Tyron Christian Dizon
Chief Product Officer · AI Product Builder · Techstars-Backed SaaS Founder
I take ambiguous, high-stakes ideas and turn them into shipped products, working systems, and real revenue. A founder-level operator across product, engineering, AI, automation, and growth, equally at home setting the strategy and building the first version of it.
~$4Mcapital raised at SanityDesk
~$2Msales driven
Techstars LAaccelerator-backed founder
10+ yrsproduct, AI & startups
Executive Summary
Co-founder and Chief Product Officer who builds companies, not just features. As co-founder and CPO of SanityDesk, a Techstars Los Angeles company, I helped raise about $4M and drive about $2M in sales. Since then I have shipped production systems most teams would split across four specialists: a healthcare data bridge that pulls thousands of patient records out of a locked-down records system with no API and syncs them into a CRM, a multi-engine system that measures whether a brand is actually cited by ChatGPT, Perplexity, and Gemini, an autonomous content and operations pipeline that publishes daily behind a safety gate, and a meeting-intelligence app with live transcription and retrieval over a private knowledge base. I operate above strategy and inside execution at the same time: I set direction, design the product, build the first working version myself, and lead the team that scales it. I am at my best where the problem is unclear, there is no clean API, and the result has to be real.
Why I Am Different
Most leaders pick a lane. I work the whole field. I can define the strategy, design the product, build the working prototype, lead the cross-functional team, and stay accountable to the number. That combination, strategy plus craft plus execution, is what lets me move a company from a vague idea to shipped software and paying customers faster than teams many times the size. I am the person founders call when something important has to get built, and built right, before the market moves.
Best-Fit Roles
Chief Product Officer · Chief Technology Officer (product-focused) · VP Product · Head of Product · Founding Product Leader · AI Product Executive · Co-Founder. Open to executive, founding, and fractional engagements, remote worldwide.
Experience
Techstars Los Angeles · SaaS platform
- Co-founded the company and owned product end to end, from the first prototype to a platform that customers paid for.
- Helped raise about $4M by turning product vision into something investors and customers could see working, not just hear pitched.
- Drove about $2M in sales by aligning product, go-to-market, and execution around the outcomes customers would actually pay for.
- Earned selection into Techstars Los Angeles, one of the most competitive startup accelerators in the world.
- Operated as the bridge across founders, engineering, design, marketing, and operations, removing the execution bottlenecks that stall most early-stage companies.
0 to 1 productFundraisingGo-to-marketSaaSTeam leadership
Chief Product Officer, Product, AI & Automation Systems
Current · SaaS, e-commerce, and healthcare
- Set product and AI strategy, then personally build the production systems that prove it, compressing months of debate into shipped software.
- Ship end-to-end systems across data integration, autonomous AI operations, and growth, then lead the teams that operate them.
- Operate as the connective layer between business goals and engineering reality, so strategy ships instead of stalling in planning.
- Trusted with the hard, ambiguous problems: the ones with no clean API, a short timeline, and a real number attached.
AI product strategyMulti-LLM orchestrationData integrationGrowth systemsCross-functional leadership
Selected Work (Evidence)
Each system below links to a full case study at tyronzky.ninja/work with role, architecture, decisions, and an honest evidence label.
- The problem: a multi-clinician healthcare practice ran patient outreach by hand. Appointments and balances lived in a locked-down records system with no API and a bot-gated login.
- What I built: an automated bridge that holds an authenticated session through the system's bot protection, pulls the schedule and the patient-balance report, matches each patient's balance to their appointment, and syncs the result into the practice's CRM with tags and fields, behind a deterministic safety gate, with no sensitive data left on disk.
- Why it is rare: there was no API to call. I solved the authentication, the bot-gating, the fuzzy patient matching, and the data-safety design, then synced about 2,800 records in a single run. Most "integrations" stop where this one started.
PythonPlaywrightCRM APIsSession / anti-botData-safety design
- The problem: "answer-engine optimization" is sold on opinion. No one could prove whether a brand is actually cited by AI engines.
- What I built: a harness that runs a fixed set of buyer questions against ChatGPT, Perplexity, and Gemini, detects citations of a target brand or domain, and tracks the citation rate over time, turning a vague claim into a real baseline and trend.
- Why it is rare: I built the instrument, not just the opinion. It quantifies what most agencies only assert, and it is the engine behind a productized audit offering.
PythonOpenAI / Perplexity / GeminiCitation detectionMeasurement design
- The problem: content and operations do not scale by hand, but naive automation will eventually publish the wrong thing.
- What I built: a headless LLM pipeline that researches, drafts, checks itself against a deterministic blocklist, and publishes daily, unattended, plus a daily health and SEO/AEO crawler and auto-deploy.
- Why it is rare: I paired full autonomy with hard guardrails. Most "AI content" is either still manual or recklessly automated. This one runs itself and stays safe.
Claude / LLMsNode.jsCloudflare Pages / Workers / D1SchedulingAEO / Schema
- The problem: founders lose context between calls, and generic note-takers know nothing about your business.
- What I built: a desktop system that transcribes calls in real time, retrieves relevant context from a private knowledge base with vector search, suggests answers live, and writes structured post-call debriefs back into long-term memory.
- Why it is rare: real-time audio, retrieval-augmented generation, LLM orchestration, and a persistent memory architecture, built end to end and solo.
PythonFAISS / vector searchWhisperOpenAIRAG
- The problem: a marketing SaaS needed to become one federated, white-labeled platform across separate products.
- What I built: led product direction and integration across engineering teams, identity bridging, content handoff, and cross-product embedding.
- Why it is rare: I held the architecture and the business case in the same head, so integration decisions served the product, not just the codebase.
Product leadershipSystem integrationREST APIs / webhooksFederated identity
Core Strengths
- Product strategy & vision, 0 to 1 and at scale
- AI product development & multi-LLM orchestration
- Data integration & automation where no API exists
- Rapid prototyping, idea to working software
- RAG & vector-search systems
- Go-to-market & growth systems
- Fundraising & investor storytelling
- Autonomous workflow & operations automation
- Cross-functional leadership
- Product & business operations
Technical Depth
AI & multi-LLM orchestration (Claude, OpenAI, Gemini, Perplexity) · Python · JavaScript / Node.js · Playwright & browser automation · RAG & FAISS vector search · REST APIs, webhooks & MCP · Cloudflare (Pages, Workers, D1) · GoHighLevel & CRM / lifecycle systems · Schema.org / AEO / GEO · Git & CI/CD. Comfortable in the codebase and in the boardroom.
Profile
- Seniority: Executive / Founder
- Experience: More than a decade
- Work setup: Remote worldwide, light hybrid when needed
- Languages: English, Filipino