Episode Details
Back to Episodes
From Token Maxing to Outcome Maxing in AI Engineering
Description
AI coding tools are helping engineers write code faster. But faster code does not automatically mean better business outcomes.
Vitaly Gordon, cofounder and CEO of Faros, joins The Tech Trek to talk about the gap between AI adoption and measurable results. The conversation looks at why engineering teams are spending more on AI, how enterprises are thinking about ROI, and why existing processes can become the bottleneck even when code generation speeds up.
Vitaly also explains why AI adoption inside large organizations looks different from simply giving engineers access to new tools. Teams still have to deal with security, legacy processes, risk, integration, and organizational change.
Key takeaways
• More AI usage does not automatically create more customer value.
• Engineering leaders need to connect AI spend to actual outcomes.
• Enterprise adoption requires process changes, not just new tools.
• AI ready engineers increasingly need both domain expertise and AI skills.
Key moments
00:36 Stop token maxing and start outcome maxing
02:51 Why FOMO accelerated AI adoption
06:32 Measuring ROI on engineering AI spend
09:19 Change management inside large engineering organizations
14:23 Why AI ready engineers are harder to hire
17:13 Will AI reduce engineering jobs?
Best Line
“Stop token maxing and start outcome maxing.”
Follow The Tech Trek for more conversations with technical leaders building and operating modern teams.