The Tech Trek

Mary Elizabeth Porray, Global Vice Chair Client Technology and COO, Growth and Innovation at EY, joins The Tech Trek for a grounded conversation about what it actually takes to operationalize emerging technologies inside a global enterprise. This episode goes past the AI hype cycle and into the real work of adoption, change management, process redesign, workforce trust, and leadership in ambiguity.

A lot of companies are asking what AI can do. Fewer are asking what needs to change for AI to actually work. Mary Elizabeth shares how EY is thinking about experimentation, employee experience, guardrails, internal adoption, and the cultural shifts required to move from curiosity to real impact.

In this episode

Why culture, not technology, is often the biggest blocker to emerging tech adoption

Why AI is not a magic wand, but can help teams solve problems in a different way

How leaders can identify the right starting points by listening for real pain points

Why productivity gains have to create psychological space, not just more work

How affinity groups, storytelling, and visible leadership help drive adoption

Timestamped highlights

01:58 Why cultural norms often slow down emerging technology adoption
03:25 AI hype, false expectations, and what the technology can realistically change
05:55 The mental load of AI at work, and why EY created Thrive Time
11:20 Why AI pilots need to go deeper than surface level experimentation
15:19 How AI is creating a shared language between business and technology teams
29:29 How storytelling, affinity groups, and positive momentum help people lean in

One line that sticks: AI is not something you dabble in.

A practical takeaway
The best place to start is not with the flashiest use case. It is with a real pain point. If a process should take one week and actually takes eight, that is a signal worth following.

Follow The Tech Trek for more conversations with leaders building through change, scaling technology, and shaping how modern work actually gets done.

Michael White, Co founder and CEO of Multiply, joins the show to talk about the path from engineering leadership to the CEO seat, and what it really takes to build in a high trust, high complexity market. If you are thinking about founder readiness, leadership growth, or where AI creates real value in fintech, this episode gets into the parts that matter.

Michael shares how early entrepreneurial instincts showed up long before Multiply, what changed as he moved from builder to company leader, and why some of the most important skills in leadership have less to do with code and more to do with communication, conviction, and influence. He also breaks down how Multiply is using AI to improve the mortgage experience without removing the human element people still need in a major financial decision.

In this episode:

• The mindset shift from engineer to CEO
• Why leadership becomes a form of sales
• How founder timing can be an advantage, not a delay
• Where AI fits in the mortgage process, and where it does not
• Why startups can move faster than legacy players in AI adoption

Timestamped highlights

00:43 What Multiply is building, and why an AI native mortgage company sees a better path to homeownership
01:47 The childhood business story that hinted at an entrepreneurial future
06:20 What changed in the move from engineering leadership to founder and CEO
08:45 Why so much of leadership comes down to influence, alignment, and selling the vision
17:19 Why mortgages are such a strong use case for AI, and why the back office is the real opportunity
22:39 The startup advantage in AI, speed, focus, and freedom from legacy systems

Follow the show for more conversations with founders, operators, and technology leaders building what comes next.

Susan Liu, Partner at Uncork Capital, joins Amir to break down what actually matters when backing early stage AI companies. From founder market fit to product wedge to the reality of churn, this conversation gets past the hype and into how strong companies separate themselves in a crowded market.

If you are building, funding, or evaluating AI startups, this episode gives you a sharper lens on where the market is heading, what Series A investors now expect, and why real ROI is becoming the line between momentum and fallout.

What stood out

• The best early stage founders usually have earned insight, meaning they have lived the problem before building the solution
• In crowded AI markets, the goal is not to be interesting, it is to become one of the few companies that actually wins
• AI buyers still care about the same core question, does this drive revenue or cut cost in a measurable way
• The Series A bar has moved up fast, and strong growth alone is not enough if retention is weak
• Some of today’s biggest AI winners may still face painful churn if they are not truly essential to the customer

Timestamped Highlights

00:37 Susan breaks down how Uncork Capital invests at seed and what it takes to get real conviction early
02:00 The three-part framework she uses to evaluate companies, team, market, and product wedge with traction
09:42 Why crowded AI markets are not necessarily a red flag, and how winners still pull away from the pack
17:04 The ROI test every AI startup has to pass if it wants to survive renewals
19:05 Susan’s honest take on 2026, cautious optimism, bigger impact, and a likely wave of churn
24:33 What founders need now to raise a strong Series A in a market where the bar is higher than ever

One line that stuck

“If you cannot prove one of these two, it is going to be a tough sell. Companies are not going to renew.”

Practical takeaways for operators and founders

• If your product cannot clearly tie to revenue growth or cost savings, buyers will eventually cut it
• Founder credibility matters more when the market gets noisy, especially in AI
• A compelling wedge wins attention, but retention is what keeps the story alive
• Happy customers who will speak for you can be one of the strongest assets in a fundraise

Stay connected

If this episode gave you a better lens on AI startups, venture, and what actually drives durable value, follow the show, share it with a founder or operator in your network, and keep up with Amir on LinkedIn for more conversations like this.

What happens to e commerce when AI agents start shopping instead of humans?

Maju Kuruvilla, Founder and CEO of Spangle, joins the show to unpack a shift most companies are not prepared for. If AI agents become buyers, the entire digital shopping experience must change. Websites today are designed for human psychology, not machines making decisions.

In this conversation, Maju explains why context is becoming the most important layer in commerce. From marketing clicks to storefront visits, most companies lose the context that originally inspired a purchase. The future belongs to systems that can capture, carry, and act on that context across every channel.

The discussion explores agent driven shopping, the limits of traditional customer data systems, and how AI can reshape both online and physical retail experiences.

Key Takeaways

• Context matters more than identity. Knowing what someone is trying to do right now is often more valuable than knowing who they are.
• Most e commerce experiences reset the customer journey. When someone clicks from an ad to a site, the original inspiration is usually lost.
• AI agents will shop differently than humans. They are not influenced by visual design or marketing psychology the same way people are.
• Commerce will not become fully agent driven. Instead, brands must design experiences that work for humans, agents, and hybrid interactions.
• Physical retail may benefit the most from AI driven context because stores can blend digital signals with real world behavior.

Timestamped Highlights

00:00 Why the next generation of e commerce will be built for AI agents, not just human shoppers.
02:08 The hidden problem in online shopping today. Most websites lose the context that brought the customer there.
06:11 Buyer agents and seller agents. How commerce may evolve into AI systems negotiating purchases.
11:38 Why a simple request like “buy a red sweater” is actually a complex problem of interpretation and context.
16:30 How AI could transform physical stores through dynamic recommendations and real time shopping guidance.
22:30 Why collecting endless customer data might be the wrong approach to personalization.
27:59 The future of autonomous shopping and why personal AI agents may eventually handle everyday purchases.

A Moment That Sticks

“Context is what matters. The fact that I bought a TV before is interesting, but not important. What matters is what I am trying to do right now.”

Practical Insight for Builders

If you are building AI driven commerce tools, start with the product layer.

According to Maju, the foundation is making your product catalog intelligent. AI systems need rich product understanding so they can match intent with inventory. Once the catalog becomes machine readable and context aware, everything else becomes easier to automate.

Call to Action

If you enjoyed this conversation, follow the show and share this episode with someone working at the intersection of AI, commerce, or product development.

New conversations every week with the builders shaping the future of technology.

Most people never think about the technology behind construction equipment rentals. But behind every crane, excavator, and lift is an industry still running on paper, spreadsheets, and manual workflows.

In this episode, Andy Feis, CEO and Co-Founder of Renterra, joins Amir to explain how a hundred billion dollar equipment rental market is finally entering the modern software era. The conversation explores how operational software, telematics data, and AI are reshaping one of the most overlooked parts of the industrial economy.

Andy shares how rental companies manage fleets of expensive machines, why legacy workflows still dominate the industry, and how platforms like Renterra are bringing cloud software and automation to a sector that has largely been left behind by the tech revolution.

This episode also explores the intersection of operational data, AI automation, and real world infrastructure. From fleet optimization to automated maintenance insights, the future of equipment rental may look very different than it does today.

Key Takeaways

• The equipment rental industry is a massive but overlooked market where over half of construction equipment is rented rather than owned.
• Many rental businesses still run critical operations using pen and paper, manual inspections, and outdated spreadsheets.
• Operational software is the first step toward modernization, helping companies manage inventory, dispatch, pricing, and maintenance.
• Telematics data from machines unlocks powerful insights around maintenance timing, asset valuation, and fleet utilization.
• AI will not replace the physical work in industrial sectors, but it can automate low value operational tasks and dramatically improve decision making.

Timestamped Highlights

00:00 Introducing the hidden technology opportunity inside the equipment rental industry
02:00 Why many rental companies still rely on paper, binders, and manual equipment checks
06:20 How Andy Feis discovered a massive opportunity inside industrial operations
09:00The low hanging fruit in modernizing equipment rental workflows
11:14 What kind of data heavy machines actually generate and how it can be used
13:03 Where AI actually helps blue collar industries today
20:18 The roadmap for modernizing the industry and what comes next

A Moment That Stuck

“The industrial sector is an enormous part of the economy, but it has been one of the last places to feel the impact of the broader tech revolution.”

Pro Tips

If you are building technology for legacy industries, start with operational efficiency before advanced analytics.

Modernization works best when it removes friction from existing workflows. Once companies see time savings and operational improvements, they become far more open to deeper data and AI driven insights.

Call to Action

If you enjoy conversations about technology transforming real world industries, follow the show and share this episode with someone building in construction, logistics, or industrial software.