Hosted by Tomasz Tunguz
Episodes
14
Latest episode
Apr 2026
Language
EN
A show that invites luminaries from Startupland to talk about how to build great businesses. Questions are collected from the audience & interleaved into the conversation.
00:00 Welcome to Office Hours 00:41 Meet Lena Waters 01:11 AI Transformation as Debt 02:24 Headcount and AI Washing 03:30 From Efficiency to Strategy 04:44 Websites vs Agent Architecture 07:10 Agent Driven Buyer Journey 09:40 Marketers Minimum Playbook 13:05 Behavior and Liability Shifts 16:09 Rebuilding Marketing Org 17:38 Does Brand Still Matter 19:02 Key Takeaways and Wrap
01:26 Journey to Snowflake02:32 Snowflake and AI06:43 Choosing your model07:44 Snowflake & OS09:43 Innovations to reduce training data size10:59 From large to small models13:14 Snowflake and agentic systems15:50 AI & data security17:17 Access control layer18:14 Embedded applications19:55 Data sharing21:37 Snowflake training & inference23:12 Data reshaping24:40 Structured versus unstructured model inputs25:24 Models providing the mean v. exceptions27:19 Vector databases30:33 Summary
01:43 Tabular Acquisition by Databricks05:57 BI's Third Form09:12 Future of BI12:50 Data Quality in the World of LLMs18:48 Building Resilient Data Pipelines & ETL21:01 Evolving Role of BI Analysts23:18 Data and Decision-Making28:05 Conclusion
01:55 Big Data is Dead06:41 Ease of Use08:54 Hybrid Architecture10:30 Audience Question: LLMs for Onboarding?12:55 Hybrid Architecture Enables New Software Design16:58 DuckDB & ETL19:24 Duck Puns22:07 Duck Community24:32 Summary
0:00 Office Hours - Evan Cheng01:28 From Meta to Mysten04:54 Why Develop a New Language, Move11:15 Developer Response to Move13:21 Zero Knowledge (ZK) Proof of Login19:00 Kiosk24:34 On Chain Storage Limitations29:01 DAGs & Web330:01 Mysten Labs Ecosystem & SUI34:03 SUI Token Launch38:30 Closing
Takeaways from this discussion include:There is a pendulum between governance and self-serve, and that swing is narrowing with developments like OmniThere's a dynamic with centralization and decentralization hybrid execution at the edge which allows super-interactive user experiences. As these experiences improve, the number of people who benefit and can access data in meaningful ways only increases.00:06 Introduction01:27 Being Chief Analytics Officer04:08 Evolution of BI08:23 Data Organization Structure10:53 Data Permissioning Philosophy14:12 Hybrid Execution17:36 BI Application Architecture19:36 Mitigating Buyer Fatigue21:20 BI & AI25:59 Semantic Layer27:12 Audience Question: Should AI Suggest Analyses?28:43 Embedded Analytics32:48 Will AI Automate BI Users Away?35:00 Summary
00:06 Introduction 02:10 Arbitrum Statistics 02:47 Building Your Developer Community 09:08 Arbitrum One v. Arbitrum Nova 14:55 L3 & Customization 19:41 Arbitrum Orbit & Chain Clusters 24:39 Future Customizations for Developers 28:30 Accepting Developer Languages: To reduce barriers to entry 30:11 Accepting Developer Languages: To access legacy code 32:38 Accepting Developer Languages: To reduce fees 33:48 Convergence of Web2 and Web337:55 Community-Source-Software42:03 Summary
0:00 Office Hours with Philip Zelitchenko 01:47 Q: How did you decide to structure your team like software engg? 05:07 Q: Determining the value of data 09:17 Structuring data teams: data PMs 10:47 Q: Same data team responsible for internal v. external PRDs? 11:14 Structuring data teams: data engineering 12:02 Q: What is a data product? 12:47 Structuring data teams: data analysts 13:22 Structuring data teams: data governance 13:37 Structuring data teams: data platform 14:18 Q: What distinguishes a DPRD from a PRD?17:33 Q: Role of the DPRD? 20:05 Q: DPRD v. TEP? 20:55 Demystifying data governance 23:22 Data alert management - internal team and customers 26:20 Q: Motivating ownership of data assets? 28:51 Defining value of a data asset 30:29 Measuring data usage 31:37 Q: Can tools today handle the stochastic nature of data? 33:28 Building a data team within the enterprise 35:42 Q: How to test data products prior to release? 40:00 Q: How do you use observability to manage diversity of alerts? 41:51 Summary
00:11 Introduction 02:54 What is Outbound Fury (OBF)? 03:34 Inspiration for OBF 05:03 OBF Tactics 07:44 Determining the Line 11:22 The Challenger Sale 14:11 Personas & OBF 16:05 Product-Led Growth (PLG), ABM & Outbound Fury 19:35 Setting Up Your Team for Success 21:54 Managing Internal Stakeholders 25:28 Measuring Success 27:16 Brand & OBF Campaigns 29:25 Pricing in Marketing Considerations 31:47 Analyst Community (e.g. Gartner) & OBF33:43 Company Scale & OBF 36:23 Conclusions Materials Mentioned in Today's Session: -- Raj Sarkar's Post: https://rajsarkar.substack.com/p/mark... -- Marc Benioff, Behind the Cloud https://www.amazon.com/Behind-Cloud-S... -- Matthew Dixon, The Challenger Sale https://www.amazon.com/The-Challenger...
00:00 Introduction to Tom and Oliver03:07 Overview of PLG at Dropbox05:30 Overview of PLG at Asana06:07 How to succeed in PLG end user acquisition phase09:15 Tactics for Generating Awareness10:17 Customer Expansion Phase13:15 When Tension Arises Between PLG & Enterprise Security Needs15:24 Security is an All Consuming Roadmap, not a Feature18:35 How the Organization Shifts during the Transition from PLG to SLG20:48 How Pricing Changes from PLG to SLG26:22 The PLG Trap28:03 Avoiding the PLG Trap31:55 Value-Based Selling: Generalizable or Vertical/Use-Case Specific?35:35 Atlassian v. Asana's Approaches37:11 Advice for New Startups Pursuing PLG38:22 Navigating from SLG to PLG42:19 Resources for Founders43:06 PLG, SLG & AI
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