In the latest episode of Future Proof, building AI products that last, Mike Gozzo, Chief Product and Technology Officer at Ada, shares how Ada is helping enterprises move from scripted chatbots to reasoning-driven AI agents, why trust and human empathy remain the foundation of customer experience, and how metrics like “automated resolution” are redefining success in enterprise AI deployments.

Highlights:

0:00 Clips

0:36 Intro

1:54 Future of customer experience

5:00 Building trust

8:00 Getting executive buy-in

10:00 What true resolution looks like

13:00 How Ada measures success with “automated resolution”

16:00 Mirroring human QA processes

18:00 Why domain expertise is the new superpower for AI founders

19:30 Grounding responses with retrieval, context, and memory

22:00 Balancing latency, reasoning, and customer experience

24:00 Deploying agents safely and effectively

26:00 Voice automation and ROI across industries

29:00 Surpassing human agents and the future of AI-driven CX

Ship integrations 7x faster: https://www.useparagon.com/

Host: Ethan Lee

Guest: Mike Gozzo

Produced by: Forrest Herlick

In the latest episode of Future Proof, building AI products that last, we chat with Elliott Choi, Director of Product at Cohere. Elliott shares how Cohere is shaping the path from simple demos to enterprise deployment, why oversight, auditability, and security are essential for agent adoption, and the role of automation and memory in moving toward fully autonomous AI agents.

Highlights:
(0:00) Clips
(1:07) Intro & $500M fundraise at Cohere
(2:20) Defining AI agents for the enterprise
(5:00) Traceability, observability & automation guardrails
(8:12) Automating well-defined enterprise processes
(11:21) Why flashy demos break in enterprise
(12:09) Architecture pitfalls: prompts, data sources & security
(15:15) Managing context & RAG performance
(17:08) Building semantic vs. procedural memory
(19:24) Permissioning & secure data access with SSO
(21:32) Why memory makes agents sticky
(25:54) From automations to fully autonomous agents
(26:57) Closing thoughts

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Host: Ethan Lee
Guest: Elliott Choi
Produced by: Forrest Herlick

In the latest episode of Future Proof, building AI products that last, we chat with Megh Gautam, Chief Product Officer at Crunchbase. Megh shares how Crunchbase's customer-first approach to AI implementations preserved user trust while transforming search workflows, and practical strategies for rolling out AI features without alienating existing power users.

Highlights:

(0:00) Intro

(1:00) Crunchbase positioning as role of CPO

(3:40) Adding AI capabilities to current product

(7:15) Learnings from experiments that didn’t work out the way it was expected

(10:45) Metrics used to measure AI features delivering value

(14:00) How Crunchbase thinks about aligning with user needs, not just cool tech

(20:30) Where are AI builders making mistakes between AI technology and their users

(24:00) Navigating the prioritization between core platform improvements and AI capabilities

(28:30) Closing thoughts

Ship integrations 7x faster www.useparagon.com

Produced by: Forrest Herlick

Host: Ethan Lee

Guest: Megh Gautam

In today’s episode of Future Proof, we sit down with Anant Bhardwaj, Founder & CEO of Instabase. Anant shares how Instabase pioneered the use of transformer models for unstructured enterprise data, and how the rise of large language models is shifting value creation from field-level accuracy to full end-to-end workflows.

We discuss:

• Finding product-market fit with nascent AI technologies
• Moving beyond “LLM wrappers” to deliver end-to-end customer value
• Lessons from building in regulated industries like banking and healthcare
• Why user experience, not model quality, defines AI product success

Highlights:

(0:00) Clips

(0:53) Opening thoughts

(2:15) Instabase early journey before the AI wave

(5:28) How new models have shifted product development strategy

(10:16) Creating value for customers with LLMs

(12:06) Working with heavily regulated customers

(15:16) What’s been the hardest about building infrastructure for unstructured data use cases?

(21:06) AI infrastructure bets companies should be making today?

(23:06) How Agents will work with unstructured data?

Host: Ethan Lee https://www.linkedin.com/in/thatethanlee/

Producer: Forrest Herlick https://www.linkedin.com/in/forrestherlick/

Guest: Anant Bhardwaj https://www.linkedin.com/in/anantpb/

Ship integrations 7x faster -> www.useparagon.com

Learn more about Instabase -> https://instabase.com/

In today’s episode of Future Proof, we sit down with Laura Burkhauser, VP of Product at Descript. Laura shares how Descript’s design philosophy enables users to maintain control over AI creative workflows, and practical strategies for building AI interfaces that feel collaborative rather than restrictive.

We discuss:

• Designing user interfaces in AI products
• How to make AI feel natural
• How to give users a sense of control

Highlights

(0:00) Clips

(0:37) Introduction

(1:00) Designing interfaces that make users trust they’re in control

(6:00) Open World AI Design Philosophy

(8:40) Was there ever a tool you needed to modify once AI got access?

(13:45) How to encourage users to understand what AI is good at

(19:00) Giving control back to users

(20:30) How to handle latency

(23:00) Context switching while AI does its work

(25:00) Biggest UI opportunities

(30:00) Will we progress beyond a chat model?

In this episode of Future Proof, we sit down with Aman Khan, the Head of Product at Arize AI. Aman reveals why traditional product metrics fail for AI systems and shares Arize's framework for building evaluation systems that actually predict real-world AI performance, plus the emerging PM skills that separate successful AI products from failed experiments.

We discuss:

• How AI builders should think about evaluations
• The role of the AI pm and how product management is evolving
• How you should build with the expectations of foundation models changing.

(0:00) Highlights

(0:37) Intro

(1:40) What is an AI pm

(4:10) How PMs are evolving with AI

(8:10) The Aha moment in AI

(11:50) What AI builders should think about evaluations

(19:40) How AI builders best leverage their time in AI evaluations

(23:40) Prompt iteration - if your evaluations are not ideal, how do you iterate?

(27:40) What’s the minimum viable eval someone should write

(30:40) How would prioritization change based on the future of AI models

(36:40) Final thoughts

(38:00) Ethan's reflection

Ship integrations 7x faster https://www.useparagon.com/

Watch all Future Proof episodes: https://www.useparagon.com/future-proof

In this episode of Future Proof - Building AI products that last, we sit down with WorkOS founder and CEO, Michael Grinich, on what it takes to make MCPs production-ready.

We discuss:

• What it means to be ‘MC Pilled’
• What’s missing from MCP to make it enterprise-ready?
• How to build a product for a world of agentic users

Highlights

(0:00) Clips

(0:44) intro

(1:11) MCP night

(3:49) What is preventing demos from production ready AI agents

(6:41 ) Authorizing tools in MCP

(9:01) Should AI builders develop protocols themselves?

(11:11) When should you build a MCP server

(12:41) MCP ecommerce shop

(14:05) Why are permissions a problem in rag

(22:11) WorkOS acquisition of warrant (FGA)

(26:11) How auth changes once agents become common users of webapps (oAuth 3.0)

(30:11) How should builders shape their apps to be prepped for the future?

Scale your AI product's integration roadmap with Paragon: https://www.useparagon.com/?utm_source=futureproofpodcast

Sign up for their MCP night → https://workos.com/mcp-night

Welcome to the second episode of the Future Proof Podcast: Building AI Products That Last! In this episode, we chat with Richard Socher, CEO and Co-founder of You.com, about how they pivoted from consumer search to enterprise, and now outperform OpenAI.

We cover:

• Building for the future of Enterprise productivity
• How to build a competitive advantage against industry leaders like Open AI
• Is chat the final interface for work?

(00:00) Clips

(00:50) Intro

(01:10) How Richard started You.com

(05:40) Building for the enterprise use case

(09:20) How to outperform OpenAI

(14:00) Advice for AI founders

(19:00) Is chat the final interface for work?

(23:30) Will there be a consolidation of AI?

(24:40) How will AGI affect the future of work?

Scale your AI product's integration roadmap with Paragon at https://useparagon.com

Welcome to the first episode of the Future Proof Podcast: Building AI Products That Last! In this episode, we chat with Aaron Levie, CEO and founder of Box, about what it takes to build successful Enterprise AI products.

We cover:

• Why good data is a moat / flywheel for AI products
• The importance of access controls in RAG
• Building broad or building deep
• APIs, MCPs, A2A

(00:00) Clips

(00:30) Intro

(01:40) Box's AI strategy

(04:45) RAG use cases with proven value

(09:05) Horizontal vs. deep product strategy

(11:14) Prompts as IP

(12:05) Importance of secure RAG in enterprise AI

(16:28) Ingest vs. agentic queries

(19:10) APIs, MCPs and Agent-to-Agent

(21:20) Moats and network effects for AI companies

(26:49) Risk of bad data

(29:48) A few large AI agents vs. many niche AI agents

Scale your AI product's integration roadmap with Paragon at https://useparagon.com/?utm_source=podcast/utm_campaign=ep1