I'm a founder-level operator. I build the systems that turn high-stakes chaos into predictable growth.

I'm Harris Gordon. I'm a two-time venture-backed founder and product leader. I find and fix the systemic failures that stall scaling companies.

My track record:saving a $900k ARR account from churn, unlocking a $2.2M pipeline by killing an unprofitable segment, and building a 0-to-1 venture to a signed enterprise pilot in 11 weeks.

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The Proof: Case Studies

Three playbooks for turning chaos into growth.

The Crisis Manager

My Playbook

  1. Own the failure to de-escalate.
  2. Build a data mirror to replace opinions with facts.
  3. Partner with the customer to build the fix.

The Result

Saved a $900k ARR account from churning

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The Situation

Our largest account was about to churn. A clinical AI was generating false patient data, and our broken release process had destroyed all trust.

My Intervention

  1. Triage: I took immediate ownership on customer calls. I used radical candor to absorb the chaos and turn a hostile situation productive.
  2. The Mirror: I built a V1 Health Dashboard that became the single source of truth. It forced data-driven conversations about the platform's real-time failures.
  3. The New Treaty: Armed with data, I led the negotiation to redesign our release process. We co-created a new protocol with a mandatory customer "Go/No-Go" before every production release. This gave them the control they needed to trust us again.

Key Results

  • Saved a $900k ARR account from churning.
  • Created a new Enterprise Release Protocol now used to de-risk all high-stakes accounts.
  • Turned a churn risk into our most important design partner for stability.

The Turnaround Operator

My Playbook

  1. Diagnose the disconnect between strategy and reality.
  2. Build a coalition of the sane with operational leaders.
  3. Architect the V1 systems that make chaos obsolete.
  4. Use a crisis as the catalyst for systemic change.

The Result

Unlocked 20%+ of GTM & Success team capacity to focus on a $2.2M enterprise pipeline

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The Situation

A YC-backed, Series A client was in crisis. A 'move fast and break things' culture created a breaking product, a burned-out team, and a P0 churn risk with their largest account.

My Intervention

  1. Diagnosis: The root cause was a leadership failure. The company had a "hype-driven" strategy with no rational system for prioritizing work.
  2. System Architecture: I built a new GTM operating system from the bottom up. It included a data-driven "Account Health" framework, a "GTM Blocker Triage" ritual to align Sales and Engineering, and a "P0 Incident Response" playbook.

Key Results

  • Unlocked 20%+ of GTM & Success team capacity to focus on a $2.2M enterprise pipeline.
  • Cut reactive "squeaky wheel" fire drills by over 50% in two weeks.
  • Shipped the V1 of a new company operating system for making data-driven strategic trade-offs.

The Venture Builder

My Playbook

  1. Invalidate the thesis fast with real customers.
  2. Diagnose the true "hair-on-fire" problem.
  3. Architect a compliant, first-principles solution.
  4. Build the full-stack MVP to prove viability.

The Result

Secured a formal pilot agreement with a major multi-site operator in 11 weeks

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The Situation

A YC-backed, Series C client started a 'Work Trial' to build a new labor marketplace. The initial concept was unvetted and the target market was undefined.

My Intervention

  1. Diagnosis: I conducted 25+ customer interviews that invalidated the initial idea. I found the real "hair-on-fire" problem for daycare directors: a crippling staffing crisis caused by regulatory friction and high turnover.
  2. System Architecture: I designed a new, compliant "On-Demand Floater" model from scratch. I acted as the solo DRI to build the entire operational infrastructure: legal entity, insurance, and all V1 GTM and onboarding playbooks.

Key Results

  • Diagnosed the true "hair-on-fire" problem in 25+ interviews.
  • Architected a fully compliant operational model in a complex regulatory maze.
  • Secured a formal pilot agreement with a major multi-site operator in 11 weeks.

My AI-Native Operating System

I developed a repeatable system for building with AI to deliver high-quality work under pressure. It de-risks development and turns a stateless LLM into a strategic partner. My work on the YesAnd Music project is the proof.

The Core Pillars of My AI-Native Development System

My Playbook

  1. Establish a persistent context with version-controlled docs.
  2. Force adversarial thinking by making the AI argue against its own plans.
  3. Extract learning from failure and inject it into the next attempt.

The Result

De-risked development by forcing the AI to anticipate failure

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The Situation

Building complex systems requires more than just technical skill. Traditional workflows break under pressure.

My Intervention

  1. The External Brain: I use version-controlled docs as a persistent brain for the AI. This kills context drift and keeps the AI aligned with the project's ground truth.
  2. The Red Team Pre-Mortem: I force the AI to argue why its own plans will fail. This surfaces hidden risks and edge cases before implementation begins.
  3. The Post-Mortem Time Machine: When the AI fails, I make it extract the key insight it wishes it had at the start. I then inject this wisdom into a clean slate, turning every failure into a lesson.

Key Results

  • De-risked development by forcing the AI to anticipate failure.
  • Solved context-drift with persistent, version-controlled documentation.
  • Turned a stateless LLM into a strategic partner through systematic analysis.

YesAnd Music: A Case Study in AI-Native Development

My Playbook

  1. Define technical requirements when no existing solution meets your needs.
  2. Apply systematic AI-assisted development using the three-pillar methodology.
  3. Build with documentation and modularity from day one.
  4. Create interfaces that others can understand and extend.

The Result

Architected a complete, hybrid Python-to-C++ system with real-time, thread-safe communication

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The Situation

I wanted a tool to get musical ideas out of my head and into my computer faster. Nothing existed. So I built it myself using my AI-native system.

My Intervention

  1. The External Brain: I used version-controlled documentation to ensure my AI partner understood the full scope of a hybrid Python-C++ audio project.
  2. The Red Team Pre-Mortem: I forced the AI to argue against the proposed architecture, which identified critical failure modes in the real-time communication bridge before we wrote any code.
  3. The Post-Mortem Time Machine: I injected learnings from my past music tech projects into this clean slate, allowing the AI to avoid known pitfalls from day one.

Key Results

  • Architected a complete, hybrid Python-to-C++ system with real-time, thread-safe communication.
  • Built a professional-grade C++ audio engine for intelligent MIDI transformations.
  • Delivered a robust natural language command interface, turning a personal workflow into a scalable tool.