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Workshop Wednesdays - Growth Tactics For Technical Buyers with Weights & Biases

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Growth Tactics For Technical Buyers with Weights & Biases Lavanya Shukla, VP of Growth at Weights & Biases

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Workshop Wednesdays - Growth Tactics For Technical Buyers with Weights & Biases
FUEL
A framework for
exponential
growth
Lavanya Shukla
VP of Growth,
Weights & Biases
Team Background
● OpenAI
● Google
● Waymo
● Microsoft
● DataRobot
● Stanford
● Harvard
● Berkeley
● Twitter
● MongoDB
Figure Eight (acquired by Appen)
● Meta
● Github
● Domino
● JP Morgan
● Alteryx
Funding
Angels & Advisors
Richard Socher — Chief Scientist, Salesforce
Greg Brockman — CTO, OpenAI
Nat Friedman — CEO, GitHub
Tom Preston-Werner — Founder, GitHub
Anthony Goldbloom — Founder and CEO, Kaggle
Vladlen Koltun — Chief Scientist, Intel
Lukas Biewald, CEO
Co-Founder & CEO
Figure Eight, Powerset, OpenAI
Chris Van Pelt, CISO
Co-Founder & CISO
Figure Eight, Powerset
Shawn Lewis, CTO
Co-Founder & CTO
Beep, Google
Weights & Biases
#1 End-to-end MLOps Landscape | W&B Positioning
Chris, MLOps
Manage ML infra, need to
ensure platform security,
model governance, and
efficient resource utilization
DATA MANAGEMENT & STORAGE DISTRIBUTED TRAINING MODEL OPTIMIZATION MODEL SERVING
Carey, ML Practitioner
Build ML models to solve
business problems, need
simple, collaborative,
productive way of build &
manage models
Data Lake & Warehouse Data Storage
W&B Managed
Storage
Platform agnostic, default to best-of-breed
Abstract away infra
details with
declarative,
composable, low-
code workflow
Provide visibility &
control into
deployment details
for optimization &
governance
Data Exploration &
Preparation
Model Training
Model Evaluation &
Selection
Model
Mgmt &
CI/CD
Model
Monitoring &
Governance
W&B
standard
workflow
Version data
& pipelines
Artifacts
Data prep,
visualize
Tables
Experiment
tracking
Experiments
W&B Platform abstraction & extensibility toolkit
Optimize
models
Sweeps
Evaluate
models
Evaluation
Model
Repository
Models
Production
monitoring
Production*
Orchestrate
training
Communicate
& collaborate
Reports
Launch
W&B – 2012
Users
Experiments
Flywheels
Learnings
FUEL: A Framework For Exponential Growth
● Build flywheels not funnels
● Set a northstar metric.
Be obsessive about optimizing it.
● Start measuring everything now
Flywheels

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Workshop Wednesdays - Growth Tactics For Technical Buyers with Weights & Biases

  • 2. FUEL A framework for exponential growth Lavanya Shukla VP of Growth, Weights & Biases
  • 3. Team Background ● OpenAI ● Google ● Waymo ● Microsoft ● DataRobot ● Stanford ● Harvard ● Berkeley ● Twitter ● MongoDB Figure Eight (acquired by Appen) ● Meta ● Github ● Domino ● JP Morgan ● Alteryx Funding Angels & Advisors Richard Socher — Chief Scientist, Salesforce Greg Brockman — CTO, OpenAI Nat Friedman — CEO, GitHub Tom Preston-Werner — Founder, GitHub Anthony Goldbloom — Founder and CEO, Kaggle Vladlen Koltun — Chief Scientist, Intel Lukas Biewald, CEO Co-Founder & CEO Figure Eight, Powerset, OpenAI Chris Van Pelt, CISO Co-Founder & CISO Figure Eight, Powerset Shawn Lewis, CTO Co-Founder & CTO Beep, Google Weights & Biases
  • 4. #1 End-to-end MLOps Landscape | W&B Positioning Chris, MLOps Manage ML infra, need to ensure platform security, model governance, and efficient resource utilization DATA MANAGEMENT & STORAGE DISTRIBUTED TRAINING MODEL OPTIMIZATION MODEL SERVING Carey, ML Practitioner Build ML models to solve business problems, need simple, collaborative, productive way of build & manage models Data Lake & Warehouse Data Storage W&B Managed Storage Platform agnostic, default to best-of-breed Abstract away infra details with declarative, composable, low- code workflow Provide visibility & control into deployment details for optimization & governance Data Exploration & Preparation Model Training Model Evaluation & Selection Model Mgmt & CI/CD Model Monitoring & Governance W&B standard workflow Version data & pipelines Artifacts Data prep, visualize Tables Experiment tracking Experiments W&B Platform abstraction & extensibility toolkit Optimize models Sweeps Evaluate models Evaluation Model Repository Models Production monitoring Production* Orchestrate training Communicate & collaborate Reports Launch W&B – 2012
  • 6. ● Build flywheels not funnels ● Set a northstar metric. Be obsessive about optimizing it. ● Start measuring everything now Flywheels
  • 7. Growth Funnel Growth Flywheel Awareness First Run Product Activated Product Qualified Lead Weekly Engaged User Discover The Product Use The Product Build Publicly On The Product 1. Build Flywheels Not Funnels
  • 8. Discover The Product Use The Product Build Publicly On The Product W&B’s Growth Flywheel - Content
  • 9. Be obsessive about optimizing it. Manager, Executive 3x user base Grow 2.1% weekly Userbase ● Weekly ● Engaged ● Cloud or Local users Grow Create model Fit & deploy model Create internal platform Manage team Academic, Researcher ML Practitioner ML Ops Engineer 2. Set a northstar metric.
  • 10. ● WEUs ● New Users per week ● New Users by channel 3. Start Measuring Everything Now
  • 11. ● Find your PIC ● Behind every metric you want to move is a decision you want the user to make. Users
  • 12. Intent What problem are they trying to solve? Channel Where are they hanging out? Persona Who is the user? 1. Find Your PIC
  • 13. Carey ML Practitioner Build ML models to solve business problems, continuously manage & improve models for better business outcome Chris MLOps Manage ML infrastructure, ensure platform uptime, security, model governance, and efficient resource utilization Morgan CTO / CDO Responsible for the business outcome of the company’s ML activities, cultivate data-driven culture & tech competency Adrian ML Team Lead ML budget owner, response to business needs & allocate team resources to high-ROI projects Tim Responsible AI (emerging persona) Govern & mitigate risks from the potential adverse consequences of decisions; Responsible AI, AI Ethics, Explainable AI 1. Find Your PIC
  • 14. Train Models Discover Reports Write Report User Journey – Creating a report 2. Behind every metric you want to move is a decision you want the user to make.
  • 15. Content Loop – Reports Published By Users
  • 16. ● Finding good experiments to run ● How to run experiments? Experiments
  • 17. Quantitative - what is happening Build mini models Qualitative - why is it happening Talk to customers/potential customers and aggregate answers 1. Finding good experiments to run
  • 18. Other Communities Twitter, Towards Data Science, HN, MadeWithML Github Building and using repos Google Finding solutions Kaggle Building their portfolio, learning new techniques Academics Grad Schools, Labs Using Complementary Tools HuggingFace, RayTune, PyTorch Go where your core users are 1. Finding good experiments to run
  • 20. Discover The Repo Use The Repo Integration Integrate Into Public Repo Oct 1 2019 Jan 1 2020 Apr 1 2020 Jul 1 2020 Oct 1 2020 Jan 1 2020 Apr 1 2021 Jul1 2021 Oct 1 2021 Jan 1 2022 Apr 1 2022 Jul 1 2022 W&B’s Growth Flywheel - Repos
  • 21. 2. How to run experiments?
  • 22. 1. The real job of a growth team is to build a machine that gets better at running experiments over time
  • 23. ● The real job of a growth team ● Create Playbooks. Productionize learnings. Learnings
  • 24. ● Data driven... and creative ● Know your user inside out ● Care about building in public ● Great writers or speakers ● Gumption, Grit, Honesty and Curiosity ● Talk to them about strategy & prioritization … constantly How To Build A Growth Team
  • 26. Good Luck! Twitter: @lavanyaai Email: lavanyashukla@gmail.com