Uploaded April 2026 | Updated September 2026, 3 weeks ago
Check out Protegrity here: https://ul.live/protegrity_yt
I had a great time chatting with James Rice about how to let AI use our sensitive data safely by baking security right into the data itself instead of relying on the old perimeter stuff. We also got into why traditional tools like DLP can sometimes break AI workflows, and we even sneaked in a quick chat about the future of quantum computing.
What we talk about:
The AI Tug-of-War:
How we're dealing with the massive conflict between security teams trying to limit exposure and AI teams needing that exact same data to drive business value.
Baking It In:
Why we need to stop just building walls around our systems and start embedding security directly into the data itself using things like tokenization and anonymization.
Semantic Guardrails:
What these guardrails actually are and how they act like a real-time bouncer to keep AI conversations on-topic and stop the models from accidentally leaking secrets.
The DLP Problem:
I bring up my old days working with DLP in 2005, and we get into why traditional security tools accidentally starve AI systems of the information they need to produce good outcomes.
Quantum Cryptography:
A sneak peek into what James is talking about at RSA and Blackhat, specifically how quantum computing is going to force us to ditch legacy cryptography by 2030.
00:00 - Introductions
01:43 - The unique approach to AI data security
04:41 - Practical examples and getting started
09:20 - Clarifying protection methods and semantic guardrails
11:22 - Comparing this approach to traditional DLP
15:27 - Customer use cases and implementation timelines
20:52 - Upcoming conferences and future sneak peeks
Subscribe to the newsletter at:
danielmiessler.com/subscribe
Join the UL community at:
danielmiessler.com/upgrade
Follow on X:
https://x.com/danielmiessler
Follow on LinkedIn:
linkedin.com/in/danielmiessler
Check out Protegrity here: https://ul.live/protegrity_yt
I had a great time chatting with James Rice about how to let AI use our sensitive data safely by baking security right into the data itself instead of relying on the old perimeter stuff. We also got into why traditional tools like DLP can sometimes break AI workflows, and we even sneaked in a quick chat about the future of quantum computing.
What we talk about:
The AI Tug-of-War:
How we're dealing with the massive conflict between security teams trying to limit exposure and AI teams needing that exact same data to drive business value.
Baking It In:
Why we need to stop just building walls around our systems and start embedding security directly into the data itself using things like tokenization and anonymization.
Semantic Guardrails:
What these guardrails actually are and how they act like a real-time bouncer to keep AI conversations on-topic and stop the models from accidentally leaking secrets.
The DLP Problem:
I bring up my old days working with DLP in 2005, and we get into why traditional security tools accidentally starve AI systems of the information they need to produce good outcomes.
Quantum Cryptography:
A sneak peek into what James is talking about at RSA and Blackhat, specifically how quantum computing is going to force us to ditch legacy cryptography by 2030.
00:00 - Introductions
01:43 - The unique approach to AI data security
04:41 - Practical examples and getting started
09:20 - Clarifying protection methods and semantic guardrails
11:22 - Comparing this approach to traditional DLP
15:27 - Customer use cases and implementation timelines
20:52 - Upcoming conferences and future sneak peeks
Subscribe to the newsletter at:
danielmiessler.com/subscribe
Join the UL community at:
danielmiessler.com/upgrade
Follow on X:
https://x.com/danielmiessler
Follow on LinkedIn:
linkedin.com/in/danielmiessler
