AI coding tools are not just changing how software gets written. They are changing how teams work, how engineers are evaluated, and where bottlenecks show up.

Scott Breitenother, CEO and cofounder of Kilo, joins The Tech Trek to talk about what engineering looks like when developers are managing multiple agents, work continues overnight, and the real constraint is no longer typing code, but judgment, ownership, and process design.

Scott shares how Kilo uses Kilo to build its own product, why AI only creates speed when companies rethink their workflows, and how teams can build trust in agent generated code without creating a new layer of busywork.

Practical Takeaways

• AI does not automatically make teams faster. If approvals, meetings, and handoffs stay the same, the bottlenecks simply move.

• Engineers using coding agents still own the outcome. AI can assist with the work, but accountability for quality does not disappear.

• The strongest teams will find a middle ground between blindly accepting AI output and reviewing every line as if nothing changed.

• Agentic engineering may feel novel now, but Scott believes it will eventually just be called engineering.

• Always on agents are already useful for monitoring, triage, and preparing recommended fixes, even if full autonomy is still selective.

Episode Highlights

00:38 Scott explains what Kilo is building across AI coding, open source infrastructure, and always on agents.

01:16 How Kilo uses its own tools internally, and why developers are shifting from working with one agent to managing many at once.

05:34 Why companies often fail to see AI speed gains when they layer new tools onto old processes.

08:51 The trust curve with coding agents, from early experimentation to accountability, review, and better judgment.

12:39 Why Scott sees agentic coding as a transition phase, not a permanent category.

15:32 Two habits he thinks matter most right now, staying curious and trying a wide range of models and tools.

18:03 What always on agents can already do today, and how that could expand over the next year.

One Line That Stuck

“Bringing in AI does not remove accountability from whoever creates the PR.”

Pro Tips

• Start small with AI assisted workflows, then expand into single agents, multiple agents, and automated review as trust grows.

• Match review depth to risk. A mission critical system deserves more scrutiny than a simple cosmetic change.

• Use automated review to guide human reviewers toward the areas that deserve the most attention.

• Keep experimenting. A tool that fails on Monday may be materially better by Wednesday.

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