[ About wallow ]

Building intelligence where complexity hides.

Wallow is the Friction Intelligence™ platform that transforms how organizations see, interpret, and act on the signals that shape delivery performance. Designed for high-performing engineering and product teams, Wallow connects data from tools like Jira, Slack, GitHub, CI/CD systems, documentation, and communication patterns—turning fragmented operational activity into a unified, real-time understanding of delivery friction and organizational flow.

Instead of reacting to issues once they appear, Wallow reveals the hidden patterns, risks, behaviors, and systemic slowdowns that impact velocity long before they escalate.

[ My Role ]

At Wallow, I help redefine how organizations see, sense, and solve delivery friction—turning every signal into intelligence, and every insight into forward motion.

At Wallow, I lead AI programs that fuse Generative AI, Agentic AI, organizational intelligence, and multi-tool signal analysis to help enterprises shift from reactive operations to proactive, predictive delivery. My work focuses on transforming how teams interpret operational friction—elevating it from hidden slowdown to a strategic asset for alignment, acceleration, and continuous improvement.

In this role, I architect and guide the development of adaptive AI systems that detect, correlate, and predict friction signals across Slack, Jira, GitHub, CI/CD pipelines, documentation, and communication patterns. These systems surface early delivery risks, automate knowledge transfer, reveal cross-tool behavioral patterns, and convert operational noise into actionable insight—strengthening Wallow’s mission of building an autonomous intelligence layer for engineering organizations.

Beyond the technology, I focus on culture. I collaborate with cross-functional leaders, engineers, and product strategists to scale AI adoption responsibly—embedding transparency, trust, and human-centered design into every workflow. The result: organizations that operate with greater speed, resilience, predictability, and collective intelligence, where technology doesn’t replace human performance—it amplifies it.

[ strategic outcomes ]

Strategic Outcomes

AI Signal Intelligence Framework

Designed and deployed a cross-tool AI framework that detects and interprets delivery friction across engineering ecosystems—correlating signals from Jira, Slack, GitHub, CI/CD pipelines, and operational workflows into a unified model of delivery risk, predictability, and flow.

Organizational Intelligence Activation

Enabled enterprise teams to operate with shared intelligence by linking operational signals to decision pathways—transforming unstructured communication, commits, tickets, and behavioral patterns into real-time visibility that improves coordination and accelerates execution across business units.

Human-Centered Automation

Built automation systems that integrate AI-driven precision with human oversight—reducing manual reporting, eliminating noisy workflows, and strengthening transparency, accountability, and trust in autonomous decision-support systems.

Enterprise Alignment & Delivery Clarity

Led multi-team transformation efforts that aligned engineering, product, and leadership around a predictive delivery model—improving responsiveness, reducing uncertainty, and reinforcing organizational confidence in AI-powered flow management.

“John’s vision shaped Wallow into more than a product—it became a movement toward clarity, intelligence, and human-centered performance. His ability to translate AI strategy into measurable impact elevated how teams work, learn, and lead.”

— Charles Polanco, President & Founder, Wallow

AI → Signals → Intelligence → Impact

Stage 01

Stage 01 — Autonomous Signal Detection

Engineered agentic AI models that autonomously detect, classify, and interpret delivery friction across multi-tool ecosystems—including Jira, Slack, GitHub, CI/CD pipelines, PR reviews, incident threads, and communication patterns.
This stage transforms raw operational noise into high-fidelity signals that expose risks long before they materialize.

Stage 02

Intelligence Unification

Unified product, engineering, and analytics data into a shared intelligence graph—correlating behavioral, technical, and workflow signals into a single operational truth.
This enables real-time delivery forecasting, cross-team pattern recognition, and a continuously updated model of organizational flow.

Stage 03

Collaborative Intelligence & Trust

Built responsible AI frameworks that seamlessly balance autonomous recommendations with human judgment—embedding transparency, explainability, and cross-functional accountability into every decision layer.
This stage operationalizes trust, turning AI into a collaborative partner, not a black box.

Stage 04

Measurable Operational Impact

Delivered quantifiable improvements in delivery precision, alignment, cycle predictability, and decision velocity—helping organizations move from reactive fire-fighting to proactive delivery intelligence.
This stage shifts enterprises from isolated workflow metrics to system-wide improvement, enabling teams to accelerate execution with clarity and confidence.

[ the journey ]

A disciplined ascent through intelligence, design, and human clarity.

Inclusions

I combined data science, design systems, and behavioral understanding to build intelligence that not only detects friction, but interprets intent, context, and hidden patterns that shape how work actually moves.
My focus was on creating AI systems that:

  • listen before they act

  • learn continuously

  • guide teams toward decisions rooted in alignment, not urgency

This stage reinforced something essential: intelligence is most powerful when it disappears—when it becomes part of the environment instead of the burden.
The outcome isn’t smarter dashboards; it’s smarter teams.
Not more automation; but more human progress.

Exclusions

At Wallow, I learned that clarity isn’t achieved through louder alerts, denser dashboards, or more aggressive monitoring. Clarity is an outcome of intention, not instrumentation.

True intelligence is not surveillance.
It is reflection, context, and meaning.

The goal was never to automate leadership or replace judgment.
The goal was to illuminate what matters—and remove what doesn’t.

This meant excluding approaches that:

  • treat data as a substitute for empathy

  • confuse activity with progress

  • amplify noise under the guise of transparency

Insight without humanity becomes distortion.
Progress without people becomes regression.

Wallow taught me that the future of intelligent work is not more AI—
it’s better alignment between people, intelligence, and decisions.