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Growing a Self-Funded Company

Code[ish]

Release Date: 01/05/2021

How Salesforce Leverages Heroku show art How Salesforce Leverages Heroku

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Robbie Birbeck, VP of Digital Enterprise Technology at Salesforce, joins Julián Duque to talk about how Salesforce leverages Heroku. Filmed at the Palace Hotel in downtown San Francisco, the big star of this episode is Agentforce, which helps Salesforce employees with IT and HR questions, among others. 

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Building Agentic Apps with RubyLLM show art Building Agentic Apps with RubyLLM

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Vestmark manages more than 1.7 trillion in assets, and its CTO, Freedom Dumlao, joins Julián Duque to discuss how AI is helping its advisors in their day-to-day work. Filmed at the Palace Hotel in downtown San Francisco, the pair discuss the role of AI in development and why all its new products are being built using Ruby. 

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Engineering Excellence and AI Productivity show art Engineering Excellence and AI Productivity

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In our second video special from the Palace Hotel, Julián Duque is joined by Shiva Nimmagadda, Vice President of Excellence, True AI and Analytics at Salesforce. Together, the pair discuss the various ways his team is using AI to improve developer efficiency, productivity, and output.

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AI Workflows for Support Ticket Integration show art AI Workflows for Support Ticket Integration

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Filmed at the Palace Hotel in downtown San Francisco, this week’s episode of Code[ish] is the first in a short series of video specials!  To kick things off, Julián Duque is joined by Keegan Bakker, CEO of audience engagement platform Audata, to explore how Heroku helped the app grow from a hobby idea to a powerful tool for major organizations across the globe.

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AI Agents and Open Source show art AI Agents and Open Source

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This week on Code[ish], host Julián Duque connects with Rizel Scarlett from Block, Inc., to discuss how agentic AI is changing the FinTech landscape. Block, Inc. is the parent company behind popular services like Square, Cash App, and many more. 

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Getting to the Heart of Twelve-Factor Apps show art Getting to the Heart of Twelve-Factor Apps

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On this week’s episode of Code[ish], Vish Abrams joins Jon Dodson to talk about the role of AI, the ways Twelve-Factor aids developers, and how science fiction shaped a little of their own history.

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Introducing Heroku Vibes show art Introducing Heroku Vibes

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This week’s episode is an exciting one because we’re talking about our brand-new release, Heroku Vibes! Mauricio Gomes joins Jon Dodson to go over what Heroku Vibes is, what it’s capable of, and how it could be a game-changer for developers and non-developers alike.  Join the pilot by visiting

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Talking Traces and OpenTelemetry show art Talking Traces and OpenTelemetry

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Jon Dodson has an 11-year Heroku veteran with him on the podcast this week, Principal Member of Technical Staff Alex Arnell. Together they talk through the native integration of OpenTelemetry in Heroku Fir, the benefits of traces over traditional logs, how they assist debugging, and what’s next for observability in modern development.

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Heroku in the Wild: Vanshiv on Using the Right Tools show art Heroku in the Wild: Vanshiv on Using the Right Tools

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You won’t find too many developers with more experience in the Salesforce ecosystem than our guest this week! Not only is Gaurav Kheterpal a Salesforce MVP and Trailblazer, he also still uses his original Salesforce org from 2007. He joined Julián Duque to discuss how Vanshiv Technologies delivers client work with Heroku, the importance of embracing AI, and why it’s vital for developers to keep an open mind in choosing the right tool for the job.   

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What’s Possible with Heroku AppLink show art What’s Possible with Heroku AppLink

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This week we’re taking a deeply technical dive into our newest feature: Heroku AppLink! Jon Dodson is joined by Chris Wall, Salesforce Architect and creator of AppLink, to explore what AppLink offers developers and how it brings Heroku and Salesforce closer together. 

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Host Greg Nokes is a distinguished technical architect with Heroku. His guests are Alli McGee, a product manager, and Lewis Buckley, a senior application engineer, from BiggerPockets. BiggerPockets was founded 16 years ago to educate non-professionals about real estate investing.

As a self-funded company, it’s critical for BiggerPockets to create products that customers will pay for. One way they achieve this product/market fit is by building cross-functional teams that are user-focused. All product teams have a project manager, tech lead, and designer that work closely together. This design-led approach allows teams to collaborate with representation from users, technology, and design.

As the PM on one of these teams, Alli lives at the intersection of what can we do for business, what can we do from a technology perspective, and what can we do for the user. She advocates for the customer, bringing knowledge of what customers want, what problems they are facing, and how they have interacted with prototypes in usability studies. Alli also advocates for the business to be sure products make money. Finally, Alli advocates for developers to make sure the project is technically feasible and won’t cause technical debt.

Another way BiggerPockets creates market fit is by creating Minimum Lovable Products—the smallest cheapest thing they can build that people love. With their current product, BP Insights, Alli and Lewis used this strategy to create the first iteration of a product that provides insight into local real estate markets. They then tested the product with users, iterated, and slowly built out a more fully formed offering.

For their tech stack, BiggerPockets is built on a Ruby on Rails monolith. While some in the industry say Ruby on Rails’ time is over, Lewis argues that it has been a great choice, as using a well-known stack has allowed them to worry less about the technology and focus more on building value for users. The BP Insights product was built on this monolith using a massive data set of nearly every property in the US. BiggerPockets imported the data to an Amazon S3 bucket and eventually copied the data to Amazon Redshift for querying.