A Staff Engineer's Guide to Inventing Work

Platform teams are engineering-led rather than product-led. There is almost never a product manager handing you a roadmap, no revenue line to follow, and no market to lose. This means that work does not exist unless an engineer invents it. The continuous struggle is to find ways to increase the value our platform provides to the users of the system. A big part of a staff engineer’s job in a platform team is to figure out what the team should build next - I like to call that “inventing work”. Thankfully, the signals that help us to invent work are already out there, and they arrive from four directions - from the systems, from the users, from your organization, and from the industry. What follows is a guide to reading each of them.

Large Language Models: Code vs. Text

Every technology hype-cycle is a Dickensian tale of two extremes.

It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of light, it was the season of darkness, it was the spring of hope, it was the winter of despair. Charles Dickens, A Tale of Two Cities

Large Language Models (LLMs) are the rage now, and we can see those extremes play out in the reception of products based on LLMs. For instance, Github Copilot has been a massive success within the programming community whereas Galactica was launched and shutdown in under 3 days by Meta and faced intense criticism.

The general perception (as of early 2023) is that (auto-regressive) LLMs are better at generating code, but have had a mixed bag of results in use-cases involving generation of general text. Why is that?

Defining a Platform is Hard

Engineering platforms are a vague concept. Software organisations across the board agree on the need to ‘platformise’ layers of their stack, but struggle to define the term. The question ‘what is a platform’ is met with a response ‘something similar to AWS, but at a higher layer of the company software stack’. I have previously argued why this is a false analogy.

I think we can agree that there is a dichotomy in engineering platforms: public platforms and internal (or private) platforms. AWS S3, Snowflake, and others are examples of public platforms, while internal platforms are engineering platforms built within a software organisation to serve internal users.

My approach here is to start with a reasonable definition of platforms in general and arrive at a reasonable definition for internal platforms. This was not as straightforward as it sounds. The minimum we can gain from such an exercise is the ability to identify internal platforms in the wild (“Is X an internal platform?” ). ¹

So, what is a platform?

Ariel

Ariel: The Restored Edition by Sylvia Plath
My rating: 3 of 5 stars

Reading Sylvia Plath is an experience, turbulent is an understatement. Her poems show her wild and repressed thrashing against her circumstances and on one occasion, I was moved to an extent that I had a nightmare - I cannot remember the last time I had a nightmare - and on many other occasions to pen my own (bad) poetry. .. Read More

AWS Is NOT Your Ideal

Let me start with an assertion. Every platform engineering team ¹ in every organisation aspires to be like AWS ².

Every platform team wants to be like AWS, because like AWS, they provide infrastructure abstractions to users. AWS provides infrastructure via the abstractions of VMs and disks and write-capacity-units, while platform teams provide infrastructure using higher abstractions which solve service definitions, database or message queue provisioning, and service right-sizing ³.

This similarity prompts leaders of platform engineering teams to model their teams as agnostic providers of universal, non-leaky (within SLO bounds), self-served abstractions for their engineering organisation. Platform teams structured as such detached units struggle to define cohesive roadmaps which provide increasing value to business. But how does your platform differ from AWS?