Evaluating New Technology

# Evaluating New Technology - All Guest Insights

*22 guests, 27 mentions*

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## Aishwarya Naresh Reganti + Kiriti Badam
*Aishwarya Naresh Reganti + Kiriti Badam*

> "When someone comes up to me and says, 'We have this one click agent, it's going to be deployed in your system.' ... I would almost be skeptical because it's just not possible. And that's not because the models aren't there, but because enterprise data and infrastructure is very messy... I would rather go with a company that says, 'We're going to build this pipeline for you,' and that will learn over time."

**Insight:** Be skeptical of 'out-of-the-box' AI solutions for enterprises; real ROI requires a pipeline that accounts for messy data and infrastructure.

**Tactical advice:**
- Evaluate AI vendors based on their ability to build a learning pipeline rather than a static 'one-click' agent.
- Assess the readiness of your internal data layer before attempting to deploy autonomous agents.

*Timestamp: 00:30:31*


## Aparna Chennapragada
*Aparna Chennapragada*

> "The models couldn't do some things one year ago. I mean, image generation was full of spellings or reasoning. You just couldn't have deeper and smarter answers. You couldn't do data analysis. So my impression of it from change, trying it a few months ago, that prior needs to be updated. And it's hard to do that, right? You have to do something almost counterintuitive and against the grain to say, 'No, no, ignore what you learned about what this can or cannot do.' The baby just grew up to be a 15-year-old in a month."

**Insight:** To effectively build with AI, product leaders must constantly update their 'priors' because technology capabilities evolve faster than human habits or 'scar tissue' from past failures.

**Tactical advice:**
- Actively work to ignore 'scar tissue' from previous technical limitations
- Regularly re-test assumptions about what AI can and cannot do every few months
- Demand more from current technology rather than relying on old benchmarks

*Timestamp: 00:31:17*


## Asha Sharma
*Asha Sharma*

> "you really need to bet on a platform or some app server type layer that allows you to swap things in and out and not really be beholden to anything, any one technology or any one tool because the reality is the whole thing is going to change."

**Insight:** Avoid vendor or tool lock-in by investing in an abstraction layer that allows for modularity as the AI stack evolves.

**Tactical advice:**
- Bet on platforms that support model diversity and easy swapping of components
- Prioritize tools that offer high observability and evaluation capabilities

*Timestamp: 11:24*


## Austin Hay
*Austin Hay*

> "I have this adage I always say, which is tools are just meant to solve problems. And the problem set for marketing technologists and business technologists is you focus on the tools."

**Insight:** Technology should always be viewed as a means to solve a specific problem rather than an end in itself.

**Tactical advice:**
- Always define the problem and the people involved before selecting a system or tool.
- Avoid 'tool bias'—picking a tool just because you've used it before.

*Timestamp: 00:10:11*

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> "It's B and B as opposed to BVB. So, build and buy as opposed to build versus buy. People all the time just think the second that you're talking about implementing a tool or procuring a solution, it's, Hey, I want to build this thing or I want to buy this really expensive thing. Build versus buy is a very narrowly constricting decision tree. If it's only build versus buy, then you've already made the decision that you can only do one or the other... Build and buy means that both of you can win"

**Insight:** The most effective technology strategy often involves buying a core tool and building custom layers on top of it.

**Tactical advice:**
- Buy tools to handle 90% of the standard functionality and build the 'cool' 10% that is unique to your business.
- Use a financial model to show tha