Engineering. Marketing. Leadership.

13+ years engineering × 10+ years marketing × 8+ years leadership.

I build systems at the intersection of software, go-to-market, and org design. The goal is durable leverage: faster execution, better decisions, and measurable business outcomes.

Scaled enterprise analytics to 10K+ users; reduced report latency from days to minutes.
Improved critical API and reporting paths by ~40% through cache and data-flow redesign.
Built growth infrastructure that tripled organic traffic in 8 months and cut experiment cycles from weeks to days.
Increased team autonomy with ADRs, CI/CD guardrails, and coaching models that outlast handoff.
Francisco
Engineering × Marketing × Leadership

Leverage Model

01.13+ Years

Engineering

Architect production systems with clear failure modes, operability, and ownership.

02.10+ Years

Market Strategy

Convert product and market signals into technical priorities tied to revenue and adoption.

03.8+ Years

Leadership

Raise team throughput and decision quality through coaching, standards, and execution discipline.

10K+
Enterprise Users Supported
Days → Minutes
Report Latency Improvement
3× / 8 mo
Organic Growth Outcome
This model compounds because technical decisions, product strategy, and team capability are designed as one system.
/// Problems, Constraints, Impact

System Case Studies

/// Trade-offs Under Constraint

Decision Log

01.

Monolith first for speed to market

Chose

A modular monolith with strict boundaries and observability from day one.

Over

A premature microservices split.

Cost

Required a later extraction roadmap as scale and team surface expanded.

Payoff

Shipped MVP in 8 weeks instead of 20 and secured integration commitments before competitors moved.

02.

Capability transfer as a deliverable

Chose

Embedded documentation, pairing, and decision records into delivery scope.

Over

Fast implementation with consultant dependency.

Cost

Higher upfront time investment during engagements.

Payoff

Client teams operated independently after handoff and systems kept improving without external bottlenecks.

03.

Custom flight stack for vertical autonomy

Chose

Built a bespoke control stack for near-wall precision and safety.

Over

General-purpose enterprise drone platforms.

Cost

Longer R&D cycle and higher hardware prototyping spend.

Payoff

Met stability and safety requirements critical to industrial facade operations.

Execution_Logic

Operating Principles

01. Define the System Boundary First

Set interfaces, failure modes, and ownership before implementation to remove recurring incident classes.

02. Tie Technical Work to Business Metrics

Major engineering decisions must map to measurable outcomes: reliability, cycle time, conversion, retention, or cost.

03. Favor Reversible Decisions Early

In high-uncertainty phases, optimize for reversibility and speed; harden only where evidence justifies complexity.

04. Make Trade-offs Explicit

Document alternatives, constraints, and expected impact so teams can reason clearly and iterate safely.

05. Build Teams That Can Replace You

Durable systems scale both software throughput and decision quality across the organization.

Organizational_System

Team Leverage

Leadership_Engine

Scaling
Capability

I treat team capability as part of the architecture: clearer decisions, faster execution, and fewer single points of failure.

01

Shared Context by Default

ADRs, runbooks, and architecture reviews make reasoning reusable. Critical knowledge is distributed, not concentrated.

02

System Ownership Mindset

Coaching moves engineers from ticket-level fixes to root-cause elimination across services.

03

High-Velocity, High-Confidence Delivery

Typed contracts, CI/CD guardrails, and test discipline enable frequent releases without heroics.