3 AI cheat codes to launch and scale your medical device

I'm joined by Jelani Abdus-Salaam, Founder at Best of AI, as we explore how AI can transform medtech operations, the critical distinction between AI automation and AI agents, and practical strategies for adopting AI without massive organizational overhauls.

In this episode, we dive deep into:

AI Literacy Gap Creates Massive Medtech Opportunity → Medtech is perfectly suited for AI with rules-based QMS, defined regulatory standards, and structured clinical data—yet AI literacy remains surprisingly low → Companies that bought specialized AI solutions from domain experts succeeded 67% of the time, while internal enterprise initiatives failed at 95% → The paradox: medtech professionals excel at clinical work but lack exposure to AI, creating adoption barriers despite clear benefits

AI Agents vs AI Automation: The Game-Changing Distinction → Automations follow sequential steps while AI agents use reasoning and context to decide their own path to accomplish goals → AI agents can pull from multiple knowledge sources and adapt their approach based on the situation → Critical factor: AI is "really dumb" until you codify your processes—you must understand your business systems before deploying agents

The Chief of AI Role Is Now Essential → Every medtech company will soon need a dedicated AI officer who touches sales, marketing, and operations as the central nexus → Don't need full developers—someone who can use cursor, Claude, and orchestration tools to build and test solutions internally → Junior AI people trained by experienced practitioners can be incredibly effective when paired with enterprise-level leadership

Specialized Small Models Outperform Everything Apps → Specialized small language models working as agentic teams outperform single large models for complex tasks → Building your own small LLM specialized in one niche delivers better performance than ingesting documentation into ChatGPT → Open source models will prevail long-term for medtech—create custom models for specific processes

The Human-in-the-Loop Mandate for Healthcare → Humans must remain in the loop for quality assurance, especially in healthcare where hallucinations can be catastrophic → AGI isn't coming for 10-20 years—companies that fired hundreds expecting AI replacement had to rehire when systems failed → Build approval checkpoints where humans review and either approve or send AI agents back for refinement

Start With Custom GPTs, Not Enterprise Overhauls → Pick ChatGPT or Claude, list manual tasks you do repeatedly, and create custom GPTs that codify how you do those things → One founder automated SOP creation that took 20-30 minutes—now saves hours weekly compounding over dozens of tasks → Turn off data tracking settings if concerned about HIPAA compliance

Best Quotes:

"AI is really dumb. It's up to you, the person, the operator, the orchestrator, to understand what you want to happen for AI to follow what you want to happen."

"You will have individual departments. You will have the ability for AI agents to take information, pass that information into other teams or departments. That's already happening now."

"Even if you don't use AI in your business, you do need to know its capabilities because it can be used against you. Voice duplication is so easy. Deepfakes are getting so good. You need awareness."

"There's more and more people who understand the value of having a specialized AI person. Some people are calling this AI Chief Officer. All they do is learn AI, deploy AI, learn AI, deploy AI."

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Episode Timestamps:
0:00 - Introduction to Jelani and his journey to medtech AI
5:00 - The medtech AI adoption paradox
10:00 - AI agents vs automation distinction
20:00 - Why medtech needs Chief of AI officers
27:00 - Specialized models vs everything apps
35:00 - Prompt engineering strategies
47:00 - Agent-to-agent healthcare ethics
57:00 - Simulation departments becoming mandatory
1:07:00 - Starting with custom GPTs
1:11:00 - Building data-first company culture