What happens when AI stops being a tool engineers use and starts becoming a member of the development team? In this episode of Ship Happens, host Per Krogslund sits down with Scott Gale, CTO and co-founder of Fluency, to explore the rise of agentic engineering and how AI is changing the way software gets built, tested, deployed, and maintained.
In this episode of Ship Happens, host Per Krogslund sits down with Scott Gale, CTO and co-founder of Fluency, to explore the rise of agentic engineering and how AI is changing the way software gets built, tested, deployed, and maintained.
Fluency has spent years automating digital advertising across platforms including Google, Meta, Amazon, TikTok, and DSPs. Now, the company is bringing AI agents into that workflow—using them to advise customers, enforce compliance, surface optimization opportunities, and help engineers tackle software development itself.
Scott walks Per through what that looks like in practice. At Fluency, engineers can use agents to triage bugs, investigate problems, propose fixes, and open pull requests. But the agents don't get the final say. Humans review changes before they make it into production.
That human layer becomes especially important when you're operating systems responsible for roughly $3 billion in annual ad spend. Scott explains why agentic engineering requires more than powerful models: it requires strong DevOps foundations, clear guardrails, reliable processes, and a thoughtful approach to what should—and shouldn't—be automated.
The conversation also tackles the bigger questions facing engineering teams: If AI can write more of the code, what should engineers spend their time doing? When should you build versus buy? And as AI makes coding easier, does the real engineering challenge shift toward judgment, architecture, and directing intelligent systems?
AI may be joining the dev team. The question is what the rest of the team does differently because it's there.
00:00 — When AI Code Fails
01:03 — Meet Fluency CTO Scott Gale
02:30 — Fluency Origins
06:06 — From Templates to Agents
07:42 — Human Control vs. Autopilot
10:00 — Automation vs. Persuasion
11:27 — Engineers Managing Agents
17:33 — Guardrails and DevOps Layers
28:00 — Build, Buy, Standardize
32:11 — What Gets Expensive Now
33:29 — Should You Still Code?
35:24 — Closing Thanks
AI is becoming part of the team.
Agentic engineering moves beyond using AI as a coding assistant. Agents can increasingly investigate problems, make recommendations, and carry out pieces of the development workflow.
The engineer's role is changing.
As agents take on more implementation work, engineers can spend more time directing systems, defining requirements, reviewing output, and making higher-level technical decisions.
Human oversight still matters.
Fluency's workflow keeps humans involved in reviewing agent-generated changes before they reach production—a critical distinction between agentic development and simply handing over control.
Production demands guardrails.
The more consequential the system, the more important reliability, testing, observability, permissions, and DevOps practices become.
Determinism still has a place.
Not every problem needs an autonomous agent. Predictable, deterministic systems remain valuable when consistency, compliance, and reliability matter.
Coding isn't disappearing—it may be moving up the stack.
The ability to generate code quickly changes the economics of development, but it doesn't eliminate the need for engineers to understand systems, architecture, tradeoffs, and consequences.
Scott Gale is the CTO and co-founder of Fluency, an advertising technology company focused on automating and optimizing digital advertising across major platforms and channels.
Scott leads the engineering vision behind Fluency's increasingly agentic platform, bringing together deterministic automation and AI-driven systems to help advertisers manage complex workflows at scale.