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Structuring a modern AI team — Denys Linkov, Wisedocs
Takeaway
Hire AI generalists matched to your bottleneck rather than dream-team researchers; most production value comes from integration and adoption, not frontier modeling.
Summary
- Denys Linkov segments companies into tech, verticalized/services, and tech-enabled; each has different failure modes and shouldn't blindly hire AI researchers first.
- Argues 90% of needed tech exists — adoption gaps (fax, checks, slow EMRs) limit value more than model capability; hiring should target your actual bottleneck.
- At Wisedocs his team hired generalists scored on three axes (model training, model serving, business acumen) deliberately mid-tier rather than top-tier-everywhere.
- Built custom MLOps, fine-tuned encoder models, ran RAG-as-a-service and 6 microservices on a small team by leaning on shadow deployments and A/B testing primitives.
ai-teamshiringmlops
Original description
You've been given an AI mandate but don't have additional headcount, what next? Re-skilling, up-skilling and team augmentation become essential to delivering on a new mandate. In this talk we'll cover strategies to structure cross functional AI teams with domain experts, software engineers and ML engineers. We'll cover key skills and milestones that each traditional role can contribute to in unique ways. ---related links--- https://www.linkedin.com/in/denyslinkov/ Timestamps 00:00:00 - Introduction to Hiring a Modern AI Team 00:01:10 - The Anatomy of an AI Team and Company Types 00:03:38 - Technology as an Enabler, Not a Limiter 00:03:56 - Do You Need to Hire an AI Researcher? 00:04:33 - Ampere's Wager: Team vs. Researchers 00:05:07 - What an AI Team Needs to Do 00:06:12 - Identifying Your Bottleneck 00:06:48 - The Evolution of a Generalist 00:07:03 - Building the First Machine Learning Team 00:07:53 - Prioritizing Skills: Model Training, Serving, and Business Acumen 00:09:16 - Building the Second AI Team with Advanced Open Source Tools 00:10:45 - Reskilling and Upskilling Existing Teams 00:10:55 - Inner and Outer Loops of Team Activities 00:11:53 - Winning with Generalists in Early AI Strategy 00:12:46 - Upskilling, Reskilling, and Hiring for the AI Wave 00:14:11 - When and Who to Hire 00:15:08 - Verifying Trends and First Principles in Hiring 00:16:00 - Asking Relevant Questions in Interviews 00:16:12 - Reconsidering Ampere's Wager and Final Lessons