Updated September 2026, 1 week ago
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![What happens when the model CANT fix it? Interview w/ software engineer Landon Gray [Podcast #213]](https://i.ytimg.com/vi/tZef2ZzbyuQ/mqdefault.jpg "What happens when the model CANT fix it? Interview w/ software engineer Landon Gray [Podcast #213]
Today Quincy Larson interviews Landon Gray. Hes a software engineer who worked at agencies for years. Then he taught himself AI assisted software development. And now hes helping other devs do the same.
Landons famous 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 a enterprise software company and runs a popular newsletter.
We talk about:
- How Large Language Models are just the raw fuel, and harnesses are the real engine to get things done
- Why building your professional network is so helpful for finding clients and landing 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 better-positioned than ever.
Support for this podcast comes from the 10,113 kind folks who donate to our charity each month. Join them and support our mission at https://donate.freecodecamp.org
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Links from our discussion:
- Landons Substack newsletter: https://landongray.substack.com
Community news section:
1. freeCodeCamp just published a new YouTube course that will teach you beginner Front-end Development skills like HTML, CSS, and JavaScript. You can code along at home and build a variety of projects: your own interactive quiz game, a currency converter app, and even a Trello-style kanban board. Along the way youll learn how to use APIs and local storage to extend the functionality of these bite-sized apps. (12 hour YouTube course): https://www.freecodecamp.org/news/build-19-web-dev-projects-using-html-css-javascript/
2. Learn how to properly test your software and ensure it doesnt break when you add new features. Prolific freeCodeCamp instructor Beau Carnes teaches this course. Hell introduce you to the Testing Pyramid and show you how to balance fast unit tests against complex end-to-end user journeys. Youll also learn how to automate some of this testing using an open source library called Playwright and an LLM testing tool. (1 hour YouTube course): https://www.freecodecamp.org/news/software-testing-with-playwright/
3. More and more apps are relying on probabilistic LLM output alongside deterministic API calls. This makes life harder for devs who now need to ensure that hallucinations dont escape to end users. freeCodeCamp just published this advanced observability tutorial that will teach you emerging best practices and architectural patterns for dealing with this. (40 minute read): https://www.freecodecamp.org/news/build-end-to-end-llm-observability-in-fastapi-with-opentelemetry/
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. His eventual answer: containerize entire project with Docker. This tutorial will show you how to structure your containers with multi-stage builds. Youll also learn how to set up experiment tracking with MLflow, versioning with DVC, GPU passthrough, and other advanced techniques. (40 minute read): https://www.freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/
6. Todays song of the week is 2006s Everybody by UK producers Basement Jaxx. If youre familiar with their work, you know youre in for a psychedelic yet silly romp. Between the spoons, bongos, and swooning chorus the song feels like its held together with duct tape but it works. https://www.youtube.com/watch?v=OrMot81VE8g
00:00 Intro & New Courses: Front-End (HTML/CSS/JS), Testing (Playwright), and MLOps (Docker/LLMs).
02:15 Song of the Week and how to support Free Code Camp.
03:16 Landon Gray on AI-assisted dev and Harnessing LLMs for structured outputs.
08:12 Iterative cycles, defining AI vs. Data roles, and avoiding black box engineering.
16:41 Creative solutions for model latency and reliability.
19:20 AIs impact on code quality and the importance of cultivating Taste.
24:25 Inbound job searches, building in public, and the dangers of career isolation.
32:25 Specializing in your Top 10% and practicing servant leadership.
40:02 Consulting tips: Rapid learning, closing deals, and avoiding unmotivated buyers.
51:41 The rise of niche teams and selling strategy over raw code.
58:44 Protecting your reputation, researching culture fit, and preventing burnout.
1:11:32 Client trust and value-based pricing.
1:18:00 Why Ruby/Rails is a powerful alternative for rapid AI/SaaS development.
1:24:46 Networking at conferences and the power of community support.")
