The future of development is full-stack
Live from Snowflake Summit, Ryan talks with Snowflake’s Head of Developer Experience Umesh Unnikrishnan about the industry-wide shift from “vibe coding” for quick prototypes to agentic engineering for enterprise-ready software, how enterprises can scale governance with guardrails like human-in-the-loop approval and control layers that go beyond the underlying LLM, and why Umesh predicts all developers will become someday become full-stack builders.
Episode notes:
This episode was recorded at Snowflake Summit. You can learn more about CoCo and Snowflake’s other new releases on their website.
Connect with Umesh on LinkedIn or reach out to him at Umesh.Unnikrishnan@snowflake.com
Vivek Raghunathan, SVP of engineering at Snowflake, also sat down this us at this year’s Snowflake Summit to break down the five-stage framework his org used to go from "let chaos reign" to a repeatable, org-wide system for AI-assisted engineering. Listen to his episode of Leaders of Code.
Our sixteenth Annual Developer Survey is now open and we want to hear your thoughts on all things software. Take the survey now!
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How do you turn AI coding chaos into a repeatable playbook?
Vivek Raghunathan, SVP of engineering at Snowflake, joins Leaders of Code at Snowflake Summit to break down the five-stage framework his org used to go from "let chaos reign" to a repeatable, org-wide system for AI-assisted engineering.
Vivek explains how Snowflake systematically rolled out coding agents across its engineering org — starting with unrestricted experimentation, then codifying what worked into a shared vocabulary of 14 "AI design patterns," from plan-in-English to fencing off parallel agents to reducing on-call toil through continuously updated skills. Vivek walks through the "inner loop" and "outer loop" of software development, explains Snowflake's internal Yegge scale for measuring how far engineers have progressed along that continuum, and shares how a three-person team used coding agents to deliver a 40x improvement on Snowflake's query compiler.
The discussion also:
Breaks down Snowflake's "focus weeks," where engineers get dedicated time to either catch up on best practices or push the frontier further.
Explores the pioneers/settlers/skeptics framework for meeting engineers where they are in adopting AI tools, and why the shift can trigger something like the stages of grief.
Covers how Snowflake cut release validation time from 15 days to a single day, and why more automated testing hasn't come at the cost of production stability.
Looks ahead to a four-step maturity model for on-call and incident response, where agents may eventually take primary on-call duty.
Connect with Vivek Raghunathan on LinkedIn.
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
SaaStr 862: The Dashboard Is Dead: What Snowflake's CMO Does Instead
The Dashboard Is Dead: What Snowflake's CMO Does Instead
Denise Persson runs a 700-person marketing organization at one of the most data-rich companies on the planet, and she does not start her morning by logging into a dashboard. She interrogates her data directly, gets answers to questions she used to have to Slack three people about, and moves on. No meetings about the numbers. No debates about what the pipeline data means. No waiting until end of quarter to find out if a campaign worked. In this session, Denise joins SaaStr CAIO Amelia LeRutte to break down what AI-powered marketing actually looks like when you have the scale, the data infrastructure, and the compliance requirements of Snowflake, and what founders and marketing leaders at any stage can steal from the playbook right now.
You'll learn:
How Snowflake cut cost per opportunity by 30% by using agents to optimize media spend in real time across fragmented channels that used to require separate analytics for each
What Denise's morning brief actually contains, from pipeline projections to org health to flagged travel expenses, and why nobody gets a Slack message from her anymore
Why the GTM engineer is the only marketing function Snowflake is actively hiring into, what profiles are converting into the role, and why business analysts are not making the list
How to build AI fluency across a large team without making it mandatory or performative, including the weekly AI challenge, quarterly AI days, and a leaderboard that rewards curiosity over token count
Why data quality is the single most important investment before deploying any agent, and why bad data plus AI just means bad decisions faster and at scale
This is for you if:
You lead a marketing team of any size and want to see what the "most AI-assisted marketing team in B2B" actually looks like in practice, not in a slide deck
You are trying to figure out how to get a large or compliance-sensitive org moving on agents without losing control of what they are doing
You want to understand what the GTM engineer role actually looks like day to day and how to find or develop one inside your existing team
20Sales: The $100M CRO Bubble: Why Anthropic Are Causing a Comp Crisis | Why You Should Never Hire From Salesforce or Service Now | How to Hire, Train and Forecase in a World of AI with Chad Peets and Chris Degnan
Chad Peets is one of the most straight-talking, no BS sales leaders of our time. Today, he partners with founders of the fastest growing companies in the world, like Harvey, Factory to build the best sales teams in a world of AI.
Chris Degnan is a legendary technology sales leader who achieved the historic feat of scaling Snowflake from $0 to $4BN in ARR.
AGENDA:
00:00 – The $100M CRO Packages Nobody Believes Are Real
04:10 – Why Most "Elite" Salespeople Are Actually Just Order Takers
08:00 – The Secret to Hiring Killer Sales Talent at Early-Stage Startups
10:05 – 20x Quotas & The Death of Traditional Pipeline Generation
16:20 – The ARR Scam: Why Most AI Revenue Numbers Are Fake
17:45 – Why the Best Engineers Do Not Want to Be Forward Deployed Engineers
21:10 – Why Paying Everyone the Same Kills Great Sales Organisations
24:15 – Anthropic's Crazy Compensation Is Breaking the Entire Sales Market
29:00 – The Brutal Truth About Replacing CROs & Firing Sales Leaders
32:20 – Forecasting in AI Is Completely Broken
38:20 – The Fatal Mistake Founders Make Chasing Venture Valuations
39:40 – Why Most VCs Give Absolutely Terrible Sales Advice
42:10 – Global Sales From Day One: The New AI Go-To-Market Playbook
44:15 – "Anthropic Is a $5 Trillion Company"
47:40 – The Death of the Traditional SDR & The Rise of Full-Stack AI Sellers
49:00 – Consumption Pricing, Vertical AI & Why SaaS Is Getting Rewritten
52:00 – What the Best Sales Cultures Still Get Right in the AI Era
Snowflake’s transition from storing data to shipping with it
Snowflake is betting that the future of AI isn’t just analyzing data, it’s acting on it. That means a shift away from chatbots and toward autonomous agents that can actually get work done. And Snowflake is reorganizing fast to keep up, from shipping hundreds of AI features to restructuring teams along the way.
On this episode of TechCrunch’s Equity podcast, Rebecca Bellan sits down with Snowflake CEO Sridhar Ramaswamy to unpack the company’s transformation and what it signals about where AI is headed next.
Listen to the full episode to hear:
Why Ramaswamy believes the chatbot era is ending and the agentic era is beginning.
How Snowflake is evolving from a data warehouse into an AI and applications platform.
What “shipping with your data” actually looks like in practice.
Why the company is making big internal changes to support its AI push.
Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod.
Chapters:
00:00 Intro
00:17 Snowflake’s AI shift and agentic future
01:45 Why 2026 marks the end of chatbots
04:09 Cortex Code, Snowflake Intelligence, and new products
06:09 Who benefits: non-technical users & enterprises
07:35 Adoption challenges and why AI pilots fail
12:11 How AI is reshaping jobs and skills
14:39 Layoffs, automation, and the future of documentation
18:37 Snowflake’s evolution into an AI platform
21:04 Competition: Databricks, hyperscalers, and AI giants
25:01 Outro
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#327 Baris Gultekin: The Next Phase of AI - Agents That Understand Your Company's Data
This episode is sponsored by Modulate. Most voice AI focuses on transcription. Velma takes it further by actually understanding conversations, analyzing tone, timing, stress, and intent using its Ensemble Listening Model architecture. Explore the live preview: https://preview.modulate.ai/
Baris Gultekin, Head of AI at Snowflake, breaks down how enterprise AI is actually being built, deployed, and scaled today. From running AI directly inside governed data environments to enabling natural language access across entire organizations, this conversation explores the shift from experimentation to real-world impact.
You'll learn why Snowflake's core philosophy centers around bringing AI to the data, how data agents are transforming decision-making across teams, and what it takes to build trustworthy AI systems with governance, guardrails, and high-quality retrieval at the core.
Baris also shares how leading companies are already saving thousands of hours through AI-driven automation, why culture and leadership determine AI success, and what the future looks like as agents move from pilots to full-scale production.
If you want to understand where enterprise AI is actually headed and what separates hype from real execution, this episode breaks it down.
(00:00) The Evolution of Snowflake AI
(01:40) Baris Gultekin: Background & AI Mission
(02:59) Why AI Must Run Next to Data
(04:29) Inside Snowflake's AI Infrastructure
(09:08) Model Choice vs Product Layer Strategy
(12:16) Building Trust: Governance, Guardrails & Quality
(16:01) How Enterprise Agents Are Built & Orchestrated
(20:10) AI Adoption Across the Entire Organization
(24:39) Reasoning vs Retrieval: What Matters More
(27:43) Real Use Case: Faster Decision-Making with AI
(31:44) AI as a Co-Pilot for Leaders
(36:52) Preparing Data for AI at Scale
(38:46) What the AI Data Cloud Really Means
Who’s Winning The AI Race? + Software’s Future — With Sridhar Ramaswamy
Sridhar Ramaswamy is the CEO of Snowflake. Ramaswamy joins Big Technology Podcast to break down the competitive dynamics in the AI race today, drawing from his experience working at Google and competing with it. We also cover the future of software, looking at whether AI will turn established software companies into "dumb backends." In the second half, we discuss “shadow AI” driving enterprise adoption from the bottom up, the risk of becoming a feature in someone else's platform, and why Chinese open-source models might actually be a net positive for the US. Hit play for a sharp, deeply informed conversation about where AI competition, enterprise software, and the future of work are heading.
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Snowflake VP of AI Baris Gultekin on Bringing AI to Data, Agent Design, Text-2-SQL, RAG & More
Baris Gultekin, VP of AI at Snowflake, explains how “bringing AI to the data” is reshaping enterprise AI deployment under strict security and governance requirements. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. He shares the importance of bringing AI directly to governed enterprise data, advances in text-to-SQL and semantic modeling, and why high-quality retrieval is foundational for trustworthy AI agents. Baris also dives into Snowflake’s approach to agentic AI, including Snowflake Intelligence, model choice and cost tradeoffs, and why governance, security, and open standards are essential as AI becomes accessible to every business user.
LINKS:
AWS' Automated Reasoning checks
Sponsors:
MongoDB:
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MATS:
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Claude
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CHAPTERS:
(00:00) About the Episode
(03:02) Snowflake 101 and AI
(09:25) Text-to-SQL and semantics
(19:10) RAG, embeddings and models (Part 1)
(19:17) Sponsors: MongoDB | Serval
(21:02) RAG, embeddings and models (Part 2)
(32:23) Bringing models to data (Part 1)
(32:29) Sponsors: MATS | Tasklet
(35:29) Bringing models to data (Part 2)
(51:14) Designing enterprise AI agents
(58:35) Trust, governance and guardrails
(01:07:14) Agents and future work
(01:15:33) Platforms, competition and value
(01:26:04) Enterprise models and outlook
(01:40:00) Outro
PRODUCED BY:
https://aipodcast.ing
20Sales: John McMahon on How to Hire, Train & Retain the Best Sales Reps | How Sales Changes in a World of AI | Sales Lessons from Snowflake and MongoDB | How to Create and Drive a Sales Process with Urgency
John McMahon is widely regarded as one of the greatest enterprise-software sales leaders of all time. He's the only person to have served as Chief Revenue Officer at five public software companies: PTC, GeoTel, Ariba, BladeLogic and BMC Software. He helped scale BladeLogic from a startup into a public company — ultimately leading to its ~$880M sale to BMC — and drove GeoTel into a multi-billion dollar acquisition. Today he sits on the boards of top names such as Snowflake and MongoDB, while also mentoring and influencing a who's-who of modern SaaS sales leaders.
AGENDA:
03:33 The Art and Science of Sales: Insights from a Veteran
04:29 Adapting Sales Strategies in the Age of AI and PLG
07:47 The Ultimate Framework to do Deal Qualification
14:13 How to Drive Urgency and Maintain Sales Process
20:06 How to Hire the Best Sales Reps
25:11 Step-by-Step Guide to Training Sales Reps
45:22 The Mindset of the Best Sales Reps
54:55 Single Most Important Skill to Win in Sales
Meet Snowflake Intelligence: A Personalized Enterprise Intelligence Agent with Sridhar Ramaswamy
Snowflake is moving beyond the data warehouse. Its new Snowflake Intelligence is an agentic platform for every employee, not just data teams. Sarah Guo sits down with Snowflake CEO Sridhar Ramaswamy to discuss his first 18 months at the helm, as well as the massive pivot to make the data giant AI-first. Sridhar talks about Snowflake Intelligence, the company's new AI agent platform, and its implications for enterprise data management. They also explore how Sridhar navigates partnerships with major tech companies, how he fosters a culture of continuous improvement within the organization, and how he envisions Snowflake’s future as an integral data-driven enterprise solution.
Sign up for new podcasts every week. Email feedback to show@no-priors.com
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Snowflake
Chapters:
00:00 – Sridhar Ramaswamy Introduction
00:42 – Snowflake’s Market Adaptation
03:14 – Snowflake’s Evolution and AI Integration
05:44 – Introducing Snowflake Intelligence
09:01 – Snowflake Intelligence User Experience
11:55 – Drawing the Line Between Data, Agent System, and App
13:30 – Leadership and Organizational Changes
16:19 – How Being an Investor, Entrepreneur Informed Sridhar’s Leadership
18:50 – Importance of Product-Market Fit
22:46 – Snowflake’s Strategic Positioning
27:10 – Snowflake’s Partnership Strategy
30:20 – How Sridhar Sees the ROI of AI
35:09 – How AI Changes the Ad Model
38:15 – Why LLMs Still Need Search
42:11 – Conclusion
SaaStr 825: How the AI Era Has Directly Impacted Marketing and Sales with Snowflake's CMO and Founding CRO
SaaStr 825: How the AI Era Has Directly Impacted Marketing and Sales with Snowflake's CMO and Founding CRO
Join us for an insightful episode discussing the impact of AI on marketing and sales at Snowflake. Hosts Chris Degnan, founding CRO of Snowflake, and Denise Persson, CMO at Snowflake, delve into how AI has revolutionized their operations. They share key learnings from Snowflake's data cloud market strategies and their record-breaking IPO. Discover the significance of company culture, security, and a centralized data foundation in leveraging AI. Hear about Snowflake's AI Council, customer use cases, task automation, and the consolidation of intelligence teams. Don't miss this comprehensive discussion on the transformative role of AI in the enterprise and valuable hiring insights for staying ahead in the AI era. 00:00 Introduction and Speaker Backgrounds 02:05 Impact of AI on Company Culture 05:09 Snowflake's AI Strategy and Data Security 08:03 AI Use Cases in Marketing 21:26 AI Use Cases in Sales 29:42 Governance and Security in AI Implementation 32:10 AI's Influence on Hiring and Company Growth 34:58 Closing Thoughts and Resources --------------------- This episode is Sponsored in part by Salesforce: Connect data, automate busywork and empower teams like nobody's business with the one platform that grows with you, every step of the way. Learn how Salesforce works for Startups at salesforce.com/smb. ---------------------
This episode is Sponsored in part by Intercom:  Fin is the #1 AI Agent for resolving complex queries like refunds, transaction disputes, and technical troubleshooting—all with speed and reliability. See how Fin can deliver the highest resolution rates and highest-quality customer experience at fin.ai/saastr.
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If you're serious about B2B and AI, you need to be in London this December.
SaaStr AI London is bringing together more than 2,000 leaders and founders for two days of practical advice on scaling into the new year.
We'll have speakers flying in from OpenAI, Wiz, Clay, Intercom, and all your favorite SaaS companies, including yours truly with Harry Stebbings for a live 20VC podcast. It'll be fun, and it's all in the heart of London.
Don't miss out: get your tickets with my exclusive discount by going to podcast.saastrlondon.com
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Hey everybody, the biggest B2B + AI event of the year will be back - SaaStr AI in the SF Bay Area, aka the SaaStr Annual, will be back in May 2026.
With 68% VP-level and above, 36% CEOs and founders and a growing 25% AI-first professional, this is the very best of the best S-tier attendees and decision makers that come to SaaStr each year.
But here's the reality, folks: the longer you wait, the higher ticket prices can get. Early bird tickets are available now, but once they're gone, you'll pay hundreds more so don't wait.
Lock in your spot today by going to podcast.saastrannual.com to get my exclusive discount SaaStr AI SF 2026. We'll see you there.
20Sales: Scaling Snowflake from $0-$3BN in ARR | Snowflake vs Databricks: My Biggest Lessons | Why Customer Success is BS and What Replaces It with Chris Chris Degnan
Chris Degnan is the former Chief Revenue Officer at Snowflake, where he was instrumental in scaling the company from less than $1M in ARR to over $3B in annual revenue. He joined as the first sales hires and built Snowflake's go-to-market engine from scratch, growing the team from to more than 6,000 globally. Under his leadership, Snowflake became one of the fastest-growing enterprise software companies in history, achieving a record-breaking IPO in 2020.
AGENDA:
04:34 How to Build a Sales Team from Scratch 07:49 How to Hire and Evaluate Sales Leaders 15:23 Four Big Lessons Scaling Snowflake to $3BN ARR 31:30 Comparing Snowflake and Databricks: What Databricks Did Better? 35:26 How to Manage Sales Team Morale in Competitive Markets 43:53 Why Customer Success is BS and What To Do With It 48:31 How Every Sales Leader Needs to Change in An AI World 49:37 Biggest Reflections on Sales Leadership 54:38 Quick Fire Questions and Final Thoughts 20Sales: Scaling Snowflake from $0-$3BN in ARR | Snowflake vs Databricks: My Biggest Lessons | Why Customer Success is BS and What Replaces It with Chris Chris Degnan
Leadership Lessons From Snowflake’s Sales & Marketing Duo | Chris Degnan and Denise Persson
Scaling a business globally comes down to leaders who align teams and drive them forward together.
Snowflake serves over 12,000 customers, and early executives Chris Degnan and Denise Persson share how they scaled the company while keeping the unlikely pairing of sales and marketing perfectly aligned through hypergrowth.
They join Joubin Mirzadegan to share insights from their new book, Make It Snow, revealing how they built Snowflake’s ‘go-to-market engine’ and fostered a customer-first culture across every function.
Guests: Chris Degnan, former CRO and advisor to the CEO at Snowflake, and Denise Persson, CMO at Snowflake.
Connect with Chris Degnan
LinkedIn
Connect with Denise Persson
LinkedIn
Connect with Joubin
X
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins:https://www.kleinerperkins.com/
(BNS) How Snowflake Wrote The GTM Playbook
Make It Snow is Snowflake’s go-to-market playbook, told by longtime CRO Chris Degnan and CMO Denise Persson. The central idea: sales and marketing must operate as “one brain in two bodies.” The takeaways are practical and candid: embed with customers sooner than feels comfortable, pick a clear foil, design programs you can rerun, centralize data so sales and marketing act from one truth, and treat culture as GTM infrastructure. If you’re a founder, CRO, CMO, or operator trying to go from zero to billions without losing the plot, Make It Snow is a field manual for aligning people, narrative, and pipeline at every stage.
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Democratizing your data access with AI agents
Jeff Hollan, director of product at Snowflake, joins Ryan to discuss the role that data plays in making AI and AI agents better. Along the way, they discuss how a database leads to an AI platform, Snowflake’s new data marketplace, and the role data will play in AI agents.
Episode notes:
Snowflake provides a fully-managed data platform that developers can build AI apps on.
We’re happy to have Stack Exchange data available on the Snowflake Marketplace.
Connect with Jeff on LinkedIn and Twitter.
Congrats to Timeless for throwing a Lifejacket to Using pandas to read HTML.
TRANSCRIPT
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Warehouse Native Incremental Data Processing With Dynamic Tables And Delayed View Semantics
Summary
In this episode of the Data Engineering Podcast Dan Sotolongo from Snowflake talks about the complexities of incremental data processing in warehouse environments. Dan discusses the challenges of handling continuously evolving datasets and the importance of incremental data processing for optimized resource use and reduced latency. He explains how delayed view semantics can address these challenges by maintaining up-to-date results with minimal work, leveraging Snowflake's dynamic tables feature. The conversation also explores the broader landscape of data processing, comparing batch and streaming systems, and highlights the trade-offs between them. Dan emphasizes the need for a unified theoretical framework to discuss semantic guarantees in data pipelines and introduces the concept of delayed view semantics, touching on the limitations of current systems and the potential of dynamic tables to simplify complex data workflows.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management
Data migrations are brutal. They drag on for months—sometimes years—burning through resources and crushing team morale. Datafold's AI-powered Migration Agent changes all that. Their unique combination of AI code translation and automated data validation has helped companies complete migrations up to 10 times faster than manual approaches. And they're so confident in their solution, they'll actually guarantee your timeline in writing. Ready to turn your year-long migration into weeks? Visit dataengineeringpodcast.com/datafold today for the details.
Your host is Tobias Macey and today I'm interviewing Dan Sotolongo about the challenges of incremental data processing in warehouse environments and how delayed view semantics help to address the problem
Interview
Introduction
How did you get involved in the area of data management?
Can you start by defining the scope of the term "incremental data processing"?What are some of the common solutions that data engineers build when creating workflows to implement that pattern?
What are some common difficulties that they encounter in the pursuit of incremental data?
Can you describe what delayed view semantics are and the story behind it?What are the problems that DVS explicitly doesn't address?
How does the approach that you have taken in Dynamic View Semantics compare to systems like Materialize, Feldera, etc.
Can you describe the technical architecture of the implementation of Dynamic Tables?What are the elements of the problem that are as-yet unsolved?
How has the implementation changed/evolved as you learned more about the solution space?
What would be involved in implementing the delayed view semantics pattern in other dbms engines?
For someone who wants to use DVS/Dyamic Tables for managing their incremental data loads, what does the workflow look like?What are the options for being able to apply tests/validation logic to a dynamic table while it is operating?
What are the most interesting, innovative, or unexpected ways that you have seen Dynamic Tables used?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on Dynamic Tables/Delayed View Semantics?
When are Dynamic Tables/DVS the wrong choice?
What do you have planned for the future of Dynamic Tables?
Contact Info
LinkedIn
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The AI Engineering Podcast is your guide to the fast-moving world of building AI systems.
Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com with your story.
Links
Delayed View Semantics: Presentation Slides
Snowflake
NumPy
IPython
Jupyter
Flink
Spark Streaming
Kafka
Snowflake Dynamic Tables
Airflow
Dagster
Streaming Watermarks
Materialize
Feldera
ACID
CAP Theorem)
Linearizability
Serializable Consistency
SIGMOD
Materialized Views
dbt
Data Vault
Apache Iceberg
Databricks Delta
Hudi
Dead Letter Queue
pg_ivm
Property Based Testing
Iceberg V3 Row Lineage
Prometheus
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
SaaStr 807: Snowflake's CEO on the AI Data Cloud, Partner Strategy, and What's Next
SaaStr 807: Snowflake's CEO on the AI Data Cloud, Partner Strategy, and What's Next
Join Sridhar Ramaswamy, CEO of Snowflake, and Jeremy Burton, CEO of Observe, in a comprehensive discussion led by SaaStr CEO & Founder, Jason Lemkin. Discover the inner workings of Snowflake's Board, the dynamics of strategic partnerships, and the evolving role of AI in data management. Learn how Snowflake aims to be the AI Data Cloud and how Observe integrates with Snowflake to provide scalable analytics. With detailed insights into the partnership strategies, future technological trends, and success stories, this conversation offers a blueprint for leveraging AI and data to drive business value. Don't miss out on the valuable lessons and future predictions shared by these industry leaders.
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This episode of the SaaStr podcast is sponsored by: Attio
This episode is brought to you by Attio — the AI-native CRM. Connect your email, and Attio instantly builds a powerful CRM - with every company, contact and interaction you've ever had. Get 15% off your first year at https://attio.com/saastr
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This episode of the SaaStr podcast is sponsored by: Attention.com
Tired of listening to hours of sales calls? Recording is yesterday's game. Attention.com unleashes an army of AI sales agents that auto-update your CRM, build custom sales decks, spot cross-sell signals, and score calls before your coffee's cold. Teams like BambooHR and Scale AI already automate their Sales and RevOps using customer conversations. Step into the future at attention.com/saastr
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Hey everyone, we just hosted 10,000 of you at the SaaStr Annual in the SF Bay Area, and now get ready, because SaaStr AI is heading to London!
On December 2nd and 3rd, we're bringing SaaStr AI to the heart of Europe. This is your chance to connect with 2,500+ SaaS and AI executives, founders, and investors, all sharing the secrets to scaling in the age of AI.
Whether you're a founder, a revenue leader, or an investor, SaaStr AI in London is where the future of SaaS meets the power of AI.
And we just announced tickets and sponsorships, so don't wait! Head to SaaStrLondon.com to grab yours and join us this December in London.
SaaStr AI in London —where SaaS meets AI, and the next wave of innovation begins. See you there!
EP 147: How Chris Degnan Built Snowflake's Sales Org From Scratch
Chris Degnan is one of the most legendary CROs of this generation. He joined Snowflake as employee #13 and the 1st sales hire. He scaled the sales org from 0 to over $3B in ARR, spanned four CEOs, and retired as CRO after 11 years.
In his first podcast post-retirement, Chris opened his CRO playbook, from early enablement to hiring rigor and fending off threats from competitors. He also reflects on lessons from working with leaders like Frank Slootman, John McMahon, and Sridhar Ramaswamy. If you’re a founder or running sales at a startup, this one is for you.
(00:00) Introduction to Chris's Journey at Snowflake
(01:47) Navigating Leadership Changes
(04:39) The Importance of Sales Methodology and Enablement
(10:22) Near-Death Experiences and Company Resilience
(13:39) Building a Strong Sales Organization
(27:25) Hiring and Scaling the Sales Team
(34:52) Board Dynamics and Mentorship
(44:29) The Influence of John McMahon
(46:22) Leadership Styles and Intuition
(46:56) Launching Snowflake Japan
(49:39) Learning from Leaders
(55:10) The Importance of Competitive Moats
(59:12) Snowflake vs. Databricks
(01:07:45) Public vs. Private Markets
(01:14:03) Sales and Marketing Synergy
(01:26:17) Final Thoughts and Future Plans
Executive Producer: Rashad Assir
Producer: Leah Clapper
Mixing and editing: Justin Hrabovsky
Check out Unsupervised Learning, Redpoint's AI Podcast: https://www.youtube.com/@UCUl-s_Vp-Kkk_XVyDylNwLA
🎙 Listen to the show
Apple Podcasts: https://podcasts.apple.com/us/podcast/the-logan-bartlett-show/id1606770839
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About the Show
Logan Bartlett is a Software Investor at Redpoint Ventures - a Silicon Valley-based VC with $6B AUM and investments in Snowflake, DraftKings, Twilio, and Netflix. In each episode, Logan goes behind the scenes with world-class entrepreneurs and investors. If you're interested in the real inside baseball of tech, entrepreneurship, and start-up investing, tune in every Friday for new episodes.
From data breach scandal to AI darling, with Snowflake’s CEO Sridhar Ramaswamy
It's been a wild few years for Snowflake, from a record-breaking IPO to a plummeting stock price to a data-breach scandal. Sridhar Ramaswamy took over in the heat of the turmoil and helped steady the ship, in part by betting big on AI. Ramaswamy returns to Rapid Response to share lessons from the company's turnaround, including insights behind high profile partnerships with OpenAI and Anthropic, how Snowflake embraced China's Deepseek early, and why Ramaswamy calls Snowflake the most consequential AI-data company in the world.
Visit the Rapid Response website here: https://www.rapidresponseshow.com/
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
20VC: Why Model Providers Will Kill Many Startups Moving into the Application Layer | Why Deepseek is not a Threat to OpenAI & Why OpenAI Beats Anthropic | Apps vs Models vs Infrastructure: Where is Value in AI with Sridhar Ramaswamy, Snowflake CEO
Sridhar Ramaswamy is the CEO @ Snowflake, the $60BN public company with $3.5BN in revenue growing 30% per year. Sridhar joined Snowflake following his company, Neeva, being acquired by them for $150M. Prior to founding Neeva, Ramaswamy spent 15 years at Google where he had an integral part in the growth of AdWords and Google's advertising business from $1.5 billion to over $100 billion.
In Today's Episode We Discuss:
1. OpenAI vs Deepseek vs Anthropic:
Why will OpenAI beat Deepseek? What does no one see with Deepseek that they should see?
Why has OpenAI beaten Anthropic? What elements turn a model from a commodity into a sustaining product suite?
Will model providers become application providers?
Will OpenAI be the biggest killer of startups in the next 10 years?
2. Snowflake vs Nvidia & Databricks:
To what extent is Sridhar concerned NVIDIA will move into the data layer and compete with Snowflake?
How does Sridhar view the competition from Databricks? What have they done better than them? What have they done worse than them and lost on?
Does being private hurt or help Databricks in their fight against Snowflake?
If Sridhar could, would he take Snowflake private today?
3. Leadership, Parenting, Money:
Do richer leaders make better leaders? How does being rich change the mindset of a leader?
What are Sridhar's biggest lessons when it comes to parenting?
What about the way that Sridhar was brought up, did he do deliberately differently with his kids?
EP 121: Snowflake CEO Sridhar Ramaswamy on the Future of AI and Data
Nine months into his role as Snowflake’s CEO, Sridhar Ramaswamy sat down for a candid discussion on the journey so far & what’s ahead.
He uncovered details about his transition to Snowflake CEO, the operational changes he’s put in place to accelerate product development, and his bold predictions for AI’s future—along with how he’s guiding a vision for Snowflake to fit into that landscape.
Sridhar also reflects on how his leadership has evolved, from leading a major Google unit to founding Neeva (acquired by Salesforce) and now running Snowflake.
[0:00] Intro
[0:56] Sridhar’s Journey to Snowflake
[3:37] Snowflake's AI Vision and Cortex AI
[10:35] Innovative Uses of AI at Snowflake
[15:49] Challenges and Future of AI in Business
[21:27] Snowflake's Long-Term AI Aspirations
[25:04] Predictable and Unpredictable Aspects of AI
[26:20] Autonomous Agents and AI Predictions
[27:01] Market Consolidation in AI
[29:54] Journey into AI and Early Experiences
[31:21] The Evolution of AI Models
[32:06] Building Neeva and AI Search Engines
[36:16] Leadership and Product Development at Snowflake
[40:45] Setting Goals and Accountability
[43:25] Leadership Style and Cultural Foundations
[47:25] Career Advice and Finding Your Path
Executive Producer: Rashad Assir
Producer: Leah Clapper
Mixing and editing: Justin Hrabovsky
Check out Unsupervised Learning, Redpoint's AI Podcast: https://www.youtube.com/@UCUl-s_Vp-Kkk_XVyDylNwLA
🎥 Subscribe on YouTube: https://www.youtube.com/channel/UCugS0jD5IAdoqzjaNYzns7w?sub_confirmation=1
Follow on Socials
📸 Instagram - https://www.instagram.com/theloganbartlettshow
📱 X - https://twitter.com/loganbartshow
🎬 Clips on TikTok - https://www.tiktok.com/@theloganbartlettshow
About the Show
Logan Bartlett is a Software Investor at Redpoint Ventures - a Silicon Valley-based VC with $6B AUM and investments in Snowflake, DraftKings, Twilio, and Netflix. In each episode of The Logan Bartlett Show, we sit down with the people behind today’s most important startups and extract the tactics, lessons, and frameworks they’ve learned the hard way. Conversations span hiring to GTM, product, growth, fundraising and everything in between - collectively forming the ultimate playbook to make you a better CEO, investor or board member.
Tap follow and enable notifications to stay ahead of the game.
SaaStr 771: The Top Marketing Strategies for 2025 Growth with the CMOs of Snowflake, LinkedIn, and Carta
SaaStr 771: The Top Marketing Strategies for 2025 Growth with the CMOs of Snowflake, LinkedIn, and Carta
Right now is one of the hardest times of the year for marketers. Most CMOs will be heads down wrapping up a year-end assessment and figuring out what to pitch for next year's budgetary spend to drive revenue, all while navigating an ever-changing environment of inconsistent metrics, lower conversion rates, and a rapid rate of change with the adoption of AI in SaaS.
A CMO panel consisting of the CMO of Snowflake, Denise Persson, CMO of Carta Nicole Baer, and the VP of Marketing at LinkedIn for Sales, Gail Moody-Byrd all answer Carilu Dietrick's questions, CMO and advisor formerly at Atlassian, about all things growth for 2025.
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SaaStr hosts the largest SaaS community events on the planet.
Hey everybody - thanks to the 10,000 of you who came out to SaaStr Annual. We had a blast and big news -- we'll be back in MAY of 2025. That's right, the SaaStr Annual will be a bit earlier next year, May 13-15 2025. We'll still be back in the same venue, in the SF bay area at the 40+ acre sprawling san mateo county events center. Grab your tickets at saastrannual.com with code NOVEMBER20 for an extra discount on our very best pricing.
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This episode is sponsored by: mmhmm.app
Build client relationships faster with mmhmm, the app that helps you impress prospects in every meeting. Create and send recordings that help them get to know you. Try it free on Mac and Windows at mmhmm.app. That's M-M-H-M-M dot app
Snowflake’s CEO Sridhar Ramaswamy on 700+ LLM enterprise use cases
In this episode of Gradient Dissent, Snowflake CEO Sridhar Ramaswamy joins host Lukas Biewald to explore how AI is transforming enterprise data strategies.
They discuss Sridhar's journey from Google to Snowflake, diving into the evolving role of foundation models, Snowflake’s AI strategy, and the challenges of scaling AI in business. Sridhar also shares his thoughts on leadership, rapid iteration, and creating meaningful AI solutions for enterprise clients. Tune in to discover how Snowflake is driving innovation in the AI and data space.
Connect with Sridhar Ramaswamy:
https://www.linkedin.com/in/sridhar-ramaswamy/
Follow Weights & Biases:
https://twitter.com/weights_biases
https://www.linkedin.com/company/wandb
Join the Weights & Biases Discord Server:
https://discord.gg/CkZKRNnaf3
Snowflake CEO Sridhar Ramaswamy on Using Data to Create Simple, Reliable AI for Businesses
All of us as consumers have felt the magic of ChatGPT—but also the occasional errors and hallucinations that make off-the-shelf language models problematic for business use cases with no tolerance for errors. Case in point: A model deployed to help create a summary for this episode stated that Sridhar Ramaswamy previously led PyTorch at Meta. He did not. He spent years running Google’s ads business and now serves as CEO of Snowflake, which he describes as the data cloud for the AI era.
Ramaswamy discusses how smart systems design helped Snowflake create reliable "talk-to-your-data" applications with over 90% accuracy, compared to around 45% for out-of-the-box solutions using off the shelf LLMs. He describes Snowflake's commitment to making reliable AI simple for their customers, turning complex software engineering projects into straightforward tasks.
Finally, he stresses that even as frontier models progress, there is significant value to be unlocked from current models by applying them more effectively across various domains.
Hosted by: Sonya Huang and Pat Grady, Sequoia Capital
Mentioned in this episode:
Cortex Analyst: Snowflake’s talk-to-your-data API
Document AI: Snowflake feature that extracts in structured information from documents
Crucible Moments Returns for S2: The ServiceNow Story ft. CEO Frank Slootman & Founder Fred Luddy
On Training Data, we learn from innovators pushing forward the frontier of AI’s capabilities. Today we’re bringing you something different. It’s the story of a company currently implementing AI at scale in the enterprise, and how it was built from a bootstrapped idea in the pre-AI era to a 150 billion dollar market cap giant.
It’s the Season 2 premiere of Sequoia’s other podcast, Crucible Moments, where we hear from the founders and leaders of some legendary companies about the crossroads and inflection points that shaped their journeys. In this episode, you’ll hear from Fred Luddy and Frank Slootman about building and scaling ServiceNow. Listen to Crucible Moments wherever you get your podcasts or go to:
Spotify: https://open.spotify.com/show/40bWCUSan0boCn0GZJNpPn
Apple: https://podcasts.apple.com/us/podcast/crucible-moments/id1705282398
Hosted by: Roelof Botha, Sequoia Capital
Transcript: https://www.sequoiacap.com/podcast/crucible-moments-servicenow/
#205 CEO Snowflake, Sridhar Ramaswamy: Visibility
Guest: Sridhar Ramaswamy, CEO of Snowflake
“People underestimate what it is to go through a complete reset,” says Snowflake CEO Sridhar Ramaswamy. And he knows it: After an incredible 15-year run at Google, he started over from zero with an AI search startup, Neeva. And in hindsight, he regrets not trying to port over more of the skills that had made him a successful leader before. “You should be truthful with yourself about what is it that you know that you're really good at,” he says.
In this episode, Sridhar and Joubin discuss Morgan Stanley, working with urgency, avoiding comparisons, following your passions, Steph Curry, summer school, the Google bubble, axes of improvement, Vivek Raghunathan, Bill Coughran, Bell Labs, Mark McLaughlin, Nikesh Arora, daily emails, Chris Degnan, competitiveness, aircraft carriers, and size 31 pants.
Chapters:
(01:05) - Travel challenges
(03:55) - Crisis mangement
(08:59) - Parenting
(14:01) - Defining success
(20:37) - From Google to Neeva
(27:57) - Transition troubles
(31:06) - Glean vs. Neeva
(34:08) - Becoming Snowflake’s CEO
(38:41) - Authority
(39:58) - Frank Slootman
(44:24) - Palo Alto Networks
(48:27) - Transparent culture
(50:56) - Sridhar’s morning ritual
(54:23) - Complete visibility
(57:49) - Priorities
(01:00:10) - Snowflake’s stock price
(01:02:33) - Who it’s hiring
Links:
Connect with Sridhar
Twitter
LinkedIn
Connect with Joubin
Twitter
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins
This episode was edited by Eric Johnson from LightningPod.fm
Snowflake's Baris Gultekin on Unlocking the Value of Data With Large Language Models - Ep. 231
Snowflake is using AI to help enterprises transform data into insights and applications. In this episode of NVIDIA’s AI Podcast, host Noah Kravitz and Baris Gultekin, head of AI at Snowflake, discuss how the company’s AI Data Cloud platform enables customers to access and manage data at scale. By separating the storage of data from compute, Snowflake has allowed organizations across the world to connect via cloud technology and work on a unified platform — eliminating data silos and streamlining collaborative workflows.
#175 CEO Snowflake, Frank Slootman: Amped
Guest: Frank Slootman, CEO and Chairman of Snowflake and author of Amp It Up
Snowflake CEO Frank Slootman doesn’t recall a time in his childhood where new achievements were celebrated — because, according to his father, putting everything into your work and “leaving it all on the field” was the only choice. “The problem with it,” Frank says, is that “it becomes a ‘never enough’ dynamic, because when is it enough?” To this day, he comes home on Friday night and asks himself, “Did it mater that I was there? ... If I’m just a passenger on the ship, that’s my nightmare.”
In this episode, Frank and Joubin discuss acting with urgency, Shlomo Kramer, negative role models, Elon Musk, Teddy Roosevelt’s “Man in the Arena” speech, aptitudes and weaknesses, ServiceNow, and the life spark of business.
In this episode, we cover:
Being tough on yourself (00:59)
Sailing and inner peace (03:00)
Confronting your demons (09:07)
Scaling Data Domain (11:15)
Judging talent (15:20)
That gnawing feeling (18:16)
Daring greatly and rejecting pride (21:04)
“Did it matter that I was there?” (25:02)
How you play the game (27:59)
The best version of yourself (29:59)
Learning from the best (34:06)
Sales as inspiration (37:52)
Retirement and Tom Brady (39:09)
The fog of war (41:16)
Snowflake vs. Data Domain (44:31)
Respect for luck (48:48)
Who Snowflake is hiring (50:42)
Links:
Connect with FrankLinkedIn
Buy Frank’s book, Amp It Up: Leading for Hypergrowth by Raising Expectations, Increasing Urgency, and Elevating Intensity
Connect with JoubinTwitter
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins
This episode was edited by Eric Johnson from LightningPod.fm
#173 Author of “The Qualified Sales Leader,” John McMahon: The Five-Time CRO
Guest: John McMahon, author of The Qualified Sales Leader: Proven Lessons from a Five Time CRO
A hell of a lot of people work in sales. But until recently, says five-time CRO and The Qualified Sales Leader author John McMahon, it was rare for colleges and universities to offer a sales degree. Salespeople had to learn on the job from experienced coaches, and adapt. And their bosses, John explains, had to themselves as agents of transformation. “If somebody’s really smart, they’re going to pick up the knowledge,” he says. “If they have what I call a PHD — persistence, heart, and desire — they’re going to learn the skills ... You’re going to have to do thousands and thousands of repetitions before you’re going to get good.”
In this episode, John and Joubin discuss lazy LinkedIn cold calls, Tom Brady’s retirement, being “married to your job,” Carl Eschenbach, crying, sales as a calling, corporate culture vs. coaching culture, adaptable workers, opportunity vs. title, Bob Muglia, transactional leaders, sad rich people, cookie-cutter advice, handshake evaluations, and David Cancel.
In this episode, we cover:
CRO to CEO? (02:21)
Ego and relevance (04:25)
Escaping the 90-day grind (06:25)
Persistence and physical discipline (09:05)
Daily habits and positive energy (14:12)
Why John quit BMC (17:09)
Poor communication (21:17)
Was there another way? (24:37)
Identifying sales talent (28:36)
Showing that you care (32:58)
Sales leaders as hockey coaches (39:46)
Firing people (44:25)
Interviewing the right type of salesperson (49:14)
Snowflake and Chris Degnan (51:22)
“What’s the book on you?” (56:03)
Managing from a position of power (58:01)
The three “whys” (01:00:31)
Why John never went VC (01:04:33)
Is he really done? (01:07:17)
Shlomo Kramer (01:10:20)
Having impact (01:13:11)
Bad advice (01:16:19)
Working with marketing (01:19:32)
Sizing people up (01:21:26)
Can CEOs give up? (01:26:51)
Coaching sales “artists” (01:28:29)
What “grit” means to John (01:30:48)
Links:
Connect with JohnLinkedIn
Buy The Qualified Sales Leader: Proven Lessons from a Five Time CRO
Connect with JoubinTwitter
LinkedIn
Email: grit@kleinerperkins.com
Learn more about Kleiner Perkins
This episode was edited by Eric Johnson from LightningPod.fm
20Sales: Five Lessons Scaling Snowflake to $1BN ARR, Why Customer Success is BS and Should Be Removed, Why All Sales Reps Should Do Eight Calls Per Week & Why You Should Hire a Head of Sales Sooner Than You Think with Chris Degnan, CRO @ Snowflake
Chris Degnan serves as Snowflake's Chief Revenue Officer and has been with the company since 2013. Starting as employee #13 and Sales employee #1, Chris built a go-to-market strategy from the ground up, driving sustained high growth and global reach. Under his sales leadership, Snowflake has grown its annual product revenue from $0 to over $1 billion. Prior to Snowflake, Chris served in Sales leadership roles at EMC and Aveksa, and worked in enterprise sales at Informatica and Covalent Technologies (acquired by VMware).
In Today's Episode with Chris Degnen We Discuss:
1. From SDR To World Leading CRO:
How did Chris first make his way into the world of sales?
What does he know now that he wishes he had known when he started in sales?
What are the single biggest mistakes young sales people make today scaling their careers?
2. The Secret to Hitting Quota in Sales:
Why does Chris believe all reps need to do 8 customer calls per week?
How do the best sales reps approach sales prospecting today?
Is cold outbound dead? How does Chris advise his teams on cold calls and emails?
What are the best reasons reps should say no to customers?
Should reps be discounting today? What is an acceptable level?
3. Sales and Product: The Most Important Relationship:
Why does Chris believe sales and product is the most important relationship?
What can leaders do to ensure sales and product communicate effectively?
How does Chris use sales calls today both with his sales team and with product?
What are the single biggest reasons comms between sales and product breaks?
4. Mastering Sales Leadership:
How does Chris approach sales forecasting? What works? What does not work?
Does Chris celebrate when quota is hit? How do you find the balance between pushing further and harder but also celebrating the wins?
How do the best sales leaders train and develop their talent? What do the worst do?
5. Customer Success is BS: Professional Services for the Win:
Why does Chris believe that customer succeed is BS and you should get rid of it?
Why are professional services so much better?
How should the org be structured then when removing CS and adding professional services?
Who is then responsible for upsell?
