What happens when the model can’t fix it? Interview with Software Engineer Landon Gray (Podcast #213)

by SkillAiNest

Today Quincy Larson interviews Landon Gray. He is a software engineer who worked in agencies for years. Then he taught himself AI-assisted software development. And now he’s helping other devs do the same.

Landon is best known for proving that RAG pipelines can be written in Ruby and popularizing Ruby as a language for building machine learning projects.

He works as an AI engineer at an enterprise software company and runs a popular newsletter.

We talk about:

  • How big language models are just raw fuel, and harnesses are the real engine to do the work

  • Why building your professional network is so helpful for finding clients and getting job interviews.

  • Why Landon helped port Python machine learning libraries to Ruby, and why he thinks that – now that AI is just an API call away – the Ruby ecosystem is in a better position than ever.

Watch the podcast on freeCodeCamp.org YouTube Channel Or listen on your favorite podcast player.

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Links to our conversation:

Community News Section:

  1. freeCodeCamp just published a new YouTube course that will teach you basic front-end development skills like HTML, CSS, and JavaScript. You can code at home and create a variety of projects: your own interactive quiz game, a currency converter app, and even a Trello-style Kanban board. Along the way you’ll learn how to use APIs and local storage to extend the functionality of these bite-sized apps. (12 Hour YouTube Course):

  2. Learn how to properly test your software and make sure it doesn’t break when you add new features. Prolific Freecode Camp instructor Beau Kearns teaches this course. He’ll introduce you to the testing pyramid and show you how to balance fast unit tests against complex user journeys. You’ll also learn how to automate some of this testing using an open source library called Playwright and the LLM testing tool. (1 Hour YouTube Course):

  3. More and more apps are relying on deterministic API calls as well as probabilistic LLM output. This makes life difficult for devs who now need to make sure that users don’t get bogged down. freeCodeCamp has just published this advanced observational tutorial that will teach you emerging best practices and architectural patterns to tackle this. (Read 40 minutes):

  4. Learn how to containerize your MLOps pipelines. This tutorial is the result of hard-won deployment wisdom. The author spent three weeks debugging a Python library error due to dependency conflicts. The ultimate answer: containerize the entire project with Docker. This tutorial will show you how to structure your containers with multi-stage builds. You’ll also learn how to set up experimental tracking with MLflow, versioning with DVC, GPU passthrough, and other advanced techniques. (Read 40 minutes):

  5. Today’s Song of the Week is from 2006 by UK producers Basement Jacks. If you’re familiar with their work, you know you’re in for a psychedelic yet silly romp. Between the spoons, the bongos, and the nonsensical chorus, the song feels like it was held together with duct tape but it works.

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