Experimentation craft
- A/B and multivariate testing
- Bayesian and sequential testing
- Power analysis
- Incrementality and holdouts
- Guardrail metrics
- Experimentation governance
- Opportunity sizing
- ICE and RICE prioritization
Working stack
Tools are useful. Shipped systems are the proof.
I combine AI agents, code, experimentation platforms, analytics, model APIs, and automation to turn growth questions into working products and defensible decisions.
Operating principle
Learning speed matters. Judgment still sets the standard.
I learn new platforms quickly, but I only move a capability up this page when I can explain what I built, how I checked it, and what decision or outcome it supported.
These tiers separate repeated consequential use, independent project work, working familiarity, and platform evaluation. That distinction is intentional.
Daily drivers
Used constantly and trusted for consequential work. This is where I claim real depth.
Platforms and measurement
- Optimizely (Advanced)
- Adobe Target
- VWO
- PostHog — analytics, experiments, and metric definition
- GA4
- Adobe Analytics
- Contentsquare
- Hotjar
- Microsoft Clarity
- Mixpanel
- Heap
- Data and event governance — metric definitions, instrumentation plans, taxonomy governance, and data-quality monitoring
AI coding and engineering · Advanced
- Claude Code
- Codex (OpenAI)
- Agent-assisted debugging, review, testing, and deployment
AI reasoning and research · Advanced
- Claude
- ChatGPT (OpenAI)
- Perplexity
- Claude Cowork
- Research synthesis and decision support
LLM APIs, evaluation, and automation
- OpenAI and Anthropic APIs
- Prompt and context architecture
- LLM evaluation and guardrails — test sets, structured rubrics, failure analysis, and safe fallbacks
- AI workflow automation
Build and ship
- GitHub
- Terminal and CLI
- macOS
- Astro
- Sanity CMS
- Vercel
- Cloudflare
- AWS
- Framer
- Webflow
- WordPress
- Shopify
Growth and discovery
- Technical SEO
- E-E-A-T content strategy
- Answer engine optimization
- Generative engine optimization
- Direct-response copywriting
- Email marketing
- Organic distribution
Product and vendor leadership
- Zero-to-one product vision
- PRDs and roadmaps
- Sprint planning
- Experimentation platform evaluation
- Agency vetting and RFPs
- Stack audits
- Contract negotiation
- Freelancer management
Proficient
Real project depth. I can work independently and become current again quickly.
Data science and programming
- Python
- SQL
- R
- Statistical modeling
- Causal inference
- Forecasting
BI and visualization
- Tableau
- Power BI
- Looker
- Looker Studio
Personalization and CDP
- Tealium
- BlueConic
- Real-time segmentation
- Predictive lead scoring
- Recommendation engines
Research and design
- Figma
- Miro
- UserTesting
- Qualtrics
- Usability testing
- Session replay
- Journey mapping
- Surveys and interviews
Data infrastructure
- Snowflake
- PostgreSQL
- MongoDB
- Typesense
- Google Tag Manager
- Segment
- Multi-touch attribution
Familiar
Used on real projects and able to evaluate or manage; not presented as mastery.
CRM and automation
- HubSpot
- Salesforce
- Marketo
- Pardot
- Dynamics 365
- Zoho CRM
Additional testing and analytics
- AB Tasty
- Unbounce
- Crazy Egg
- Medallia
- Quantum Metric
- Amplitude
Collaboration
- Jira
- Confluence
- Asana
- Monday.com
- Trello
- Notion
- Slack
- Microsoft Teams
- Microsoft 365
Additional platform experience
Research, demos, vendor evaluation, or brief hands-on use—useful context without a production-depth claim.
Experimentation platform evaluation
- Eppo — research, demo, and sales engineering evaluation
- Statsig — research, demo, and sales engineering evaluation
- LaunchDarkly — researched and evaluated
- GrowthBook — researched and evaluated
AI-assisted GTM and automation
- Clay — brief hands-on use
Beyond the inventory