Getting to the Heart of Twelve-Factor Apps
Code[ish]
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
Code[ish]
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
Code[ish]
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
Code[ish]
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
Code[ish]
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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Agentforce for Developers
Code[ish]
Salesforce Principal Developer Advocate Mohith Shrivastava joins us on Code[ish] this week to share a few tips and tricks for using Agentforce! Speaking with Julián Duque, the pair cover a range of insightful dev topics including working with agents, vibe coding, programmatic deployment, and more.
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Looking into the Future of Agentic AI with Kit Merker
Code[ish]
At the bleeding edge of computer vision is Plainsight Technologies, a company that’s modernizing infrastructure to handle future agentic AI workloads. Join us as we speak with CEO Kit Merker on Plainsight’s vision for the future, technological goals, and the leading case studies for computer vision. Hear from host Julián Duque and Kit Merker in this new, insightful episode of the Code[ish] podcast.
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Heroku in the Wild: reinteractive on AI and Rapid POCs
Code[ish]
We love hearing from developers who are building amazing things with Heroku, and this episode of Code[ish] is a perfect example! CEO of Australian firm reinteractive, Errol Schmidt, is here to speak with Julián about what his team has achieved and what they’re working on next. Together, they discuss why Heroku is the best tool for Ruby on Rails development, how organizations can safely integrate AI, and the importance of being able to quickly stand up proof-of-concept apps.
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Spring Boot with Guest Josh Long
Code[ish]
This week, Julián is joined by the first Spring Developer Advocate and Java champion, Josh Long! Tune in as the pair discusses Spring Boot and tools like Spring AI, Spring Modulith, Spring Cloud, and Spring Shell that build upon it. If you're a Java veteran like Josh, or returning to it after years away like Julián, this Tips & Tricks episode of Code[ish] will bring you up to speed.
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Getting Started with Slack Apps and Slack AI
Code[ish]
Slack can be so much more than a way to chat with your colleagues. In this episode of Code[ish], we’re joined by Maria José Hernández to find out how Slack Apps and Slack AI can elevate the app into an organization-wide, personalized Work OS. In conversation with Julián Duque, Maria shares insights into the tools available for developers, and what’s included in the Slack Developer Program. Whether you’re pro-code or no-code, this episode is packed with valuable information to help you build, innovate, and improve your workday with Slack.
info_outlineHost 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.