through you. Not because you want control, but because things drift when you're not involved.
Your team asks "what should we prioritize?" multiple times per week. Engineers need constant clarification to get the outcome you expect. Work gets done, but not quite the way you would have done it, so you find yourself stepping in late to course-correct.
The invisible tax: You can't step back because product quality depends on your involvement. And with pressure to hit milestones, you can't afford to let things drift.
Engineering Executes Without Product Judgment
Your engineers are technically strong. But they keep building "the wrong thing" without realizing it.
They ask for constant direction. They optimize for tasks, not outcomes. They over-engineer when you need to learn fast. Decisions are technically fine, but not the ones you would make.
What's missing isn't skill. It's shared product judgment. The frameworks for "what makes a good decision here" live only in your head.
And when you're under pressure to figure out PMF or deliver wins, you can't afford expensive wrong turns.
Too Much Noise Creates Decision Paralysis
Customer feedback floods in (often contradictory). Sales has urgent requests. Metrics point in different directions. Investors want traction. The team needs direction.
Everything feels important. Nothing feels obviously right.
You've written a roadmap, but don't feel confident defending the bets. There are 10 reasonable directions. You don't know which one actually matters. And the pressure to "get it right" makes every decision feel higher stakes.
Result: Strategy gets crowded out by operations. You spend your days firefighting instead of thinking clearly about what will actually move the needle.
How I help
For founders navigating the "messy middle" towards product-market-fit
You've proven the product works, but you are stuck in execution. Now you need product systems that scale. You are too small to hire a full time product manager, but too big to feel the pain and chaos that comes from not having product management support in your teams.
You need confidence that the signals you're seeing translate into the right bets. And you need a path to remove yourself from day-to-day execution.
What you get:
Engineering teams that own outcomes, not just tickets
Clear roadmap and betting process you trust
Strategic frameworks that work without you in every decision
A plan to transition from founder-led to product-led
A plan on how to build you product team
Who this is for: Technical founders building toward Product-Market-Fit
Learn More: Founder PM Advisory →
For teams taking AI from PoC to ready-to-scale in production
Your AI PoC works in the demo. Now you need it to work reliably at scale. Moving from proof-of-concept to production AI isn't just an engineering problem, it's a product problem. You need evaluation frameworks, quality standards, and a systematic approach to continuously optimize and stay on top of your AI features as the ecosystem and environments shifts.
What you get:
Frameworks on how to measure impact of AI features
Approaches to evaluate and improve AI output quality
Testing approaches that catch issues before users do
Strategic guidance on what problems to solve with AI
A process to operationalize AI features
Confidence in your AI product decisions
Who this is for: Product teams integrating LLMs who need PM perspective on quality and reliability
Learn More: AI Product Advisory →
How I work
Advisory
I work on monthly retainers with a small number of companies at a time. This means regular access, ongoing support, and accountability, not one-off recommendations you'll never implement.
Most engagements start with diagnostics: figuring out whether you need process, strategic clarity, or just someone to take work off your plate. Then we build the lightest-weight systems that actually help.
Fractional Product Leadership
I take on 1-2 fractional engagements for companies that need hands-on execution alongside strategic guidance.
Sprints
Project-based
Work With Me. Outcomes You Walk Away With.
I help product leaders operationalize their AI solutions and make them ready for scale.
AI Ops Audit: Is your AI solution ready to scale?
A fast, structured assessment of your AI feature maturity and readiness to scale. We walk through metrics, evals, automations, reliability and economic concerns and identify potential gaps and high priority initiatives for your roadmap.
Outcome: A roadmap to operationalize your AI solution and make it ready for scale.
Advising
3+ months engagement
Video calls
Optional async access
Product & AI
Product process with AI
Product best practices
Opertionalize AI solutions
Fraction Product Leadership
Fixed period engagement
Head of Product / AI roles
Product process implementation
Mentoring
Product leader hiring support
Start Learning
Build the foundations you need to understand, validate, and scope AI capabilities with confidence.
Adaptive AI-Tutor
Learn core AI concepts in plain language, fast. This adaptive AI tutor helps PMs understand AI concepts like RAG, agents, evals, vector databases, and more in under 30 minutes.
AI Feature Validation (Mini Course)
A structured mini-course that teaches you how to validate AI feature ideas before investing time and engineering resources.
Practical product thinking applied to real AI work.
Not theory or hype.
Built & Shipped (Hands-on AI Experience)
I’ve worked hands-on with AI at the application layer building, integrating, and operating AI-powered features with real-world constraints.
Custom GPTs for structured product workflows
Prompt chains using the OpenAI Completion API
Cost estimation & monitoring (per request / analysis / customer)
Vision API integrations for high-fidelity image understanding
Building AI-enabled products is new for most teams. I focus on applying AI at the application layer, combining strong product discipline with hands-on experience to help teams turn AI capabilities into production-ready features.
Mini Case: AI Cost Transparency & Control
Problem: We built an LLM-based analysis that evaluated long-form articles across five major categories, each with multiple sub-checks. This required extensive prompting and multiple model calls. To make responsible product decisions, we needed to understand the real cost of a full analysis run — across input/output tokens and different model choices.
Approach: I designed a lightweight cost-estimation and monitoring layer that made cost per category, per full analysis, and per user visible early. This allowed us to reason about pricing models, compare model choices, and iteratively optimize prompts and checks.
Outcome: Clear scoping decisions, pricing confidence, and guardrails in place before rollout.