Developer Relations Explained
Tags: devrel, ai, machinelearning, startup
Published: 2021-08-06 07:19:12

![image](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/9gipq380voyid7871rir.png)

A couple of weeks ago I published a [blog about MLOps](https://faun.pub/what-is-mlops-9c1ad1723c1b) and mentioned how I'd "given up trying to explain what I do to non-technical friends and family". I foolishly implied that the fault is theirs for not understanding the technology I work with or my niche job role. The reality is that it's **totally my fault** because I clearly haven't figured out a concise way to explain what I do. The more I think about it, the more I realise that being able to explain my job in simple terms actually helps *me* to define my role far more than it helps anyone else. Being totally honest, you probably don't even care what I do anyway. So here goes…

## Developer Relations

Let's start with, arguably, the easier part - Developer Relations. Sometimes called Developer Advocacy, Developer Evangelism or DevRel (if you're one of the cool kids 😎) the job is a weird blend of responsibilities.

The `Developer` part of it is pretty easy to comprehend - basically everything DevRel does is related to software developers. This is actually a really important distinction because, as you'll come to see, a lot of the functions DevRel provides overlap with more traditional job roles.

The `Relations` term is where it becomes a lot more unclear. I usually try to explain this bit using these three commonly understood jobs:
* **Marketing **- driving awareness and usage of your product or brand
* **Software Engineering** - writing code and documentation for your product 
* **Product Management** - gathering user feedback and understanding market trends to improve your product

But those three jobs already exist so why do I need Developer Relations? Very good question! In fact, the answer is that very few companies *do* need developer relations (I told you it was niche!). The ones that do are almost always those who offer highly technical products. When this is the case, the barriers in between the traditional roles tend to break down:
- Marketing can't reach the right audience when they are demanding highly technical content and actively avoid the usual sales or marketing channels.
- Product Managers struggle to understand new industry trends without being experts in the domain
- The Engineering team are busy building a product and may not have time or the skill set to do everything

![image](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/n4d2zub8xa9t4donoogr.png)

Developer Relations is the department that glues everything together and solves these challenges. Experts in the product, the industry and with the relevant soft skills to do public speaking engagements and manage communities.

People often ask what a typical day looks like for me but the reality is that no two days are ever the same. I might write a code sample one day, speak at a conference the next, and then help a customer architect a solution the day after. The variation is what makes the job so much fun 😀.

Hopefully I've at least given you a rough idea of what **i do**, now for the hard part; what **my company does**. 

## Seldon
![Alt Text](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/hug6qka1g8nvcdgabi9d.png)

The simplest explanation is that we're an "AI startup". It definitely makes us sound cool, but it also doesn't disentangle us from the thousands of other AI startups out there. Most AI startups focus on a specific industry and then either:
- Provide software that has machine learning built in to it
- Do machine learning for clients in the industry as consultants

[Seldon](https://seldon.io) does neither of those. In fact, if you work at one of those AI startups there's a good chance you've heard of Seldon because what we do is provide tools for people who do AI.

![image](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/040mdp8umh9cnknj691k.png)
 
Here's an analogy; imagine machine learning is pizza instead 🍕. While most companies in the pizza industry are busy making pizza, coming up with recipes and sourcing the best ingredients, we're the ones who supply the wood-fired ovens, the paddles and the pizza cutting wheels. It doesn't really matter if you're making italian-style, deep dish, sourdough or calzone, having an awesome oven lets you cook more pizza, faster and more reliably.

What does that mean in terms of machine learning? Well, the output of machine learning is what we call a model. It's the set of complex algorithms that allow you to predict or classify something. In order to actually use that model we do what's called "putting it into production" (`production` is just a term used in the software industry for stuff that's running *for real* rather than as an *experiment or prototype*).

Running models "in production" is actually *really* hard. Seldon provides tools that make it a lot easier, particularly at scale (think hundreds of thousands of bank transactions being monitored every second for fraud, for example).

So there you have it, hopefully, a relatively simple explanation of what I get up to and what my company does.

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**TL;DR** - I do lots of nerdy stuff that looks a bit like marketing, product management and software development all at once for an AI startup in London. 💻