This as-told-to feature recounts the professional journey of Barry Duong, who currently serves as the lead artificial intelligence strategist for public equities at the forward-thinking professional services AI startup Hebbia. Within this organization, Duong leads a specialized team dedicated to designing original prompt systems and collaborating directly with financial institutions to integrate cutting-edge AI solutions into their everyday operations. Prior to stepping into the realm of artificial intelligence, Duong cultivated a distinguished career in finance, having held prominent positions including portfolio manager at the well-known hedge fund Balyasny Asset Management, analyst at Citadel, and associate at New Mountain Capital. The insights and reflections he shares here, as conveyed to Business Insider correspondent Reed Alexander, have been carefully condensed and refined for the sake of clarity and concision.
Why I Left Wall Street for AI
My most recent role within financial services placed me deeply in the world of hedge funds—a highly data-driven and competitive environment. After departing from my position at Balyasny, I found myself under a noncompete clause, which unexpectedly granted me valuable time to explore new intellectual frontiers. I used this period to immerse myself in the rapidly evolving landscape of artificial intelligence. I began experimenting with various emerging tools, including those created by stealth-mode startups still in early developmental phases. What I encountered was far more transformative than I could have imagined. The practical capabilities of these technologies seemed to extend well beyond incremental efficiency gains—they hinted at an entirely new paradigm of analytical reasoning and operational enhancement.
As an investor by training, one is always inclined to think several steps ahead, to envision where industries might be heading. That mindset naturally made me contemplate the long-term potential of AI and the trajectory of its integration into finance. The more I learned, the more irresistible my curiosity became, until I could no longer relegate AI to a casual interest—it demanded my full attention. At the firms where I previously worked, some progress toward AI adoption had begun, but these initiatives were still rudimentary, particularly at the moment when ChatGPT first debuted and the field’s possibilities suddenly expanded in public awareness.
Earlier this year, I formally joined Hebbia as lead AI strategist for public equities. From the very beginning, entering the AI industry from within felt innately logical—a shift from being an external observer reacting to technological change to becoming an active participant helping shape that change.
As an AI strategist, my responsibilities are multifaceted. I guide clients through our product ecosystem, help them understand how to best utilize it, and ensure their feedback is thoughtfully incorporated into continuous development. In parallel, I focus on upskilling their teams—empowering professionals of differing levels of experience to build their own prompts, develop dynamic workflows, and embrace AI fluency. One of the elements that differentiates Hebbia from many of its peers is its holistic philosophy toward automation. Rather than viewing AI merely as a means to replace repetitive, low-value tasks, we aim to enhance performance at all professional tiers. Whether it is a junior investment banker compiling analyses or a senior managing director orchestrating strategic decisions, each professional can become better at their work through thoughtfully applied AI systems.
How Our Wall Street Insights Enhance the Work
At Hebbia, my team’s primary mission involves architecting and refining prompts on behalf of our clients—building bridges between human expertise and machine intelligence. We regularly conduct large-scale training sessions before audiences numbering in the hundreds, composed of personnel from our clients’ firms. These sessions focus on teaching employees not only how to employ existing prompts effectively but also how to design their own to meet specialized needs. On other occasions, we hold individualized sessions with senior bankers or investors, where we co-develop finely customized workflows that unlock new levels of efficiency. For example, one client might automate the construction of a complex PowerPoint deck or financial model—tasks that previously consumed hours of manual effort but can now be executed with a few lines of optimized prompting.
Our approach is iterative and nuanced. It involves multiple layers of what we refer to as “context engineering,” followed by a precise process of prompt refinement, which often resembles linguistic craftsmanship or wordsmithing. Additionally, selecting the correct AI model for any given objective is critical. Our objective is to find that ideal confluence where prompt design and model capability align in harmony, producing what we call a golden outcome—an output that maximizes accuracy, efficiency, and usefulness.
Within this workflow, human involvement remains indispensable. Success in AI isn’t solely determined by technical skill or years of experience; it relies heavily on ingenuity, adaptability, and the creativity to solve problems under dynamic conditions. My team exemplifies this ethos. Each member brings a background rooted in elite financial institutions—both buy-side and sell-side—spanning various asset classes and product specializations. Unlike purely technical professionals found in traditional Silicon Valley startups, our strength lies in our dual expertise: deep financial knowledge combined with fluency in advanced AI applications. Whether the focus is investment banking, credit analysis, or another vertical, this domain mastery ensures our AI work continuously aligns with the real-world needs of financial professionals.
What unites this diverse team is not only their skill but an authentic passion for artificial intelligence and its transformative potential. Every individual on our team is driven by a shared ambition: to lead meaningful change within finance and to collaborate closely with clients so that they can participate in—and benefit from—that change firsthand. The scale of the results we are achieving is already remarkable. Some of our most proficient users are capable of processing hundreds of thousands of pages of information within a single week. Collectively, our systems have now surpassed one billion pages processed for clients—equivalent to roughly 3,000 years’ worth of human reading and approximately 2,000 years of analytical labor.
Why Others Should Consider the Shift
Platforms like ours empower professionals to approach deal-making and complex financial operations with an unprecedented level of intelligence and strategic focus. Rather than merely increasing productivity in a mechanical sense, AI integration enables both individual employees and entire organizations to concentrate their efforts on the opportunities most likely to generate meaningful returns. Contrary to common fears, productivity-enhancing technologies do not necessarily imply fewer people will be required in the industry. Instead, they raise expectations of each professional’s capacity to output more—elevating the qualitative standard of the work itself.
Artificial intelligence is poised to reshape business practices, workflows, and functional roles across every dimension of finance. Professionals will increasingly need to master prompt engineering and, beyond that, learn to orchestrate networks of AI agents effectively. In many respects, junior analysts may soon find themselves managing semi-autonomous systems that perform analytical or administrative functions once done manually. Consequently, mid-level and senior leaders must now equip themselves to manage not only human subordinates but also AI-driven processes. It is impossible to effectively supervise someone who manages AI unless one also understands, experimentally and practically, how those systems operate.
Finance has always existed at the crossroads of art and science—a domain requiring both quantitative rigor and creative intuition. Artificial intelligence is continuing to push forward this boundary. Much remains to be explored, particularly in areas such as advanced quantitative modeling, where foundational systems may someday perform mathematical reasoning more effectively than current large language models. For now, however, we stand in an era of extraordinary possibility, where human insight and machine intelligence are converging to redefine how the financial world operates.
Those wishing to share their own experiences of how artificial intelligence is transforming their professional landscape are encouraged to reach out to Business Insider correspondent Reed Alexander at ralexander@businessinsider.com or via SMS or Signal at 561-247-5758. For utmost privacy, use a personal email account and nonwork device. Business Insider provides a detailed guide for anyone interested in contributing securely to this ongoing dialogue about the future of work and technology.
Sourse: https://www.businessinsider.com/hedge-fund-pm-leaves-wall-street-ai-startup-hebbia-2025-10
