Founding Team

People Behind Mindful Machines

About Fellows

Architecture
meets application.

Foundation Fellows are senior practitioners whose careers have confronted the real-world consequences of unstructured, ungoverned intelligence. They bring domain authority, institutional relationships, and deployment experience that ground the Foundation’s architectural principles in operational reality.

Fellows are active architects of responsible deployment — contributing to governance framework development and cross-sector adoption pathways worldwide.

The gap between principle and deployment is not philosophical. It is institutional. Fellows close that gap.

Current Fellows

06 Active · Accepting Applications

Max Michaels

Founder & CEO

As the Founding CEO, Max Michaels guides the translation of mindful architectures into scalable real-world applications in manufacturing, energy, and infrastructure — domains where resilient, accountable intelligence is not aspirational but mission-critical.

Strategist and institution builder with graduate studies at MIT and senior executive experience at IBM, AT&T, and Cisco. Eight-year thought partner to Dr. Rao Mikkilineni as the ideas behind Mindful Machines evolved from architectural insight into institutional and commercial vision.

His work has consistently centered on how transformative technologies scale without eroding coherence, accountability, or institutional trust. As Founding CEO, he guides global strategy, shaping partnerships and translating the principles of Mindful Machines into deployable frameworks and institutional standards.

Rao Mikkilineni, Ph.D

Inventor & Chief Scientist

Dr. Rao’s expertise sits at the intersection of technology engineering, cybersecurity, and philosophy — bringing deep technical and scientific knowledge to the Foundation’s mission of governed, coherent AI architecture.

Pioneer in Information Technology and AI whose work has helped define the transition from computation as automation to computation as governed agency. Inventor of the Mindful Machine Architecture — a foundational framework integrating the Digital Genome, Autopoietic Control Planes, Structural Knowledge, and Meta-Cognitive Governance.

Distinguished Professor at Golden Gate University and Dominican University. Leads the scientific direction of the company and development of its core technical assets, including the Mindful Reliability Reference Stack. Based in Silicon Valley with enduring professional ties in Japan and France.

Ben Hendrick

Chief Information Security Officer

Ben’s expertise sits at the intersection of cybersecurity, cloud computing and business development — bringing deep institutional knowledge of global innovation ecosystem to the Foundation’s mission of governed, coherent AI architecture.

Technology disruptions have defined Ben Hendrick’s career, and leading through them has become his signature. Over 30+ years, he has helped enterprises move across successive eras of change, from mainframes and PC networks to data centers, cloud, Zero Trust, and now AI-powered security. In senior roles at Novell, Dell, IBM, Microsoft, and Ryder, he has led teams, built offerings, and delivered large-scale transformations for some of the world’s most demanding organizations.
Today, Ben is applying that experience to one of the toughest frontiers in technology: using AI to solve complex IT security challenges. As Director of Security at Ryder System, he leads Security Architecture & Engineering across operations, architecture, network, cloud, and M&A security. His focus is simple: turn emerging technology into practical protection, stronger resilience, and measurable business outcomes.

S. V. Prasad

Chief Revenue Officer, Asia

At Mindful Machines, Prasad is responsible for building strategic customer relationships, developing the Asia partner ecosystem, and bringing the company’s governance-native computing platform to enterprises deploying autonomous and agentic AI. Combining deep technical expertise with decades of customer-facing leadership, he is passionate about helping organizations adopt AI that is not only intelligent, but also governed, explainable, and worthy of trust.

Prasad is Chief Revenue Officer, Asia, at Mindful Machines, where he leads the company’s growth strategy, enterprise partnerships, and market expansion across Asia. He works closely with customers, technology partners, and academic institutions to help organizations transition from AI experimentation to governance-native AI, where trust, accountability, and operational resilience are designed into intelligent systems from the outset. 

With more than three decades of international experience, Prasad has built and led technology initiatives across Japan, India, the United States, Israel, Finland, and other global markets. His career spans telecommunications, embedded systems, cloud technologies, medical diagnostic equipment, enterprise software, business development, and solution engineering. He has held senior leadership positions in Japan, including serving as Associate Vice President and Head of Pre-Sales at Tech Mahindra, where he helped global enterprises navigate large-scale digital transformation and technology modernization. He holds an M.Tech in Electronics and Instrumentation from the Indian Institute of Science (IISc).

Patrick Kelly

Director of Engineering

Patricks expertise sits at the intersection of technology engineering, and cybersecurity, and financial strategy — bringing deep technical knowledge to the Foundation’s mission of governed, coherent AI architecture.

Approaches engineering as the disciplined translation of architecture into reality. Focuses on the harder problem of how to construct systems whose internal logic is explicit, whose behavior is traceable, and whose evolution does not compromise integrity.

As Director of Engineering, leads development of core technical frameworks including structured memory systems, graph-based substrates, and integrated Self-Model and World-Model architectures. Ensures the Digital Genome, Meta-Cognitive Governance, and Autopoietic Control are encoded into executable, auditable systems — not treated as abstractions.