I design and build AI-first products where orchestration, decision engines and feedback loops drive real business impact.

Barcelona 🇪🇸

VP of Product & Technology with 15+ years building and scaling SaaS and AI-first platforms across startups, scale-ups and global companies.

Led Product, Engineering, Data and AI organizations from 10 → 65+ professionals.
Owned end-to-end product strategy, roadmap, AI transformation, and P&L across multi-product environments.

Founder mindset. Operator discipline. Systems thinking.

I don’t ship features.
I design systems.

• AI-native product strategy (ICP → architecture → GTM loops)
• Multi-agent orchestration & execution layers
• Decision & scoring engines (structured + unstructured signals)
• Platform foundations (multi-tenant, RBAC, event-driven systems)
• AI as infrastructure — not as a UI gimmick

AI is not an add-on.
It is the execution layer.

AI Search Visibility & AEO Pulse
https://ateneai.com

A private AI venture focused on search visibility in the LLM era.

Operational AI orchestration framework
https://github.com/davidgarzon/multi-agent-business-operator

Foundation for building agent-based operational systems.

Structured PRD evaluation system with scoring & readiness signals
https://github.com/davidgarzon/prd-decision-engine

Transforms product requirements into measurable decision artifacts.

Decision-first experiment tracker for product teams
https://github.com/davidgarzon/experiment-crm

Append-only decision logs to prevent learning decay.

Founder & operator interviews
https://comotrabajan.com

Long-form conversations on how companies are actually built.

🔹 Digital Presence Score Engine
Weighted scoring model turning digital signals into decision intelligence (ongoing)

• Platform > Feature
• Decisions > Dashboards
• Memory-driven systems
• Tools + Agents + Feedback loops
• Business impact > Technical novelty
• Distribution matters as much as architecture

Traditional SaaS:

User → UI → Backend → Database

AI-native systems:

User → Orchestrator → Agents → Memory → Tools → Execution → Feedback loop

Intelligence is not an endpoint.
It is a loop.

AI-native companies are designed around:

• orchestration
• decision layers
• feedback systems
• compounding data advantage

Python · FastAPI · OpenAI · LangGraph · Postgres · Vector DBs · GCP · AWS · Terraform

Stack is secondary. System design is primary.

I explore:

• AI-native product design
• AEO / GEO strategy
• Multi-agent system models
• AI-driven growth loops
• Operating systems for product teams

Blog (soon): https://davidgarzon.com
LinkedIn: https://linkedin.com/in/davidgarzon

• LinkedIn → https://linkedin.com/in/davidgarzon
• Email → davidgarzon@gmail.com
• Website (soon) → https://davidgarzon.com

"Build systems that execute."