Office Hours with Tomasz Tunguz

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.

Office Hours with Baris Gultekin: The Era of Enterprise AI is Here

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

08-05
31:28

Office Hours with Benn Stancil: BI's Third Form

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

07-03
29:06

Office Hours with Jordan Tigani: Modern Data Architectures

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

05-06
25:42

Office Hours with Evan Cheng, Building the Future of Blockchains

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 

04-22
39:36

Office Hours with Tom Tunguz & Colin Zima

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 

03-19
35:52

Office Hours with Tom Tunguz & Steven Goldfeder

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

02-27
42:48

Office Hours with Tom Tunguz & Philip Zelitchenko

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

12-18
43:06

Office Hours with Tom Tunguz & Raj Sarkar

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...  

11-03
37:39

Office Hours with Tomasz Tunguz & Oliver Jay

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

10-12
48:25

Office Hours with Tomasz Tunguz & Fredrik Haga

On November 29th at 9am Pacific Time, Office Hours hosted Fredrik Haga, founder & CEO of Dune. Dune is the authoritative source of web3 data. For information on Decentralized Exchange activity, lending volumes, or even the current FTX account balances. I used Dune to make the State of Web3 Presentation. During this Office Hours, Fredrik & I will talked about - the importance of data in a decentralized world - the impact of the three major collapses this year: FTX, Luna, & ThreeArrows on the ecosystem - the evolution of web3 in 2022 - building a startup through tough market conditions Thanks to Fredrik for the great session.

12-09
46:20

Office Hours with Tomasz Tunguz & Carilu Dietrich

On October 18th at 10am Pacific, Office Hours will host Carilu Dietrich. Carilu headed corporate marketing for Atlassian from $150m to $450m in revenue & through their massively successful IPO. Since then, she’s advised Segment, Kong, Miro, Bill.com & 1Password, among many others. Needless to say, her vista across many leading SaaS companies marketing practices is exceptional. During the Office Hours, we’ll discuss: the role of marketing in PLG motions. debate the two different ways of trimming marketing spend : better to cut people or programs? how to develop excellent positioning for a business. When to rebrand a company? If you’re interested to attend, please register here. As always, we will collect questions from participants before the event, weave them into the conversation, and answer live questions at the end of the session. I look forward to welcoming Carilu to Office Hours!

10-19
49:10

Office Hours with Tomasz Tunguz & Bill Binch

Office Hours welcomed Bill Binch, former CRO at Pendo, EVP Worldwide Sales at Marketo & operating partner at Battery to share his views on building world-class sales organizations.Bill & I exchanged emails about Deliberately Underselling as Sales Strategy. I asked him to share his views on land & expand team structure & quotas. But we covered much more. Here are three highlights from the session.First, Deliberately Underselling means optimizing the sales process for Net Dollar Retention (NDR). Logo-based quotas focus the team on speed to close. Sometimes, these plans have a minimum contract value plus a bounty.Another structure establishes land account executives & expand account executives. The company’s leadership should calculate sales efficiency on the combined OTE (on-target earnings) to quota ratio of these teams.A land AE with a $300k OTE might have a $600k quota. Her land AE counterpart might also have a $300k OTE with a $2.8m quota. If they attain plan, the combined OTE/quota ratio is 0.176. Most startups operate between 0.15-0.25.This land & expand team construct recognizes the difference in difficulty between landing & expanding accounts; also, the potential difference in ideal AE for each role. Last, the plan compensates those responsible for growing accounts with a quota - in line with Frank Slootman’s philosophy.Second, Bill offered a bold prediction. Top startups will record 200-300% NDR as PLG becomes a dominant go-to-market strategy. Today, best-in-class tops out at 170% or so. We agree there!Third, Bill revealed his Mojo Metric, his north-star metric. The Mojo Metric reports the net change in pipeline daily. Here’s how to calculate yours:Mojo = new pipeline + new_pipeline_expanded + deals_pulled_forward deals_killed - deals_shrunk - deals_pushedEach day’s Mojo reveals how much incremental pipeline the team has generated & informs the sales leader early on about this quarter’s health.There’s much more in the session including handling commissions on multi-year deals (TCV vs ACV), criteria for evaluating ramping account executives that echoes insights from the Vista sales playbook, optimal ratios for team construction, how sales has changed in 30 years & how it changes after Covid, amongst other topics.

08-16
51:38

Office Hours with Tomasz Tunguz & Lars Nilsson

Office Hours welcomed Lars Nilsson, VP Sales Development from Snowflake to talk about his learnings across 5 companies he helped take public.Throughout the hour, Lars provided insightful perspectives on how to build sales organizations. These the five most memorable takeaways for me.In early-stage companies, founders sell for the first three to four quarters. Then, many founders opt to hire an AE. Hiring a sales or business-development representative (SDR/BDR) can be the better choice. Incoming account executives will want to see a significant lead volume before joining, especially when selling into the enterprise.Teams often overlook storytelling as a critical part of effective lead generation. Fear-of-missing-out or the inspiration of a potential future, stories equip champions inside customer organizations to sell the product through the buying process. Founders validate the effectiveness of their stories when hiring SDRs better. SDRs call ten-times as many prospects as AEs do. Much the better to iterate with greater speed and confidence.As the company grows, building the sales development team becomes the most productive source of pipeline particularly for enterprise-grade technical products. Hire for hunger. Then surround the new SDR/BDR with three pillars: strong training materials, a manager who cares about the employee’s success, and a peer to accelerate learning.At Snowflake, sales development lives within the marketing team. Lars manages his team through a single metric, meetings. Getting to an account late, a few days or a week after they’ve signed with a competitor accrues to the meeting metric (see why in the video).Last, exiting unlikely sales processes saves the company’s resources and boosts team morale. Closed - no decision is the worst outcome of an engagement.We covered much more in the session including the techniques Snowflake uses to align account-based marketing with sales development & sales teams; how to structure career paths within the team; transitioning accounts between SDRs/BDRs to account executives; and the right SDR:AE ratios as companies scale.Thank you, Lars, for the masterclass on sales development.

07-14
56:34

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