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Where I've been in 2026, and where I think we're going as software engineers.
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<table cellPadding="0" cellSpacing="0" style="width:100%;margin:0 auto"><tbody><tr><td><p>Hey Andrea,</p>
<p>This has been a crazy year for me and <a href="https://go.drovr.sh/U6qa1sGA4f/iOPSln8Zyh">AI Hero</a>. My biggest year yet, honestly.</p>
<p>It's certainly been my most successful year in terms of open source. <a href="https://go.drovr.sh/JD53T04kqn/qK7e7MwP9Z">My personal skills repo</a> is about to cross 300,000 stars on GitHub, and the adoption doesn’t seem to be slowing. I've even been recognised in public a couple of times by people who've used my skills. Madness.</p>
<p>The rate of change in the world of AI is even more staggering, though.</p>
<p>And with all of this change and growth, it’s good to stop and ask: where are we actually heading?</p>
<p>It’s a question I’ve been chewing on as I build my next cohort, <a href="https://go.drovr.sh/cMzjErB7Pz/724NRoPpQr">Software Factories for Real Engineers</a>. More details on that below.</p>
<p>But first, here's a quick look at where I've been in 2026, and where I think we're going as software engineers.</p>
<h3>It started because of a loop</h3>
<p>The thing that kicked off the year for me was Ralph loops.</p>
<p><a href="https://go.drovr.sh/FP7E40NaUr/rho34oiv9l">Originally shared by Geoffrey Huntley</a> in the summer of 2025, the idea behind Ralph Wiggum loops was so simple. Give the agent a goal, then run the same prompt over and over, one agent after another, until it gets there.</p>
<p>In other words, a basic hill climb toward the provided destination.</p>
<p>Like most, I didn’t really take this seriously until Opus 4.5 dropped in late November of last year. Pretty much everyone agrees it was a huge turning point in what models could do, especially on their own.</p>
<p>Opus 4.5 + a simple Ralph loop was the first time I saw real potential for AFK coding agents, and by February 2026 I ran a workshop sharing what I had learned over the holidays.</p>
<p>This combination was pure catnip for me. It was the first time I saw a way to marry the programmer and systems-designer parts of my brain with these new agents.</p>
<p>I thought to myself: <em>“loops are fun, but what about other parts of programming?”</em></p>
<p>What about if statements? Switch statements? Routing between models and agents?</p>
<p>And could we combine them to orchestrate agents so they produce software of high quality?</p>
<p>I wasn’t the only one thinking about this, of course. But I couldn’t get the idea out of my head, and continued to experiment with building my own primitives based on the classic programming concepts from books like the ones I shared earlier this week.</p>
<h3>Getting agents to check their own work</h3>
<p>Also back in November 2025, Anthropic published an article called <a href="https://go.drovr.sh/43gNFhTosk/3vlGbxBbi4"><em>Effective harnesses for long-running agents</em></a>.</p>
<p>In their research, one of the most common failures was Claude marking a feature as “done” without properly testing the work.</p>
<p>Their fix was verification: give the agent the ability to see its own work and give itself feedback.</p>
<p>This feedback loop became an essential tool for me, and many other professional engineers.</p>
<p>Most recently, <a href="https://go.drovr.sh/0ElwVphZqd/F5AFkaTQdP">I interviewed Lauren Tan</a>, who also swears by verification as the central pillar of her AI coding philosophy:</p>
<blockquote><p><em>"the single most important skill that should be in your toolkit is verification"</em></p></blockquote>
<p>Her analogy is that verification is like giving your agent hands and eyes, allowing it to run the code and poke at it like a real user would. But unlike a human user, the agent can do it automatically, and consistently, without getting tired or bored.</p>
<p>Without that automatic feedback loop, many devs were burning out as they spent more time being the human verification in the loop.</p>
<p>I knew we could do better, and I kept refining my process in this direction.</p>
<h3>“They’re more like guidelines”</h3>
<p><a href="https://go.drovr.sh/3wNy8p1avV/QHsQmxpjCK">Interviewing Uncle Bob</a> was fun because like most of us, he'd started out writing “rules” for his agents. Pages of SOPs with lists of things to do and things to avoid. Examples of success and failure.</p>
<p>In his own words, Uncle Bob’s agents treated those rules, <em>"in the Pirates of the Caribbean sense. They're more like guidelines."</em></p>
<p>So he shifted to using a gauntlet of fast and cheap deterministic checks. He only let his agent continue when its code passed the checks.</p>
<p>Once again, old ideas came to the rescue. Many good ideas date back decades, but they were too hard or too slow for teams to bother adopting, let alone maintaining.</p>
<p>But for agents, they’re cheap to run <em>and</em> maintain.</p>
<p>Automated self-verification became another valuable tool for keeping the quality bar high.</p>
<h3>What changed in 2026…and what stayed the same</h3>
<p>This year, I've gone from writing some code by hand to <strong>writing no code by hand.</strong> That alone feels significant, and I know I’m not alone in that shift.</p>
<p>My own process had to change quite a bit to get there, though.</p>
<p>I went from rudimentary planning, and being a big fan of plan mode, to hating plan mode. So I built my own versions: <a href="https://go.drovr.sh/iBIBpnRvIr/JkISwAAyQM">/grill-me</a>, then <a href="https://go.drovr.sh/jKTQRYtsFW/P22U2ZKp0m">/grill-with-docs</a>, then <a href="https://go.drovr.sh/Qz6Poi0vh2/lYkZyu7ErM">/wayfinder</a>.</p>
<p>Along the way, my loops evolved from “get the work done, eventually, please” to reliable self-verification and automated checks that kept my agent’s code good enough to meet professional standards, including my own.</p>
<p><strong>But given the rate of change, I think it’s more notable what has stayed the same.</strong></p>
<p>For most of this year, I’ve been using (and improving) the same main workflow that I use every day, and have been teaching in my AI Hero cohorts and <a href="https://go.drovr.sh/eRrRvq3hYv/BDQk6esrHe">AI Coding Crash Course</a>.</p>
<p>Don’t get me wrong, I’ve made critical fixes and improvements along the way. And I’ve codified the most valuable techniques into new and improved skills for my open source skills repo.</p>
<p><strong>The core six steps of my Real Engineering Loop are still:</strong></p>
<ol>
<li>A grilling session to get aligned</li>
<li>Some kind of document, sized to the change. For me, that's a spec and then tickets</li>
<li>Agent implementation, one session per ticket</li>
<li>Code review</li>
<li>A pull request</li>
<li>Something that looks back at previous runs to improve the system. For me, that's /retro</li>
</ol>
<p>So even during this huge proliferation of tools and models, my own skills and process have remained durable and reliable.</p>
<p>That process durability and reliability brings us to today, and the best example of where I think we’re headed with AI coding and software engineering as a profession.</p>
<h3>Where we're heading</h3>
<p>A year ago, I was prompting agents turn by turn.</p>
<p>Less than a year later, I’ve shaped that same Real Engineering Loop into a <em>mostly</em> automated process that folks are calling a Software Factory.</p>
<p>Instead of babysitting my agents all day long and going home exhausted at the end of the day, I work with my agents to get clear on what I want, and my Software Factory turns tickets into real working features powered by high-quality code. In many cases, all that’s left for me is QA before deployment. (or even QA after deployment)</p>
<p>Even though the agents are doing all of the coding, I’m still in the driver’s seat.</p>
<p>I’ll be sharing a lot more about how my Software Factory works in the coming weeks, and how you can build your own. I’ll show you the ropes, and how to think about your role as a software engineer when using this process.</p>
<h3>Software Factories for Real Engineers opens Monday</h3>
<p>Want to learn and practice with me, and a cohort of fellow software engineers?</p>
<p>My next two-week cohort, <a href="https://go.drovr.sh/cMzjErB7Pz/724NRoPpQr"><strong>Software Factories for Real Engineers</strong></a>, opens for registration next Monday, with big discounts for returning students and early enrollment.</p>
<p>Check out the course description and outline linked above, with more details coming this Friday.</p>
<p>For now, mark your calendar:</p>
<ul>
<li>Doors open with 30% off: Monday Oct 26</li>
<li>Discount ends: Monday Nov 2</li>
<li>Class starts: Monday Nov 9</li>
</ul>
<p>And if you run or belong to a team of developers cobbling together your own software factories, this is a great way to build from the same shared foundation! We offer bulk discounts on team seats, and we can put together a quote for procurement.</p>
<p>Just reply to this email, or forward it to <a href="mailto:team@aihero.dev">team@aihero.dev</a>.</p>
<p>Really excited for this one, see you Friday.</p>
<p>- Matt</p>
<p>P.S. I’m curious, what's the one thing that changed how <strong>you</strong> code with AI this year?</p>
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