From AI skeptic to an advocate
Автор: Resolve AI - AI for Prod
Загружено: 2025-07-30
Просмотров: 47
Featuring Angelo Marletta, Staff Software Engineer @coinbase
Key takeaways:
Implementing AI across all functions (PM, design, engineering, QA) creates broader efficiency gains than just focusing on engineering.
Legacy systems create AI barriers. Teams working on newer codebases see significantly better AI ROI than those maintaining 12-year-old legacy systems.
Leadership must actively re-engage skeptics. It's not enough to provide tools. Leaders need to help engineers overcome early negative experiences with AI.
Context window limitations are real. Large, complex codebases bump against fundamental LLM limitations, requiring sophisticated management strategies.
Individual curiosity trumps seniority. Personal learning agility and curiosity matter more than traditional experience levels for AI adoption success.
Operational burden creates AI opportunity. Super apps and complex platforms that require significant operational overhead are ideal candidates for AI-powered toil reduction.
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