Use factories to create jumbo object graphs

The entire time I’ve been using FactoryBot, several years at this point, I’ve used it one factory at a time:

company = create(:company, name: "Acme, Inc.")
alice = create(:user, name: "Alice Smith")
posts = create_list(:post, 3, user: alice)

Do you see the mistake I make all the dang time? Spoiler alert, I forgot the company relation on Alice’s user, so she is either orphaned (unfortunate) or created on an entirely unrelated company. That’s gonna make my test fail in weird ways!

Lately, I’ve been trying something different: create the whole object graph I want to test on in one fell swoop:

company = create(
  :company,
  name: "Acme, Inc",
  user: build(
    :user, 
    name: "Alice Smith",
    posts: build_list(:post, 3)
  )
)

The entire intent of the test scenario is made clear right here. And, the error I so often make is solved structurally rather than by vigilance.

Granted, that’s pretty chunky and way more lines. I feel like it’s a worthy tradeoff!

When I need to reference the models created by my jumbo object graph, I use RSpec let and ActiveRecord finders with a mind towards consistently finding the right thing:

let(:company) do
  create(...) # the whole company bit from above
end
let(:alice) { company.users.find_by(name: "Alice Smith") }
let(:posts) { alice.posts }

Failure = entropy due to adding humans

Here’s a real dinger of a sentence from Michael Lopp’s latest, The Art of Leadership: Small Things, Done Well:

Failure is created by the increasing entropy of a growing number of humans running around the building, good intentions in hand, breaking things.

Growing an organization requires rethinking trust, coordination, and collaboration. The breakpoints where things go from working pretty well to an absolute shamble come faster than we think. They don’t even occur at nice, round numbers like base–2 or base–10 orders of magnitude.

Figuring out how this works for teams, companies, social networks, and whole countries feels like one of the big unsolved problems of the knowledge/attention-era.

Writing is thinking, so write about code

Writing clarifies thinking. Therefore, writing design docs clarifies one’s thinking about code. Design Docs at Google and an example/meta design doc from the same author are great places to start!

I found that writing prose until I run out of clarity and then switching to proof-of-concept code is even better. The constraint of making an ambitious design work with a minimal change-set is a nice way to work for a day or so.

Lots of features or fixes don’t require in-depth thinking to get started. But when they do, sorting out the ideas and tradeoffs in writing helps a lot.

Write until I run out of ideas, flesh those ideas out, write about the nuances I found. It’s a nice feedback loop!

Bradford Fults on feedback and human bias

A Better Approach to 360° Feedback: Bradford Fults shares ways to route around fallible human memory and gather useful information when it comes to review season.

Humans also have a recency bias and suffer from long-term memory distortions that change to fit their current opinions of other people. This means that “observations” from months ago often aren’t so much observations as they are current opinions and emotions repackaged as fixed stories about the past. Most people don’t even intend to distort the truth like this: it’s just the way the human brain works.

Instead, ask questions in the context of how the reviewer works with the reviewed, particularly in the last 90 days or so. Paraphrasing Janet Jackson: “What Have You Done For Me Lately?”

Towards smaller JavaScript

The JavaScript ecosystem’s gone to a strange place where dense frameworks and complex tooling are the status quo. But, there are data-points suggesting the pendulum could swing back sooner than later:

  • Snowpack 2.0 – download all your deps, import them as modules. Snappy development experience ensues.
  • lit-html – generate DOM without going through React/Vue/etc. intricacies
  • Alpine.js – attach dynamic interactions to elements with data elements describing DOM manipulations
  • htmx – attach dynamic networking to elements with data elements describing AJAX/Websocket/SSE events

Caveat: I haven’t tried any of these. But, the trend-line is promising. JavaScript the language, while not perfect, is Pretty Good now. Perhaps the next few years will see the great ideas of the frameworks squeezed into more accessible, less sprawling expressions of those ideas.

The possibility of software through the ages

The gestalt of what’s new in software and how it’s changing our world has evolved over the decades.

In the ‘90s, it was “don’t make me think!”. User interfaces went from text-based systems that required memorization and expertise to graphical systems that afforded more casual use of computers. Unix users and their terminals are a notable holdout to this day.

In the ‘00s, it was “don’t make me remember!”. The internet let us to stop worrying about access to common knowledge. Search engines, news feeds, e-commerce, and listing sites made it pretty easy to answer many questions without a resident expert. Nascent social platforms made it possible for our “friends” to feed this information back to us. Notable holdouts: it was impossible for me to search for punchlines from SNL skits, and largely still is.

In the ‘10s, it was “don’t make me describe the content I want to see!”. The now-giant tech companies figured out that their products were more “engaging” if they pushed content to people instead of people clicking around and typing queries to describe what they want. Thus was born machine learning, recommendation systems, and infinite/algorithmic feed scrolling. Notable holdout: none, the blast radius of ad-tech is wide and far-reaching.

From this particular moment, it seems like the ‘20s are going to be “don’t make me leave my enclave”. Even if there’s a breakthrough in medicine and this pandemic is a temporary blip, the writing seems like it’s on the wall. Many kinds of service and retail commerce we used to go out into the world to interact with, along with offices, are going to fade away as climate changes and viruses come and go. Notable holdout: the not-so-middle class folks who do the machine’s bidding and keep the wheels of commerce rolling.


Over three decades, things are at once noticeably better and yet there’s vast room for improvement. If you’re wondering where impactful work can be done in technology, it’s in making the benefits of the technology we’re building for the middle/upper classes today available to the less fortunate tomorrow. If we can make fantastic televisions available to everyone, surely we can improve the outcomes that matter most in everyone’s lives.

If we could bend this curve, the ’20s could be the decade of “no pithy quote, just people helping their neighbors.”

The Revenge of the Intuitive and developer tools in 2020

The Revenge of the Intuitive – Brian Eno lamented the downsides of a modern, computer-based recording console. Twenty years ago! The trade-offs for “freedom” at the expense of human affordances were too much for Eno at the time.

Feels like we’re in a similar spot with developer tooling. It works for the most accomplished and persistent of us. For many people who would like to build software, it’s too much. It’s too easy for our castles of complexity to thwart the novices.

The trouble begins with a design philosophy that equates “more options” with “greater freedom.” Designers struggle endlessly with a problem that is almost nonexistent for users: “How do we pack the maximum number of options into the minimum space and price?” In my experience, the instruments and tools that endure (because they are loved by their users) have limited options

You could just as easily write this today about software development libraries and tools. Too many of them discard pretty good ideas about how to build applications. Too much fascination with meta-tooling. Not enough thought put into how to put applications in people’s hands.

With tools, we crave intimacy. This appetite for emotional resonance explains why users – when given a choice – prefer deep rapport over endless options. You can’t have a relationship with a device whose limits are unknown to you, because without limits it keeps becoming something else.

We need standalone tools and libraries to build upon. However, well-curated, opinionated developers tools are where the magic happens. Frameworks like Rails, Tailwind, Next.js are where the leverage is.

A determined expert can build an application from building blocks. Novices can at least get started with a well-crafted framework. A good community and forgiving documentation can get them through the valleys of confusion to the peaks of accomplishment.

Perhaps low/no-code tools will bring the benefit of the “golden, narrow path” to more people. Maybe the trade-winds of developer tooling will blow away from showmanship back to accessibility. Either way, we should tidy up our house and make software development more welcoming to those who aren’t already monks in the monastery.

One strong center and two senses stimulated

I rented a 12-year old Porsche Boxster via Turo this weekend. Good app, great car. I’m shopping older German convertibles for my next car. Paying a little to rent a prospective car for a day is way better than driving one for less than an hour. Plus, no sales tactics!

I swear this isn’t a headshot for a TV show set in an era where masculine pastels are Extremely The Thing.

The center of the Boxster experience, it turns out, is the tachometer and the engine. The tachometer is dead-center, set in distinctly-Porsche numerals with a digital speedometer in the bottom. You don’t want any other gauges. It’s nice to know when you’re about to run out of fuel, I suppose.

2008 Porsche Boxster speedometer and tachometer

The flat-six cylinder engine sits right behind your shoulders. It is, according to my wife, loud. I found it sonorous. I don’t have a picture of it because you literally can’t see it without taking the car apart. And, a picture of a dirty machine with 130,000 miles isn’t right. The engine on a Porsche is meant, and designed, to be heard.

Once I was between that tachometer and engine, I knew I was definitely in a Porsche Bubble. The switches, seats, even entertainment system didn’t matter much. It helped that it was a lovely day and the air conditioner was up to the challenge. But it’s all auxiliary to the sights and sounds.

Turns out, that’s sort of all you need. A strong design center and two senses stimulated can make a product that stands the test of a decade or three.

Manage for time and mental burden

Features in software are answers to questions. How can customers send what they’re looking at to someone else? That’s share via email. How can customers distill all the data about my project’s tasks down to raw data to analyze it? That’s a report, probably with a CSV export.

All of these answers exist on some kind of spectrum. There are simplistic and sophisticated answers. Maybe reporting has no interaction affordances at all; it’s an HTML table and a link to download it as a CSV. Perhaps reporting is full of interactions, using metaphors of spreadsheets like sorting or filtering.

It hurts to waste time and effort. We get attached to the things we work on. But that’s the Sunk Cost Fallacy talking. If you don’t think a feature is worth the time it takes to make it great, then it is not rational to ship a crappier version simply because you have sunk time into it.

Julie Zhou, How to Make Things High-Quality

Early in the development of a feature is the time to seriously consider whether to ship the simplistic or sophisticated version of the feature. Before Sunk Cost starts to weigh on our souls. The first few days of building the feature are often about figuring out how much sophistication we can afford to build given the amount of time we have to ship the feature.

It is tempting to stop when it works, but it is only the beginning. That’s the shitty first draft you’d never turn in. Now you must go through the process to make it as simple as possible for others to understand.

Simon Hørup Eskildsen, Shitty First Software Drafts

In a sense, we’re matching a time budget to a mental complexity budget. In one week, we could figure out how to do a very simplistic CSV export. We could get it to work, make the implementation clear, test it out, iterate on code review, and have it ready to ship. In four weeks, we could add all the features that make a crisp and clear customer feature: generating it in the background, emailing a link to download the CSV after its generated, showing progress of the export to a user, etc.

With the teams I work with, we operate with the idea of peak complexity: the time at which a project reaches its highest complexity. Peak complexity has proved a useful mental model to us for reasoning about complexity. It helps inform decisions about when to step back and refactor, how many people should be working on the project at a given point in time, and how we should structure the project.

Simon Hørup Eskildsen, Peak Complexity

Somewhere in the middle of the time allotted to the project, a feature might start to feel like its getting out of hand. Inevitably, there’s some surprise complexity or scope that no one anticipated. If the code of the feature were a combustion engine, it is sitting on a stand, partially disassembled, and in need of a rebuilt component.

Maybe we decide that the surprise scope isn’t worth the toil and scrap part of the feature. We might decide it is essential and scrap some other part of the feature so we can finish this while affording the time and complexity budget.

Eventually you reach a point where there aren’t any more unsolved problems. That’s like standing at the top of the hill. You can see clearly all the way down the other side. Then the downhill phase is just about execution.

Basecamp Hill Charts

We reach that Peak Complexity, decide how to get through it, and start working downhill. We’re now reaping the benefits of the thought and effort we put into managing the complexity budget of the feature, given the our time budget. We’re crossing t’s and dotting i’s, finishing detail work, and getting the project ready to ship.

I find that managing software projects as time plus complexity works far better than viewing it as tasks for people to work on until it’s “done”.