Over the past two years, advances in autonomous AI agents have reshaped how organizations approach complex decision-making. The author previously wrote exclusively for Stankevicus on Holo Sail: Redefining Secure Communication in the Era of Cyber Warfare, Autonomous AI’s Spellbook and the Absent Necromancer, The AI Risk Repository, Filter Bubbles, and Isaac Asimov In March 2023, OpenAI released GPT-4, vastly expanding the capabilities of generative language models. Soon after, open-source projects like Auto-GPT sparked widespread interest by demonstrating how multiple AI agents could collaborate autonomously to complete intricate tasks. Microsoft responded by unveiling Copilot, a generative AI service for its Office suite, streamlining teamwork through AI-assisted editing and data analysis. Meanwhile, Google added generative AI enhancements to its Workspace platform, amplifying the role of AI-driven solutions in everyday workflows. Against this backdrop, the 9-HI platform exemplifies a new paradigm: cutting-edge AI agents that work alongside human expertise, magnifying rather than supplanting it, to guide technology selection, risk mitigation, and project innovation.
The author was privileged to sit down for an exclusive Stankevicus interview with Dave Mroczka, President of AI Strategy Corp. and principal architect behind 9-HI, to discuss the company’s mission, its groundbreaking technology, and the broader implications of AI and collaborative decision-making in today’s AI-driven world. For Dave Mroczka’s vision on AI and collaborative decision-making, cutting-edge AI does not need to supplant human expertise; it can magnify it. His company’s 9-HI platform embodies his philosophy by combining five GPT-enabled AI “co-pilots” with expert human collaboration. Developed initially to strengthen America’s industrial base and streamline technology development within the U.S. Department of Defense (DoD) ethical framework, 9-HI is now poised to transform commercial enterprises and educational settings. The platform supports a broad array of user-centric applications, from risk identification in supply chain management to proposal generation and organizational knowledge capture.
The following interview was conducted on February 19th, 2025, and has been edited for clarity and brevity.
Dr. Cowin: Hello, Dave. First, would you like to introduce yourself and your company to my readers?
Dave Mroczka: My name is Dave Mroczka, and I serve as President and CEO of AI Strategy. We have developed a software platform called 9-HI to facilitate human-AI collaborative decision-making. Our company is technically still a startup, launched in 2020 during the COVID-19 pandemic- an unusual time to begin, but it drew considerable attention to remote software tools. 9-HI was initially envisioned to guide people through complex projects, focusing on what the U.S. Department of Defense (DoD) calls the “valley of death,” where 90% of new technologies fail to reach operational use. We secured $5.6 million in funding through the Small Business Innovative Research (SBIR) process. Over the last year, we launched a fully functional collaborative platform applicable to many fields beyond DoD—from biomedical research to investment management.
My background includes mechanical engineering, manufacturing engineering, significant software development experience, and an MBA. Before founding AI Strategy, I ran the largest privately owned test lab in the country for the DoD, from 2006 to 2013. During that time, I observed first-hand how a structured decision-guidance system could benefit numerous organizations, prompting the creation of 9-HI.
Dr. Cowin: The physicist and author David Deutsch asserts that explanations are fundamental to the universe, possessing limitless scope and transformative power. Their continual improvement is the guiding principle of science and all successful human endeavors. Do you agree there is no upper limit to human understanding and achievement? Why or why not, and how does your company fit into this broader context?
Dave Mroczka: I strongly agree with Deutsch’s premise on the boundless nature of human understanding. The creation of 9-HI stemmed from frustration over project failures, prompting me to capture and analyze data from both successful and unsuccessful undertakings. Over about 25 years, this approach evolved into a decision-guidance system.
Early in my career, I worked for a large Japanese materials conglomerate. Their R&D philosophy was remarkable: they continuously funded engineering and scientific work, shelving prototype-ready technologies if market conditions were unfavorable. My task was to select which of their 700 shelved innovations could be commercialized. This experience illustrated the importance of aligning technologies with suitable applications and resources methodically. After 9/11, I transitioned to the defense sector, confirming that a comprehensive guidance system could assist diverse organizations in navigating complex technology development. I believe that as we continually push boundaries, we discover new frontiers of knowledge and capability. Our brain’s efficiency – and the adversity we overcome – fuel learning and innovation.
Dr. Cowin: Our human brain is incredibly efficient, functioning on about 20 watts of power, and I suspect replicating it via massive computational resources may not be optimal. Would you say your platform seeks an AI “companionship” model rather than a hostile takeover?
Dave Mroczka:: Absolutely. We always viewed 9-HI as a companion that augments human expertise, not as a platform that replaces people. The “HI” in 9-HI stands for “human intelligence.” Our goal is to provide structured insights, enabling users to make more informed decisions. We plan to incorporate more AI capabilities over time, yet we prioritize human oversight.
Dr. Cowin: As an educator, I see new potential for preparing the future workforce. I believe humanity is in the ‘age of algorithms.’ How did you and your team conceive the 9-HI platform, and what core challenges in technology development sparked its creation?
Dave Mroczka: I did not initially set out to build a formal guidance system. Rather, I wanted to reduce waste in large-scale projects and enhance success rates for million-dollar investments. By meticulously collecting data and observing patterns, I recognized we needed a universal framework that surpassed the typical ad-hoc approach of consulting firms. Our resulting algorithm applies across various industries, helping individuals and organizations systematically identify the steps needed for successful technology deployment. In essence, 9-HI is a universal decision-guidance platform that is equally suited to government, business, and research.
Dr. Cowin: On the topic of data, where do you source your datasets? Too little data can lead to “overfitting,” and too much or biased data can also pose major problems. What constitutes the right kind of data for 9-HI?
Dave Mroczka: We purposefully integrate human expertise. While other companies aim for purely algorithmic solutions, 9-HI is a human-AI collaborative platform. Our methodology prioritizes reliability and subjects all data to a structured, human-in-the-loop approach. Subject matter experts contribute top-level direction, which then informs how we incorporate other data layers, such as vetted databases and generative tools. We employ four data layers in a hierarchical design, with human insights at the pinnacle. This structure mitigates bias and ensures data relevance.
Dr. Cowin: There’s a saying: “Wisdom is born of struggle and suffering.” AI systems do not experience adversity like humans, and can lack the embodied cognition that fosters practical wisdom. What is your perspective on this distinction between wisdom and intelligence?
Dave Mroczka: AI inherently lacks the physical experiences and hardships that shape human wisdom. We can encode human expertise into AI models to form “intelligent” systems, but the deeper wisdom that involves common sense and lessons from hardship remains a distinctly human attribute.
Dr. Cowin: In your system, you reference a two-tiered power-set guidance framework. How does this mathematical structure facilitate practical risk identification and mitigation for diverse technologies?
Dave Mroczka: I realized early on that a product moves from a base technology through a team and relevant stakeholders before reaching a market application. I developed a standardized approach, which flags essential elements in each of a set of nine categories, which has repeatedly proven effective. By systematically filling these “power set” boxes, 9-HI can pinpoint why a project may be struggling and suggest remediation strategies.
Dr. Cowin: Do you believe this framework could have applications in teaching?
Dave Mroczka: Yes. We’ve had conversations with senior leaders at institutions such as the US Army. They connected us with their Training and Doctrine Command(TRADOC), who see the potential for embedding such a system in military education. Likewise, it can benefit broader academia by providing a systematic way to guide complex problem-solving. We must balance this integration with sound pedagogical practices, recognizing that younger learners benefit from open-ended exploration and psychological safety.
Dr. Cowin: You mentioned five GPT-enabled agents – Orion, Scorpius, Cassie, Hercules, and Libra – working in tandem with human experts. What do you see as the major advantages and possible pitfalls of this human-AI “teaming” approach?
Dave Mroczka: We aim to simplify how people engage with multiple AI models by categorizing them into distinct “personas,” each responsible for a specific dimension of decision-making.
- Orion addresses the people and expertise required.
- Scorpius focuses on risk.
- Cassie pinpoints critical success factors.
- Hercules recommends specific solutions.
- Libra evaluates evidence.
Although we have over a dozen algorithms under the hood, we filter them through five personas like a persona-structured engineered prompt. This approach helps users recall which agent handle which area of concern. The benefits include structured guidance, improved resource allocation, and in-depth risk assessment. The potential drawback is that too much AI assistance may encourage minimal human effort; we must ensure users remain actively engaged, offering their own creativity and expert judgment. Many of the prompts from our AI Agents are presented in a format that actually challenges their human collaborators to think on a higher level. It’s a delicate balance but one that we seem to be managing well at this point.
Dr. Cowin: Can the broader public try out 9-HI?
Dave Mroczka: Yes. Anyone can sign up at 9-HI for a two-month free trial. After that, the current rate is $599 per user per year for unlimited usage, though pricing structures may evolve. We also plan special models for educational institutions – acknowledging budget constraints and the potential benefits of academic partnerships. We’re exploring collaborations with university networks and specialized consortia to create pilot programs that test 9-HI’s utility in educational contexts. Insights from these pilots will help refine our platform to serve academia, particularly those seeking to integrate a systematic decision guidance framework.
Dr. Cowin: Your platform has been employed for U.S. Army demonstration projects and submitted to the Joint Rapid Acquisition Cell (JRAC). What unique demands do defense organizations place on technology-scouting and risk-management software?
Dave Mroczka: The JRAC addresses top-priority technology needs across the DoD. We recently developed a disruptive “scouting” approach that identifies suitable technologies before formal contracting. Traditionally, the DoD would award contracts without fully grasping what they are financing, leading to cost overruns and inefficiencies. Our program finds relevant solutions, assesses their fit with DoD requirements, and maps out risk-assessed pathways that consider time, money, and resources needed for success. This approach benefits all parties by providing visibility and clarity from the outset. While some organizations might want exclusivity on emerging solutions, we have already demonstrated that early scouting accelerates the entire process – compressing what can take 18–24 months into mere days.
Dr. Cowin: Speaking of scaling, with ever-growing demands for computational power – from GPU clusters to specialized AI chips – how do you view computing hardware’s current and future role in powering next-generation AI?
Dave Mroczka: I see a dual track of algorithmic innovation and hardware advancement. While we can optimize large language models to run faster using existing GPUs, hardware must also continue improving in raw computational capacity. Each innovation prompts further growth in the other area. We have not yet reached a plateau in hardware performance, and breakthroughs in specialized chips or emerging paradigms will continue to shape AI’s capabilities.
Dr. Cowin: Finally, what is your perspective on quantum computing’s potential for large-scale data modeling and cryptographic challenges? Could this be as transformative as some predict?
Dave Mroczka: Quantum computing is already in limited use, but its reliability is still questioned. I believe, we lack a complete scientific understanding of the deeper parameters enabling stable quantum computation. We currently approach quantum computers more as engineers than as scientists, leveraging results without fully understanding them. True breakthroughs in quantum hardware and theoretical knowledge could revolutionize data modeling, cryptography, and AI, but that horizon may still be distant. Meanwhile, I agree that advanced intelligence, while achievable in computational terms, remains different from true consciousness or the human experience.
Conclusion: Applied Nicomachean Ethics and 9-HI
“Plainly, then, practical wisdom is a virtue and not an art (Aristotle NICOMACHEAN ETHICS Complete, Translated by W. Ross.)
In sum, the distinction between intelligence and wisdom highlights the unique place of phronesis, which hinges on lived experience and moral insight. The word itself stems from Greek phrónēsis (φρόνησις), often translated as “practical wisdom” or “prudence,” and was carried into Latin as phronēsis. In the author’s opinion, the concept of phronesis remains highly relevant in contemporary ethical and professional contexts because it underscores the importance of integrating moral discernment and situational awareness in AI decision-making processes. Although AI can replicate aspects of cognitive processing, it cannot authentically mirror the lived experience-driven growth that deepens human judgment. By placing human expertise at the forefront, 9-HI melds the precision of algorithmic processing with the nuance of ethical deliberation. The author summons Ovid for the article’s final words.
‘All other creatures look down toward the earth, but man was given a face so that might turn his eyes toward the stars and his gaze upon the sky.’
Ovid, Metamorphoses
Glossary of Key Terms
- AI (Artificial Intelligence): Simulation of human intelligence in machines designed to learn, reason, and solve problems.
- Generative AI: Systems that create new content or ideas, drawing upon patterns from existing data.
- GPU (Graphics Processing Unit): A specialized electronic circuit designed to accelerate the processing of images, videos, and complex computations.
- Human-AI Collaboration: A partnership model where AI provides insights and humans maintain control over final decisions.
- Joint Rapid Acquisition Cell (JRAC): A DoD entity focusing on urgent, high-priority acquisition needs.
- Large Language Models (LLMs): AI models trained on extensive text corpora to process and generate language.
- Neural Networks: Computing systems loosely inspired by biological neural networks, used to model complex patterns.
- Power Set Guidance Framework: A structured approach that analyzes multiple aspects of product, team, and market to identify risks and opportunities.
- Quantum Computing: A computing paradigm leveraging quantum phenomena, such as superposition and entanglement, to solve certain classes of problems more efficiently than classical computers.
- Small Business Innovative Research (SBIR): A program enabling small businesses to engage in federal R&D with commercialization potential.
- US Army Training & Doctrine Command (TRADOC): A major command of the United States Army headquartered at Fort Eustis, Virginia. It is charged with overseeing the training of Army forces and the development of operational doctrine.
- Valley of Death (Technology): The high-failure gap between proof-of-concept research and a viable commercial or operational product.
This article was written by Dr. Jasmin (Bey) Cowin, Associate Professor and U.S. Department of State English Language Specialist (2024-2025). As a columnist for Stankevicius, she writes on Nicomachean Ethics: Insights at the Intersection of AI and Education. Connect with her on LinkedIn.
