I spent a long time mastering software program structure, solely to find that 70% of my hard-won experience may now be delivered by AI in seconds. This could have terrified me. As an alternative, it set me free.
Let me again up. I began my profession as a software program engineer and shortly progressed by the ranks to architect. Across the begin of this century, Microsoft launched their Microsoft Licensed Architects program—an unique certification requiring peer assessment of real-world structure case research. I flew to Singapore for my board assessment and have become one in every of solely 40 architects worldwide to earn that certification earlier than Microsoft sundown this system on account of prices. I co-authored a ebook on Skilled UML with Visio, again when UML was the graphical normal for designing structure.
I’m telling you this to not wave credentials, however to determine one thing necessary: I lived and breathed structure for years. And thru all that have, I found one thing basic.
READ PART 1: Why your AI coding agent wants greater than a plan: Classes from the trenches
The 30/70 Rule
A minimum of 30% of structure work is the artwork of asking the proper questions. This got here naturally to me—perhaps it was mental curiosity, perhaps simply widespread sense. However I watched gifted engineers fail as a result of they by no means requested these crucial questions. You ask them of shoppers. You ask them of your self. You ask them of skilled engineers. By means of these questions, you arrive on the proper architectural selections.
However right here’s the factor: widespread sense isn’t at all times that widespread.
The opposite 70%? That required immense trade expertise and information. Always studying. Studying from your personal errors—or higher but, another person’s. Should you’re sitting excessive sufficient in an enormous firm like Google, you get uncovered to inner errors and successes by quite a lot of totally different groups. However mainly, you’re continuously sucking in an amazing quantity of knowledge so you could have that contextual consciousness.
This data was my aggressive benefit. However not like advantageous wine, technical information has an expiration date.
The Decay Downside
As I moved from pure structure into constructing companies—creating category-defining corporations like Wrike (which helped create collaborative work administration alongside Asana and Monday) and now Zencoder (constructing AI brokers that automate your complete software program growth lifecycle)—I drifted farther from day-to-day technical selections. Applied sciences advanced. Patterns shifted. Greatest practices remodeled.
My bottled-up information was turning to vinegar.
Lately, I wanted to dive deep into some laborious architectural selections. What occurred subsequent modified every thing I believed about experience.
The AI Multiplier Impact
My thoughts was blown by what I may accomplish with AI help. That 70% of trade information I’d spent years accumulating? AI may ship it immediately, precisely, and comprehensively.
Right here’s my new course of: When going through an architectural query, I instantly fireplace up a minimum of three AI queries. If the query requires analyzing an current codebase that I’m not conversant in, I open it in Zencoder and fireplace a bunch of parallel queries to the agent. In parallel, I ask GPT5 or Opus for the trade greatest practices perspective. Then, whereas it’s working, I copy-paste the trade query to “deeper” public analysis brokers – GPT-5 Professional and Analysis Mode in Claude Opus. By the point I launch my final question, the primary one already has a response for me, and it’s time to dive into the rabbit gap.
It’s like being a detective with a crew of tireless investigators. The preliminary response offers me threads to comply with. Like all good detective, I pull on these threads—they result in extra threads. It’s a back-and-forth course of, diving deeper into promising instructions. By the point the analysis brokers return with their full write-ups, I’ve already shaped preliminary opinions that I can validate or revise towards their complete analyses.
What occurs then is I can act as an actual architect once more, even after years away from each day observe. My prior knowledge and battle scars mix with AI’s up-to-date information to create one thing neither may obtain alone.
The New Structure Equation
The equation has basically modified:
- Earlier than: 30% asking proper questions + 70% collected information = Good structure
- Now: 30% asking proper questions + AI-delivered information + Human judgment = Distinctive structure
This isn’t about AI changing architects. It’s about AI finishing us. The architects who will thrive aren’t these with essentially the most memorized patterns or the deepest technical information. They’re those who ask one of the best questions, who know which threads to drag, who can synthesize AI-delivered insights with human judgment and expertise.
The Paradox of Progress
Everybody fears AI will substitute architects. After constructing a number of category-defining corporations, I’ve found the other reality: AI doesn’t diminish the worth of expertise—it amplifies it.
My “expired” information isn’t nugatory. These scars, these classes discovered, that instinct about what inquiries to ask—these develop into extra precious, not much less, when paired with AI’s infinite capability for present info.
I used to be one in every of 40 Microsoft Licensed Architects on the earth. At present, I’d lose a technical information contest to any junior developer with ChatGPT. But I’m constructing higher methods now than I ever did at my peak.
That’s not a contradiction. It’s evolution.
The 30% that was at all times the artwork of structure—that’s now the place your complete recreation is gained. And for those who’ve spent years honing that artwork, when you have the scars and knowledge from real-world methods, then AI isn’t your alternative.
It’s your superpower.
