What if writing code isn’t actually the most important part of engineering?
In this episode of Futureproof, Prakash Chandran sits down with Aleksander Hakestad, CTO and co-founder at Apart Tech, to explore what it really takes to build software in an AI-native world without losing quality, craft, or control. Aleksander explains why the best leaders stay hands-on so they can evaluate quality, why depth of expertise beats climbing the career ladder, and why communication becomes the true bottleneck in modern engineering—especially across cultures and teams. Together, they unpack a pragmatic model for AI-assisted development where agents touch everything, humans own the architecture, and teams learn fast by setting clear standards, building tight feedback loops, and committing fully to a new way of working.
Topics covered include:
00:00
Owning The Outcome In An AI World
Aleksander frames AI-assisted development as serious engineering where humans stay accountable for the end result.
02:15
Early Curiosity And The Builder’s Path
He traces his origin story from childhood computers to early projects, and the drive to build that never left.
05:45
Choosing Depth Over The Career Ladder
Aleksander shares the realization that staying hands-on mattered more than continuing upward in title and scope.
08:33
The Leader’s Job: Evaluate Quality
He argues that managing without technical proximity makes it harder to judge quality and steer good decisions.
10:39
Throwing Away The Book At Heimstaden
Why conventional best practices weren’t delivering—and what it looked like to pursue a different approach.
13:52
Communication Is The Hard Part
How misunderstanding—not coding—becomes the core challenge, and why visual systems can change team dynamics.
16:18
Strategic Execution Requires Commitment
Aleksander explains why transformations fail when leaders go halfway, and how to deal with detractors.
20:24
Agentic Workflows From Issue To PR
A walkthrough of a pipeline that turns GitHub issues into PRs with multiple improvement rounds.
26:54
Hiring For Leverage And Worrying About The On-Ramp
Why small, high-leverage teams work—and what this shift could mean for junior engineers.
29:53
A Practical Model For AI-Assisted Development
Where agents help across the stack, and where humans must retain control over architecture and standards.
34:49
Visual Verification And Faster Understanding
Why seeing what’s happening matters for verification, communication, and excitement in the work.
37:49
Advice For Leaders And New Developers
How to start small, set quality early, stay curious, and build real depth through exploration and passion.