The Tech Trek

The goal is not to do less. It is to give agents the flexibility to handle more of the work customers actually need.

Henry Hopcroft, Chief Product Officer at Gradial, joins The Tech Trek to discuss how building AI products is changing traditional approaches to product development, engineering, and customer delivery.

Henry explains why his team has moved away from building individual agent features toward a smaller set of core capabilities. He also shares how Gradial tests agents against difficult enterprise environments, uses forward deployed engineers to learn directly from customers, and approaches product planning when AI capabilities are improving so quickly.

What You'll Learn

Why adding more features can limit an AI agent's flexibility.
How real customer failures shape Gradial's agent evaluations.
Why forward deployed engineers play a central role in product development.
How coding agents are bringing product and engineering roles closer together.

Episode Highlights

03:59 Why Gradial started deleting agent features.
07:31 Why traditional software testing falls short for enterprise AI agents.
08:35 Building a nightmare marketing stack to test agents.
12:03 How forward deployed engineers improve the core product.
15:56 Why great engineers increasingly need product judgment.
21:55 Why long term roadmaps are becoming harder for AI companies.

A Moment Worth Pulling Out

"Features can be something of an anti-pattern, I think, for agentic software."

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Jayeeta Putatunda, AI Engineering Lead at Turing, joins The Tech Trek to explore what happens after AI generates the first draft. She explains how excessive code can create maintenance challenges, why growing pull request volumes put pressure on code reviews, and how teams can build AI review agents around their own business rules.

The conversation also explores how AI is changing product development. Teams can test ideas, create prototypes, and gather customer feedback faster. But taking those ideas into production still requires testing, security, and engineering discipline.

Jayeeta also discusses LLM observability, the growing importance of domain expertise, and why sharing lessons across engineering teams matters as AI tools evolve.

Key Takeaways

More AI generated code can create additional review and maintenance work.
Code review agents need business context, not just generic rules.
Faster prototypes still require careful testing before production.
Domain expertise and human judgment remain important in AI systems.

Episode Highlights

00:34 Why AI generates more code and documentation than teams may need.
03:46 How growing PR volumes create new review challenges.
06:44 Measuring productivity beyond the number of features delivered.
12:10 Managing stakeholder expectations when prototypes become easier to build.
14:34 Why LLM observability matters in regulated industries.
18:44 The role of domain experts in building more specialized AI models.

One Line That Stuck

"Who's reviewing those 10 PRs?"

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AI teams can build solutions faster than many organizations can make decisions. That gap is changing how engineers work with the business and what companies need from technical leaders.

Ash Pembroke, Managing Director of AI Strategy at Accordion, joins The Tech Trek to discuss the growing role of forward deployed engineers. She explains why technical depth alone is not enough and how successful teams combine engineering, product thinking, and business knowledge.

The conversation covers leading lean engineering teams, finding the right mix of skills, working alongside business stakeholders, and navigating the tension between rapid AI development and slower organizational adoption.

Key Takeaways

Strong forward deployed engineers combine technical expertise with curiosity and business understanding.
Lean teams need complementary skills rather than one engineer who can do everything.
AI agents can extend existing SaaS systems, but replacing those systems requires careful decisions.
Faster development does not automatically mean faster adoption or better business decisions.

Episode Highlights

01:30 What makes a strong forward deployed engineer?
03:18 Leading small engineering teams with overlapping responsibilities
08:25 How AI agents are changing the role of traditional SaaS
16:50 Moving from software engineering or product into forward deployed roles
25:13 Why business decisions can become the bottleneck to AI adoption
33:48 Giving business teams the ability to automate their own workflows safely

A Moment Worth Pulling Out

"Nobody knows the work better than the person doing the work."

Ash makes the case for giving employees the tools, access, and guardrails to improve their own workflows.

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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."

Follow The Tech Trek for more conversations about AI, engineering, leadership, and building technology companies.