The Future of Software Engineering in an AI-Native World
I recently watched an interview with Boris Cherny on Lenny’s Podcast, and I wanted to share my take on it because it put words to something I have been seeing play out in real time.
If you don’t know Boris, he is the Creator and Head of Claude Code at Anthropic. The conversation focused on AI and coding, but what really stood out to me is that it was not just about tools. It was about a fundamental shift in how software gets built.
As VP of Engineering at ConnectWise, I am right in the middle of driving hyper-automation and AI adoption across teams. This discussion did not feel theoretical. It felt like a description of what is already happening.
The Core Thesis: Coding Is Being Solved
Boris said something that stuck with me:
We are approaching a world where coding itself is “solved” by AI, and that fundamentally changes software engineering and knowledge work.
That is a bold statement, but it tracks.
We are not fully there yet, but we are clearly moving in that direction. AI is already capable of generating large portions of working code. More importantly, developers are starting to trust it enough to make it part of their default workflow.
This is not a tooling shift.
This is a paradigm shift.
What’s Happening Right Now
What makes this moment different is how fast it is happening.
This is not like previous waves of developer tooling where adoption took years. AI-assisted development is scaling rapidly because it removes friction immediately. Once engineers see that it works, they do not go back.
We are seeing:
We are moving from AI-assisted development to AI-first development.
The Printing Press Moment
Boris used an analogy that really clicked for me.
The printing press did not just make writing faster. It democratized communication.
AI is doing the same for code.
We are no longer limited by how fast someone can type or how many engineers we can hire. Code is becoming a lever, not a bottleneck.
And when that happens, the value shifts.
The Shift in Engineering Value
If AI can generate code, then writing code is no longer the highest value activity.
The value moves up the stack.
From:
To:
I am already seeing this across our teams at ConnectWise.
The engineers who are thriving are not the ones writing the most code. They are the ones who think in systems and know how to guide AI toward the right outcome.
The New Role of the Engineer
The role of the engineer is evolving into something closer to:
We are moving from builders to directors.
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Instead of writing every line, we are defining intent, reviewing outputs, iterating quickly, and ensuring quality and safety.
It is a shift from execution to amplification.
The Winning Operating Model
Beyond small teams, Boris outlined what I would call the winning operating model for this new world.
We are leaning into this at ConnectWise.
We have identified key teams that are running pilot programs to demonstrate how AI can safely accelerate development. The goal is not just speed. It is proving that this model works at scale and responsibly.
Emerging Risks
With all of this acceleration, there are real risks.
As we push forward, we are working closely with our InfoSec and Compliance teams to ensure strong validation, human oversight, and secure usage patterns.
Speed without control is not a strategy.
What Comes Next
If coding becomes easy, the next frontier is clear.
We are not just building applications anymore.
We are building systems of agents.
Strategic Implications for Leadership
If you are leading engineering teams today, here are five steps I would strongly recommend:
1. Redefine engineering productivity: Measure outcomes, cycle time, and AI-leveraged output.
2. Invest in an internal AI agent platform: Enable agent creation, tool integration, and workflow orchestration.
3. Stand up small agent teams: Focus on high-impact use cases and prove value quickly.
4. Prioritize governance early: Build validation, security, and compliance into the foundation.
5. Upskill your organization: Train teams on AI interaction, system thinking, and evaluation of outputs.
My Takeaways
If I had to simplify it:
Final Thought
We are at one of those rare moments where the ground is shifting beneath us.
This is not about coding faster.
It is about rethinking how software gets built entirely.
The leaders who recognize that early and act on it will have a massive advantage.
You can also read this article on Medium: https://medium.com/@prock13/the-future-of-software-engineering-in-an-ai-native-world-709e14696110
The shift from "engineer who writes code" to "engineer who designs systems" has been talked about for years — the difference now is that the people who don’t make that shift are visibly slower, not just theoretically slower.