Strategy that ships.

Identify opportunities to create leverage and impact from the use of LLMs or traditional machine learning techniques within your tech stack or consumer experience.

• AI opportunity assessment across your product and workflows
• LLM or traditional ML: model choice, costs and maintenance
• Build, buy, open-source or partner, backed by a business case

Make the product idea real with a working prototype shipped into a production environment. Work through LLM feature and agent design, build real software and define how quality will be evaluated.

• Agent design with tool calling, RAG and prompt architecture
• Working software on GCP or AWS and commercial LLM APIs
• Eval harnesses that set the quality bar before scaling

Translate an opportunity into a concrete, sequenced plan. Align the product vision, positioning, success metrics and roadmap with what your team can execute.

• Product vision and competitive positioning
• Force-ranked priorities via custom scoring rubrics
• Practical build sequencing with room for MVP market testing

Make priorities explicit and give teams a shared way to make decisions. Connect customer insight, engineering capacity and business outcomes with a product operating cadence that keeps everyone on the same page.

• Prioritization across sales, engineering and data science
• Discovery, requirements and release practices that scale
• AI-native workflows over spec writing

Bring an experienced product executive into the leadership team. Own product outcomes together while building the strategy, team and operating rhythm.

• Ownership and maintenance of vision, strategy and roadmap
• Hiring and coaching across product, UX and analytics
• Pricing, packaging and go-to-market alignment
• Board materials and the investor narrative