Software Snack Bites Shomik Ghosh of boldstart ventures

This episode is for builders experimenting in AI. We dive deep into technical aspects of agent based workflows, data models, and interesting new fundamental research.
Madhav Singhal is a lead AI researcher at Replit focused on the frontier of what AI can enable for Replit users. In this episode, we dive into specific applications of models across code generation, testing, programming languages and more. We get fairly technical into how data maps to ML models and the types of agent based workflows that work today or may work in the future. We cover why focusing time on new model architectures may not be as relevant for founders to spend time on and how everything with new technology always maps to thinking about what solves the core problem efficiently. Enjoy this deep dive into the technical aspects of agent based workflows.
Where to Find Madhav:
* Twitter: https://x.com/madhavsinghal_
* LinkedIn: https://www.linkedin.com/in/ms337/
Where to Find Shomik:
* Twitter: https://twitter.com/shomikghosh21
* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
* Software Snack Bites Podcast: Apple Podcasts, Spotify, Google.
In this episode, we cover:
(00:40) – What does Replit do?
(02:40) – Tackling Data Bottlenecks and the Shape of the Data
(05:50) – Evolution of LLM Usage & Orchestration
(07:58) – Synthetic Data Use Cases
(11:25) – Background Behind Replit’s Program Repair Agent
(14:48) – Sampling Petabytes of Data a Day for ML
(16:06) – Handling Models Across Programming Languages
(17:12) – When to Pretrain Models and Use Smaller Models
(21:53) – Narrower Problems Means Less Hallucinations
(23:05) – Real-Time Inference
(25:51) – How Madhav Allocates His Research Time
(28:00) – Choosing Mixture of Experts or Model Merging Based on Product Use Case
(30:00) – Multi-Modal Applicability for Code
(33:25) – Why New Model Architectures Don’t Necessarily Benefit Users
(34:46) – Binary Embeddings Improving Memory & Performance for Agents
(36:18) – Agent Based vs CoPilot Approaches
(38:45) – Replit’s Culture & How They Ship So Fast
(41:57) – Simple vs Complex Agent Use Cases
(43:56) – New Paradigm: IDE Specific Workflow Models
(49:20) – Wrap Up
Show Notes:
IDE Specific Agent Workflows


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com

This episode is perfect for those interested in tactical advice from seed stage to IPO around marketing tactics and sales compensation.
Meghan Gill is SVP Sales Operations & Sales Development at MongoDB. She previously joined as employee #8 and has scaled with the org over the past 15 years. In this episode, we cover tactical learnings about early and scaled marketing & sales compensation approaches. We tackle how to incentivize sales teams and how educational content can be effective lead gen for an early go-to-market motion. Meghan also shares many anecdotes from the scaling journey at MongoDB with advice for founders along the way.
Where to Find Meghan:
* Twitter: https://x.com/meghanpgill?lang=en
* LinkedIn: https://www.linkedin.com/in/meghanpgill/
Where to Find Shomik:
* Twitter: https://twitter.com/shomikghosh21
* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
* Software Snack Bites Podcast: Apple Podcasts, Spotify, Google.
In this episode, we cover:
(00:50) – Joining MongoDB as Employee 8
(04:37) – Moving from Marketing into Sales Ops
(05:45) – Setting Appropriate Sales Compensation
(07:08) – What Early MongoDB Got Right
(08:30) – Early Criticism
(10:27) – Do Things That Don’t Scale Moment
(12:08) – Early Enterprise Customers
(13:42) – Early NoSQL Messaging & Positioning
(16:55) – What Meghan Would Tell Herself Back as Employee 8
(18:30) – Managing 3 Kids While Building Startups
(19:50) – How Meghan Scaled Across Stages
(24:10) – Incentivizing Reps with New Product Rollouts
(26:20) – Focus Drives Efficiency
(29:05) – Career Advice
(31:00) – Early Marketing
(33:13) – Early Pricing
(34:18) – When to Make First RevOps Hire
(36:42) – What Are Common Mistakes with Sales Quotas
(39:45) – When to Adjust Sales Compensation
(40:57) – Most Common Advice Meghan Gives Around Marketing
(42:37) – Education Content as a Marketing Engine
(44:00) – Wrap Up


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com

For those curious about the $25B valued business of Canva, this episode is the deep dive you’ve been waiting for.
Sandy Kory is the Founding Partner of HorizonVC, an early stage VC fund, and an angel investor in Canva. In this episode, we cover everything about the company. How it scaled to $2B ARR growing 50-60% while being cash flow positive, it’s unique product and go-to-market motion, and how AI will continue to drive the next leg of future growth. Sit back and enjoy this masterclass on Canva.
Where to Find Sandy:
* Twitter: https://x.com/sandykory
* LinkedIn: https://www.linkedin.com/in/sandykory/
* Blog: https://sandykory.substack.com
Where to Find Shomik:
* Twitter: https://twitter.com/shomikghosh21
* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
* Software Snack Bites Podcast: Apple Podcasts, Spotify, Google.
In this episode, we cover:
(00:37) – Canva’s Founding Story
(06:38) – How Sandy Invested in Canva
(08:50) – Canva’s Scale & Revenue Composition
(11:30) – Canva’s Early Land Use Case
(14:27) – Core Land Use Cases Today
(17:45) – Becoming a Platform
(19:47) – M&A Strategy
(21:50) – Personas Who Use the Product
(24:06) – TAM Estimate
(28:34) – Competitive Landscape
(31:15) – Pricing Model & User-Led Motion
(36:30) – Distribution Channels
(38:14) – Evaluating Canva’s Moats
(42:10) – Australia’s Startup Ecosystem
(44:25) – Future Product & Market Evolution for Canva
(46:50) – Potential Risks Ahead
(50:10) – Text to Video Product
(52:22) – Wrap Up


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com

For those interested in learning about how tech powers capital markets and how enterprises approach digital transformation, this is the episode for you.
Sid Bala is the CIO of Data & Analytics at BNY Mellon. He is also Head of Public Cloud at the bank. In this episode, we chat about how to approach enterprise scale transformations & architecture and taking a portfolio approach to using new and existing tech. We also cover the use cases for Generative AI and how data sharing advancements across enterprises will continue to change the landscape in the future. This is a great peek into how an enterprise leader is thinking about future use cases that enterprise software could help with.
Where to Find Sid:
* LinkedIn: https://www.linkedin.com/in/coffeehead/
Where to Find Shomik:
* Twitter: https://twitter.com/shomikghosh21
* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
* Software Snack Bites Podcast: Apple Podcasts, Spotify, Google.
In this episode, we cover:
(00:40) – Sid’s Background in Enterprise Scale Tech Transformations
(02:50) – “The Art of the Possible”: Shifting to the Cloud at Large Enterprises
(08:41) – Justifying Large Scale Tech Modernization & Migrations
(12:20) – Enterprise Architecture
(13:30) – Knowing Your Own Identity
(16:25) – BNY Mellon’s Data & Analytics Platform
(19:17) – How Enterprise Can Learn From Startups
(21:00) – When to Explore New Tech Vs Improve Existing Tech
(24:17) – How Data Sharing Across Enterprises is Unlocking New Opportunities
(25:54) – Shifting from the World of Math to World of Verbal with Generative AI
(30:52) – Taking a Portfolio Approach to GenAI vs Current ML Use Cases
(33:18) – Tying Innovation to Client Needs
(34:38) – GenAI Unlocking Knowledge in Codebases & Shortening Code Review Cycles
(38:32) – How Startups Can Effectively Sell to Enterprises
(42:12) – What’s Coming Up for BNY Mellon
Show Notes:
BNY Mellon & Microsoft Strategic Alliance for Data & Analytics Platform
BNY Mellon ML Trade Settlement Models



This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com

For those interested in learning about OneTrust (last valued at $4.5B), this is the episode for you.
Kumar Gautam is a Partner at Sands Capital, a multi-strategy asset manager where he focuses on the late stage venture practice. In this episode, we do a deep dive into OneTrust, the ~$500M ARR business that is scaling rapidly in the data privacy, trust & GRC space. We cover all the aspects of the business in depth including the platform, customer use cases & personas, competitive landscape, go-to-market motion, and the future ahead.
Where to Find Kumar:
* Twitter: https://twitter.com/kumargautam11
* LinkedIn: https://www.linkedin.com/in/kumar-gautam-8736996/
Where to Find Shomik:
* Twitter: https://twitter.com/shomikghosh21
* LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
* Software Snack Bites Podcast: Apple Podcasts, Spotify, YouTube
In this episode, we cover:
(00:33) – Founding Story of OneTrust
(03:34) – OneTrust Scale (ARR, FCF, Customer Scale)
(05:06) – Why Cookie Collection is Only the Tip of the Iceberg
(09:24) – Overview of OneTrust Platform’s Components
(12:45) – Buyer & User Personas
(14:29) – Customer Pain Points & Case Study
(19:12) – OneTrust’s TAM
(20:58) – Competitive Landscape
(23:40) – How OneTrust Prices & Generates Revenue
(25:48) – Go-To-Market Motion Behind 14k+ Customers
(27:55) – Why First Party Data is So Valuable
(30:13) – OneTrust’s Moat
(33:42) – Indirect Network Effects Benefiting the Business
(34:58) – Regulations, Data Management, & Consumer Expectations
(37:15) – Future Risks
(39:12) – Wrap Up
Where to Listen:
* Apple Podcasts, Spotify, YouTube


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com

This episode is a great balance of the high level impact of AI & Cloud on enterprise use cases and detailed tech deep dives behind how they’re powered. Whether you’re a CIO, Founder, or IC, there’s stuff in here for everyone.
James Barney is Director of Cloud Platform Engineering at Ally Financial. He previously was a data engineer at Accenture and Lowe’s. In this episode, we cover how Ally as a digital bank builds and utilizes cloud technology to deliver a great experience to customers. We talk about migrating through modern tech transitions, centralizing data for internal teams’ efficiency, and of course the impact of AI. James discusses where he sees the impact of AI on enterprise workflows in the future and how to manage the challenges around using LLMs.
Where to Find James:
·       LinkedIn: https://www.linkedin.com/in/james-barney/
Where to Find Shomik:
·       Twitter: https://twitter.com/shomikghosh21
·       LinkedIn: https://www.linkedin.com/in/shomik-ghosh-a5a71319/
·       Podcast: Apple Podcasts, Spotify, YouTube.
In this episode, we cover:
(01:50) – Migrating to Hadoop & Centralizing Data at Lowe’s
(07:31) – Ally’s Early Cloud Journey
(10:50) – How Ally Innovates Using Modern Technology
(15:46) – Managing Downtime in Systems
(18:58) – Building a Cloud Workload, Security & FinOps Internal Developer Platform
(26:04) – Utilizing GenAI for Platform Eng Use Cases
(30:02) – How Good Are LLMs at Text to SQL
(34:50) - AI’s Impact of Access to Knowledge Across the Org
(38:08) - What’s Slowing Down Potential Enterprise Adoption of GenAI
(42:27) - Wrap Up
Show Notes:
* PII Masking Module for Langchain
* Early Efforts into Generative AI
* Ally Tech Blog
How to Subscribe:
Available on Apple Podcasts, Spotify, YouTube.


This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit shomik.substack.com