The Tech Trek

Spencer Penn, Co founder and CEO of LightSource, joins The Tech Trek for a sharp conversation on AI native procurement, agentic workflows, and what actually happens to knowledge work as automation gets better. This episode is worth your time because it moves past lazy takes about AI replacing jobs and gets into something more useful, how work changes, where human value holds, and why procurement may be more strategic than most companies treat it.
This conversation starts with procurement, but it quickly expands into a bigger discussion about role design, change management, and the pace of AI adoption inside real companies. Spencer breaks down why some jobs get redesigned while others disappear, how AI can elevate overlooked functions, and what people should do right now if their company is behind.
In this episode
Why procurement is a strong fit for AI, especially where teams are buried in tedious process work
The difference between job automation and job elimination
Spencer’s idea of role plasticity, and why it matters more than most AI debates
Why procurement teams may become more valuable, not less, as AI improves
Practical ways professionals can start using AI before their company rolls out a formal strategy
Timestamped highlights
00:37 What LightSource does and why direct material sourcing is a high stakes AI use case
01:51 Why procurement teams spend too much time on transactional work
06:47 Which jobs get enhanced by AI, which ones get eliminated, and Spencer’s framework for role plasticity
13:44 What the next few years could look like for procurement professionals
26:18 Where to start if your company has not adopted an AI native workflow yet
30:07 How to learn more about LightSource and connect with Spencer
“AI will not replace your job. Someone who knows how to use AI will.”
A practical thread running through this episode is simple. Start using the tools now. Use foundation models for secondary work, reporting, summaries, and internal communication. Build familiarity before the workflow shift gets forced on you.
If you are interested in AI, procurement, operations, supply chain, or the future of knowledge work, follow The Tech Trek for more conversations like this.

Michael Fanning, CISO at Splunk, joins The Tech Trek for a grounded conversation on how the security leader role is changing in the AI era. This episode gets into the real tension facing modern CISOs, balancing risk without slowing the business down, hiring for technical depth over narrow credentials, and defining success in a field where perfection is not a realistic metric.
This is a practical conversation for security leaders, engineering leaders, founders, and operators trying to make sense of AI adoption inside the enterprise. Mike breaks down why security has to move from fear based messaging to business enablement, why many teams may be overlooking strong security talent hiding in adjacent technical roles, and where AI can either reduce burnout or make it worse.
In this episode
Why the CISO role is becoming more engineering driven and more tightly tied to business outcomes

Where AI creates real leverage for security teams, and where it introduces new operational risk

Why the security talent gap may be as much a hiring mindset problem as a supply problem

What actually causes burnout in security teams, beyond the usual talking points

How to think about success in security when zero incidents is not a serious metric

Highlights
1:44, The CISO role is shifting from pure protection to business enablement

7:11, AI creates leverage for defenders, but it is also accelerating the attacker playbook

9:31, The biggest AI security risks, from developer copilots to agent driven decision making

14:15, Why security teams need room to experiment with AI or risk falling behind

16:58, Only 1 percent of CISOs surveyed prioritized technology to close the skills gap

22:16, AI can reduce burnout, but only if it cuts noise instead of creating more of it

Security is about assessing risk and finding a way to say yes in a way that is responsible.
A practical idea worth taking back to your team
Look beyond candidates with formal security titles. Mike makes the case that strong engineers, SREs, and cloud practitioners often already understand the systems, access models, and infrastructure realities that matter most. Security can be taught on top of that foundation.
Link to report: https://www.splunk.com/en_us/form/ciso-report.html
Follow The Tech Trek for more conversations with leaders shaping how technology actually gets built, secured, and scaled.

What does it really take to go from engineer to CEO?

In this Tech Trek Brief, Michael White, Co founder and CEO of Multiply, shares a few of the ideas that matter most from a broader conversation on founder growth, leadership, and the shift from building things to building a company.

What stood out most is that this is not really a story about title progression. It is a story about learning to operate with more uncertainty, taking on bigger challenges before you feel ready, and realizing that leadership at the highest level starts to look a lot more like influence than execution.

What we get into

• Why growth often starts before you feel ready
• Why strong founders are pulled by a real problem
• Why founder timing matters more than people think
• Why leadership becomes influence, alignment, and conviction

Timestamped highlights

00:00 The real shift from engineer to CEO
00:18 Growth starts before readiness
00:56 Leadership changes when execution is no longer enough
01:50 The best founders are pulled by a problem
02:35 The three ideas that tie it all together
Follow The Tech Trek for more conversations on leadership, company building, and the people shaping what comes next.
The full Michael White episode is also available.

Raj Koo, CTO at DTEX, joins The Tech Trek for a sharp conversation on insider risk, shadow AI, and why security teams need a more modern way to think about intent. This episode is worth your time if you are trying to understand how AI is changing cyber risk, why non malicious behavior can still create major exposure, and what it takes to protect the business without slowing down innovation.
Raj explains why the old approach of blocking known bad behavior is no longer enough. As employees bring personal AI tools into the workplace, security teams are dealing with a new reality, one where productivity gains, agentic workflows, and data exposure are all colliding at once.
In this episode
Why DTEX focuses on inferring intent, not just catching exfiltration

Why shadow AI is different from shadow IT, and harder to control

How non malicious employee behavior can become the biggest insider risk category

Why agentic AI raises the stakes for visibility and governance

How mature insider risk programs are shrinking response times even as costs rise

Timestamped highlights
00:00 Raj Koo on inferring intent in cybersecurity

01:59 Why early warning signals matter more than the exfiltration point

04:38 The rising cost of insider risk

06:25 How shadow AI became a major non malicious risk

08:13 Why shadow AI is more complex than shadow IT

17:53 Detection times are improving, but the cost problem is getting worse

Standout line
Security has a chance to stop being seen as the function that blocks productivity and start being seen as the function that helps the business adopt better tools safely.
Practical takeaway
If your team is dealing with AI adoption in the wild, start with visibility before judgment. Understand which tools people are using, what they are using them for, and where the real risk sits before defaulting to blanket restrictions.
Link to 2026 Cost of Insider Risks Global Report: https://ponemon.dtex.ai/
Follow The Tech Trek for more conversations with builders, operators, and technology leaders shaping how modern companies work.

Sumeet Arora, Chief Product Officer at Teradata, joins The Tech Trek for a sharp conversation on the shift from human driven SaaS to agentic software. This episode digs into what changes when software stops just supporting human workflows and starts driving outcomes alongside people, why trust and governance matter more as AI systems take on more responsibility, and what serious companies need to do now to prepare.
This is a practical discussion about where the market actually is, what gets overhyped, and what leaders should focus on beneath the noise. Sumeet lays out a clear view of the emerging enterprise stack, from knowledge and context to agents, governance, and outcomes. He also explains why the winners may not be the loudest companies in AI, but the ones that get their data, knowledge, and operating model right.
In this episode
• Why agentic software is a real shift, but still in its early stages• What trust, governance, and explainability need to look like in an AI first enterprise• How software companies should rethink product strategy for agents as well as humans• Why every employee may need to become a manager of AI agents• Why knowledge infrastructure could matter more than the agent layer itself
Timestamped highlights
• 00:45 Teradata’s role in helping enterprises become autonomous• 02:34 Where we really are in the agentic AI maturity curve• 10:16 How software shifts from workflow centric to outcome centric• 16:17 Why every employee may need an AI workforce• 21:57 The skill gap between enterprise users and agentic adoption• 24:48 Why knowledge, not just agents, will define the winners
Standout line
“The fundamental winners will be ones who get the knowledge fabric correct.”
Practical takeaway
If you are building for an AI driven future, do not start with agents alone. Start with trusted knowledge, usable context, clear policies, and systems that can explain decisions. The companies that treat agentic AI as a stack, not a feature, will be in a much stronger position.
Follow The Tech Trek for more conversations with leaders shaping the future of technology, product, AI, and enterprise transformation.