The Subtle Art of Giving Code Walkthrough Talks

DevRelCon 2021 Virtual

Nov. 2021

Ricardo Ferreira

Slides

Abstract

If your audience is developers, then there is a high chance that you will need to show how code works in one of your talks. While you can always play safe and show snippets of code through slides — giving people code walkthroughs is often a more effective method to see the code where it really matters: in the development environment. But doing so can be a daunting task. Not so much because you may not know the code — but because now your content is the code. So many moving parts now need to be addressed by your code walkthrough, the talk’s timing, how much the audience will absorb, the outcomes you want people to have, and how exciting your talk will be if using this method. In this talk, Ricardo will explain what best practices you should follow to nail your following code walkthrough, so your talk becomes memorable. It will do it by providing an utterly wrong code walkthrough example that will be polished during the talk to highlight each best practice.

Video

© 2018 - 2026 Ricardo Ferreira

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Open Source

I contribute to LangChain4j, an idiomatic open source Java library for building LLM-powered applications on the JVM. Recent work includes adding native vector search embedding stores so developers can build RAG, recommendation engines, and AI memory systems.

I also ported RedisVL to Go, an open source, AI-native client that brings vector search, semantic caching, LLM memory, semantic routing, rerankers, and an MCP server to the Redis ecosystem for Golang developers.

Speaking

I’ve been speaking at conferences since 2008 and doing it full time as part of my work since 2018. Some of the events I’ve spoken at include AWS re:Invent, Microsoft Ignite, Google Cloud Next, KubeCon, Oracle OpenWorld, QCon, Strange Loop, Kafka Summit, Pulsar Summit, JavaOne, DevNexus, JFokus, JNation, and All Things Open.

Recordings of my talks live on my YouTube channel, and the code I write for talks, demos, and tutorials is on my GitHub.

Who am I?

I work at the intersection of distributed systems, AI, and data infrastructure, turning complex technology into things developers can understand, adopt, and build with.

Lately, that means hands-on AI engineering: building vector search, semantic caching, agent memory, and RAG into the data layer; contributing to LangChain4j and RedisVL for Golang; and figuring out how to make AI agents secure enough to ship.

The AI-native work isn’t a pivot. It draws on the same systems-design foundation I’ve built for 20+ years, moving data fast, at scale, close to compute, watching where systems break; now applied to vectors and agents. I have worked on event streaming with Apache Kafka and Flink at AWS and Confluent; observability at Elastic; as well as RDBMS, NoSQL, and Big Data at Oracle. That foundation is exactly what separates AI demos that work on stage from AI systems that survive production.

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