Future Proof: Building AI Products that Last

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 Clips0:36 Intro1:54 Future of customer experience 5:00 Building trust 8:00 Getting executive buy-in10:00 What true resolution looks like13:00 How Ada measures success with “automated resolution”16:00 Mirroring human QA processes18:00 Why domain expertise is the new superpower for AI founders19:30 Grounding responses with retrieval, context, and memory22:00 Balancing latency, reasoning, and customer experience24:00 Deploying agents safely and effectively26:00 Voice automation and ROI across industries29:00 Surpassing human agents and the future of AI-driven CXShip integrations 7x faster: https://www.useparagon.com/Host: Ethan LeeGuest: Mike GozzoProduced 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 thoughtsShip integrations 7x faster → https://www.useparagon.com/Host: Ethan LeeGuest: Elliott ChoiProduced 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 thoughtsShip integrations 7x faster www.useparagon.comProduced by: Forrest HerlickHost: Ethan LeeGuest: 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 technologiesMoving beyond “LLM wrappers” to deliver end-to-end customer valueLessons from building in regulated industries like banking and healthcareWhy user experience, not model quality, defines AI product successHighlights:(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.comLearn 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 productsHow to make AI feel naturalHow to give users a sense of controlHighlights(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?