The Tech Trek

AI can generate answers in seconds. But what happens when the information needed to make a decision isn't available online?

Sagar Kadakia, founder and CEO of Qualitate, believes reasoning is becoming abundant while real world evidence remains scarce. His company uses AI moderators to interview experts, capture their knowledge, and make that information accessible to businesses.

In this episode of The Tech Trek, Sagar explains how AI can change the economics of primary research. We discuss why human knowledge still matters, how AI interviews work, and what happens when companies can gather expert insight faster and at lower cost.

The conversation also explores AI's impact on jobs, why Sagar is hiring more engineers, and how early AI adoption could create lasting advantages for businesses.

Key Takeaways

AI reasoning is becoming widely available, but firsthand human knowledge remains difficult to access.
AI moderators can reduce the cost and complexity of collecting expert insights.
AI may affect coordination roles differently from engineering, sales, and physical services.
Companies adopting AI early could build advantages that compound over time.

Episode Highlights

00:55 | How Qualitate captures human knowledge using AI
04:20 | Why reasoning is abundant but real world evidence is scarce
08:20 | How AI could reshape research and consulting services
12:00 | Inside an AI moderated expert interview
23:00 | Which jobs could change as AI adoption increases
28:00 | Why AI adoption could separate competing companies

One Line That Stuck

"Reasoning is no longer scarce."

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AI can help a small company move faster. But a leaner team also has fewer people to rely on when someone leaves.

Kevin Bradt, founder and CEO of CasaPerks, joins The Tech Trek to discuss building an AI first company as a nontechnical founder. Drawing on his experience in hospitality and multifamily housing, Kevin explains how he uses AI to rethink business operations, engineering, hiring, and customer delivery.

Kevin shares how CasaPerks uses AI to support software development and quality assurance, accelerate product requests, and generate business insights. He also explains why domain expertise and customer relationships may become more valuable as AI makes software development more accessible.

What You'll Learn

How AI changes staffing decisions across a growing company.
Why smaller engineering teams need stronger retention and specialist coverage.
How automated QA helps CasaPerks deliver features faster.
Why Kevin invests more heavily in customer support while automating internal work.

Episode Highlights

00:55 How hotel loyalty experience led to CasaPerks
03:00 Thinking like a business engineer
05:34 Building lean teams without losing coverage
07:18 Casa Flow and automated development workflows
12:31 How faster feature delivery helps win enterprise customers
17:18 Using automation to help residents after a flood

One Line That Stuck

"We're a service company first, and how we deliver service is through the medium of technology."

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The original idea may not be what makes a startup successful. As AI changes markets and creates new opportunities, the ability to learn and change direction becomes increasingly important.

Tim Chen, Managing Partner at Essence Venture Capital, invests in highly technical founders building infrastructure and developer tools. A former engineer and founder himself, Tim started his fund to provide the kind of support he wished he had when raising capital.

In this episode, Tim explains why his investment approach has evolved as AI accelerates change. He shares how he evaluates technical teams, what makes a pivot worth pursuing, and why he believes specialization helps investors stand out.

The conversation also explores his decision to operate as a largely solo investor, the importance of founder autonomy, and what it means to build a venture fund around a specific area of expertise.

Key Takeaways

Why a team's ability to learn matters beyond its initial product idea.
How AI is changing investment decisions in infrastructure and developer tools.
Why specialist investors can offer founders more relevant connections and guidance.
How Tim approaches pivots without making decisions for founders.

Episode Highlights

00:30 Why Tim started Essence Venture Capital.
03:32 The advantages of making independent investment decisions.
12:08 How specialist investors demonstrate value before investing.
17:03 What the Tabular investment revealed about technical opportunities.
18:04 Why some of Tim's strongest investments have involved major pivots.
22:33 How Tim evaluates the reasoning behind a founder's decision to pivot.

A key quote:

"Don't be too religious about the approach you take because you most likely are wrong."

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An AI agent can be fast, available, and still get the answer wrong. That changes what engineering teams need to measure.

Jeetendra Soneja, VP of Engineering, AI Platform at iHerb, joins The Tech Trek to discuss why AI observability goes beyond traditional software monitoring. Teams need to understand not just latency and errors, but also response quality, groundedness, cost, and whether an agent completes its intended task.

We also explore how to measure AI ROI without relying on misleading productivity metrics. Jeetendra shares his perspective on risk based guardrails, the skills engineers need, and why observability should begin during development rather than waiting until production.

Key Takeaways

Monitor agent quality and task completion alongside latency, availability, and cost.
Build evaluations around the specific business problem the AI system is solving.
Connect AI spending to business outcomes, not just token usage or code output.
Start with basic observability, then expand controls as AI adoption grows.

Episode Highlights

01:00 Why AI observability requires more than traditional monitoring.
06:00 The metrics that matter for cost, quality, and reliability.
08:00 How to measure AI ROI beyond productivity claims.
11:00 Setting risk tolerances and choosing appropriate guardrails.
16:00 The engineering skills becoming more valuable with AI.
22:00 Proving value before scaling AI systems.

One Line That Stuck

"It's one thing to get it done, it's another thing to get it done economically."

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What happens to engineering teams when everyone can code?

Bali Raghavan, cofounder and CTO at Hero Safety, joins Amir Bormand to discuss how AI is changing team structures, engineering skills, and hiring. At Hero Safety, designers, product managers, and operations teams are using AI to build and solve problems that once required engineering support.

That shift changes what companies need from engineers. Bali explains why systems thinking, architecture, judgment, and problem solving are becoming more valuable. He also shares why he now expects engineering candidates to use AI during interviews.

The conversation explores where specialized expertise remains essential, including computer vision and edge AI, and how public safety organizations are approaching AI adoption with both interest and skepticism.

Key Takeaways

AI is expanding who can build software across a company.
Engineering judgment and architecture matter more as code generation becomes easier.
Coding interviews should reflect how engineers actually use AI at work.
Specialized skills remain essential for complex AI systems and edge computing.

Episode Highlights

02:15 | Why Bali considers his entire company an engineering team
04:00 | How AI changes the value of programming skills
08:30 | Judgment, first principles, and evaluating AI output
11:45 | Why using AI is now expected in engineering interviews
14:25 | Generalists, specialists, and the need for edge AI expertise
16:15 | AI adoption, privacy, and skepticism in public safety

One Line That Stuck

"The bug has become a feature."

Bali explains how AI use went from something employers tried to prevent in interviews to something they now want to evaluate.

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