Pittsburgh TechFest 2026

Somewhere in every organization, someone is using an AI tool that nobody signed off on. They're doing this because it works, and because waiting for permission wasn't an option. We'll shine a light on the idea that many individuals are keeping some of the greatest value to their organizations and their career prospects hidden out of sight, due to fear of being caught doing something they're "not supposed to be doing".


This is NOT a playbook for circumventing AI acceptable use policies, but it IS a session that flips the usual "Shadow AI is a security risk" conversation on its head. We'll unpack what it actually looks like to move from quiet, unsanctioned AI use to visible, trusted leadership on AI adoption, and why the people who make that move first are becoming indispensable to their organizations.


Expect to learn from real-world experiences, gathering insights from an IT services CEO who has personally worked alongside individuals in a wide variety of industries in our region to bring AI usage out of the shadows. Employees from both technical and non-technical backgrounds who became a force multiplier for their organizations, and opened up a whole new frontier of career opportunities for themselves in the process.

The product leader's job doesn't get harder because of scale; it gets harder because the job changes. And now AI has quietly rewritten the job description and forgotten to tell anyone.
When anyone can generate a 20-page strategy doc in five minutes, knowledge stops being the moat — beautiful, fluffy documents nobody reads, and a creeping anxiety that "anybody can do this job now." The tool commoditized knowing. It didn't commoditize judgment.
In this talk, I'll make the case that the modern product leader is three people at once: a strategist who knows where to point the tool, a systems builder who designs how the system decides and moves, and a customer whisperer who spends the time AI gives back getting closer to the people the dashboards can't see. Drawing on how we've upleveled our operating muscle at k-ID — where all our management and operational tools are wired together, 40% of the team has built their own agents, and our CEO shipped an end-to-end customer product in 20 minutes with one click — I'll show what each of those three roles looks like when speed is abundant and judgment is the scarce resource.
Speed is the vehicle. Judgment is the driver.

It only takes ½ of a “drop” of venom from an Inland Taipan snake to kill a five-ton elephant. It doesn't take a flood of venom to be lethal. It takes one bite, from one source, at the wrong moment.


External data works the same way. A single bad source flowing into an AI system can trigger the same kind of damage: hallucinations, bias, and decisions built on a foundation no one should trust. And unlike a snakebite, you often don't see it coming until the outcome is already wrong.


External data is nearly a trillion-dollar global market, yet the industry still has no reliable antivenom - no consistent standard for verifying where data comes from, whether it can be trusted, or whether it's fit for the system consuming it.


Andy Hannah, CEO of Blue Street Data, has spent his career building the infrastructure to change that. In this talk, he'll unpack the antidote most AI strategies are missing, and what it takes to keep the poison out before it ever reaches your models.
The payoff isn't just safer AI. It's the trust and harmony between people and machines that only comes when you know exactly what's flowing through the system.