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Hello everyone. My name is Justin Searls, and you can find me on Twitter under that same name. Feel free to call me either.
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This is what my face looked like in 2011, and thanks to how social media branding works, I'm now stuck with it forever.
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I work for a company called Test Double, a software agency on a mission to improve how the world writes software.
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You can learn more about us at our URL. The title of this presentation is "How to Program," and it's a rumination on the word 'workflow.'
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This two-part word—'work' referring to the structure and behavior of programs—will guide our discussion.
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I often find that we reprogram our thoughts and actions throughout our programming journeys.
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When I reflect on my experience as a computer science student, I recognize that I was taught data structures, P versus NP, big-O analysis, and cryptography.
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However, very little attention was paid to how to think or how to work effectively as a developer.
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Boot camps today often focus on practical skills like web standards and frameworks, but they still overlook critical thinking.
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We may admit the role of thought leaders in the community, but they often discuss work activities, not how to think through problems.
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As programmers, we should ask ourselves, when and how do we learn? Who teaches us how to think?
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If you're fortunate, you might stumble upon a productivity tip during your career. Usually, it's the 20-minute work and 3-minute break technique.
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However, it can feel a bit like gaining a $4 plastic pin after 10 years of hard service. It's somewhat insulting.
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Still, we all learn what programs do, but I dare say most of us were never truly taught how to program.
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Just looking at search results for 'how to program' reveals a lot of poor teaching methods.
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The traditional method involves starting from nothing and showing a finished example, leaving students to figure it out on their own.
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My experiences in computer science mirrored that of drawing a cartoon owl: starting with two circles and nothing more.
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I spent entire weekends in labs, staring at blank screens, having no idea how to write code.
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This realization led me to the conclusion that programming is largely a philosophical activity occurring in our minds.
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In recent years, we have seen evolution in computer science education, breaking down complex ideas into manageable parts.
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However, explanations rarely convey the necessary thinking to make concepts real.
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It may take years to replicate an application from a book, and I believe this is an act of imitation, not learning.
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In our profession, we are inundated with how questions, like when to create a new method.
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Simple advice we receive, such as 'messages should be three lines long,' reflects a lack of sophistication.
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For instance, when my wife was in first grade, her teacher told her that sentences should be two lines long.
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She followed this guideline without question until she was corrected years later.
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It's amusing because here we are, as adults in the programming world, with simplistic guidelines influencing our work.
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In spite of these limitations, let's say you eventually write a great program that you're proud of.
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If I were to ask you about the productive or unproductive actions that led to this success, could you answer?
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Most of us would likely struggle, which leads to rampant insecurity in our profession.
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The reality is that 99% of the work I've done as a programmer has been about transferring spreadsheets to the Internet.
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Yet, it took me a decade to feel confident as a programmer, which indicates something is wrong with how we teach.
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Despite this industry being around for 60-70 years, we still look for quick fixes.
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We think the next language or framework will make programming easier, but it seldom works out.
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When environments are chaotic and uncertain, brilliant people often thrive, while those without validation struggle.
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Imagine walking into a room full of programmers and not fitting in; it's truly a daunting experience.
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Unless we resolve our issues with teaching, programming remains a terrifying endeavor for many.
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Thus, if we want to promote diversity and inclusivity in this industry, we must address how we teach programming.
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As it stands, the industry seems disconnected from understanding how software truly works.
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Often, it analogizes software development to construction, design, or manufacturing, which is misleading.
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Instead, we ought to focus on understanding how we think and solve problems as software developers.
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So, how do we begin solving this issue? By introducing feedback loops, as programmers already use them to establish progress.
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Let’s practice reflecting on our actions in our development processes today.
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By doing so, we can improve our performance and emotional states through introspection.
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Spoiler alert: we can also think about our thinking in order to optimize our productivity.
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This concept leads us to what I call 'programmer enlightenment', but we must start from scratch.
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In team environments where emotional immaturity exists, initiating conversations about feelings can be challenging.
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Often, we resort to ineffective personality tests, like the Myers-Briggs Type Indicator, which oversimplifies human behavior.
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It assigns people into arbitrary categories, implying there are only 16 types.
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In reality, we know human complexity is far greater than this system accounts for.
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Today, I present you with the Searls-Briggs Type Indicator instead.
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Instead of asserting that there is a singular magical way to program, I'll share my personal journey.
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Let's use an example feature to explore my thoughts and emotions throughout my career.
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At Test Double, we've always been a distributed company, but we're learning that distribution doesn't imply equality.
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In a flat organization, one might expect spontaneous collaboration, but that's not always the case.
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We've experienced times where team members want to learn new technologies and have no means to connect.
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This sparked an idea for virtual coffee chats among team members to facilitate conversation and collaboration.
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It's akin to a handshake problem in mathematics, which calculates the number of potential relationships within groups.
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We discussed assigning people randomly for short 15-minute chats, with the expectation that connections would grow.
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Let's explore my approach and the first question to ask ourselves about emotional intelligence: Are you sensitive or fearless?
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I personally prefer hearing all requirements upfront, but that overwhelm can be daunting.
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Complexity often paralyzes me when staring at a blank screen, leading to doubt about my skills.
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This sensitivity affects how I approach programming projects, as I'm often nervous about the unknown.
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I focus on creating pairs, which sounds simple, but involves a decent amount of logistical effort.
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To overcome this, reflect on the problem, keeping the core idea in mind rather than getting overwhelmed.
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In my past, I embodied bottom-up programming, but I’ve transitioned to a top-down approach.
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By defining the problem at a macro level, I can keep the end goal clear, allowing for better coding decisions.
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This perspective encourages the minimization of wasted work and the inclusion of essential guard clauses.
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Being sensitive often feels like a double-edged sword; while it encourages caution, it can lead to paralysis.
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The act of rushing into coding without clarity can cause overwhelm because the details feel burdensome.
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I found myself stuck at points, unsure of what to tackle next because of the lack of decomposition in my work.
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Transitioning to discovery testing was a game changer for me, as it helped break down larger issues into manageable tasks.
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Working through top-level concerns and methods allows me to see progress toward project goals.
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Next, explore the inventive versus aesthetic side of programming choices.
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When building software, I believe it's more important to construct the right thing than simply to build well.
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I often find myself prioritizing implementation work rather than getting caught up in beauty or neatness.
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That said, I still strive for visually appealing code, being mindful of syntax and symmetry.
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Consistency across coding standards is crucial, but many find it boring digging through similar code.
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As developers, we need clarity and understanding of our craft, so we avoid stubbornness in our practices.
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This discourse highlights a fundamental truth; aiming to comprehend programming as a communication medium can yield better results.
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Take feedback on your code seriously; it can highlight your biases when writing for yourself instead of others.
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After all, our audience is other developers who will read what we've produced.
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This realization shifted my approach toward making my code more approachable and discoverable for future teams.
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Instead of the directed graph approach, I began organizing my code in a tree structure.
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By separating value objects and functionalities, I could keep my code clearer and actions predictable.
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Contrast becomes clear when we explore which methods serve specific functions and clarify interactions.
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As a minimalist, I prefer to limit clutter in my code. The clarity increases my productivity as a developer.
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In this pursuit, I considered how styles can introduce unnecessary complexity by encouraging inconsistencies.
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To maintain productivity, I decided to minimize those unnecessary decisions upfront.
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This way, I avoid falling into the rabbit hole of making arbitrary choices that lead to confusion.
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My vulnerability led to identifying how better organization can create clarity and foster collaboration.
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The last aspect is exploring the balance between economy and thoroughness in programming practice.
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Quickly shipping code can be a good strategy, yet it sometimes leads us to neglect thorough testing.
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In fact, most teams would benefit from deepening their understanding of code dependencies.
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The reality is many developers don’t fully grasp how their code interacts within larger systems.
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Encouraging separated coding styles may lead to siloed development, which hinders teamwork.
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Some developers gravitate towards the lowest common denominator, resulting in mediocre outcomes.
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As programmers, we should lean into normalizing clarity in our projects, urging collaboration and deep understanding.
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Be aware of the complexity that arrives during coding. Sharing knowledge fosters better performance across teams.
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Earlier, I mentioned the importance of pausing to reflect on our actions to enhance programming performance.
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This practice will lead to more insightful questions, which will help us invest in our personal growth.
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The true key to effective programming lies in understanding ourselves—our motivations, our feelings, and our reactions.
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As we venture into this complex field, we develop systems to help articulate new ideas and solve bigger problems.
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Programming is more than just writing code; it's about fostering understanding, collaboration, and creativity.
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Henceforth, I encourage all of you to reflect deeply on your unique approaches to programming.
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Thank you so much for your presence today. If you’re seeking a company that supports self-improvement, please check out Test Double.
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Feel free to come up and take a commemorative edition of my printed material.
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Also, we have a Test Double sticker for you if you'd like one. Your time here has been appreciated.
