2026 is the year of the clinician-builder.
This past year, I’ve immersed myself in new tools - from developing proofs-of-concept (PoC) in secure environments to shipping features alongside engineering teams at Cadence.
Below is a practical starter toolkit for tech-curious clinicians. These are accessible, no-code, freemium tools to learn by doing.
1. Vibe-Coding Platforms
My favorite, bolt.new, is an incredible canvas for translating clinical workflows, logic, and product concepts into tangible prototypes that engineers can build from.
Pro tip: If Bolt isn’t delivering what you want, ask ChatGPT to help restructure your prompt.
2. Voice Agents
I started messing around with voice late last year and have been blown away. ElevenLabs is best-in-class for prototyping clinical workflows.
Pro tip: If your voice agent struggles with prompts or RAG (knowledge base) access, ask an LLM (ChatGPT or Gemini) to help debug the setup.
3. Ambient Scribes
While 2024 was the year of the ambient revolution in health systems, over 40% of physicians still work in private practice and may not have the same accessibility to enterprise solutions. Fear not, as both OpenEvidence and Doximity have excellent freemium scribes.
Pro tip: Do not use these on live patients unless sanctioned by your administration. If live use isn’t allowed, run simulated visits with colleagues.
4. Presentation Magic
I stumbled upon Gamma earlier this year. It's essentially an AI tool that generates presentations, one-pagers, and websites from simple text prompts and draft materials. For academic clinicians needing creative juice to spice up Grand Rounds decks, this is a game-changer.
5. Agentic Assistants
ChatGPT, Gemini, Claude, Perplexity, Grok etc...each has strengths, each has weaknesses. You should try them all. Beyond general Q&A, I’ve experimented with scaling domain expertise by building GPTs. They are also incredibly useful as editorial assistants.
Pro tip: Model arbitrage is real. If you don’t like the output from one LLM, paste that draft into another platform and ask it to refine it. 🔄
6. Clinical Decision Support (CDS)
For now, OpenEvidence is is the clear leader because of the tight alignment with evidence-based-medicine practices that were hardwired into our brains. Keep in mind, none of these tools connect directly to EHR data. The clinician is still the API, bridging the insight to and from the patient record.
Key Point: Experimenting ≠ deploying in live clinical environments. Be mindful of your health system policy as it pertains to any PHI. That being said, you don't need permission to learn, prototype, test, and build in closed or simulated environments. In my opinion, clinicians who understand the capabilities and limitations of these tools before enterprise adoption will become vastly better partners in digital transformation.
Now I’m curious: What am I missing? Are you experimenting with tools that clinicians should know about? Drop them below👇
My favorite, bolt.new, is an incredible canvas for translating clinical workflows, logic, and product concepts into tangible prototypes that engineers can build from.
Pro tip: If Bolt isn’t delivering what you want, ask ChatGPT to help restructure your prompt.
2. Voice Agents
I started messing around with voice late last year and have been blown away. ElevenLabs is best-in-class for prototyping clinical workflows.
Pro tip: If your voice agent struggles with prompts or RAG (knowledge base) access, ask an LLM (ChatGPT or Gemini) to help debug the setup.
3. Ambient Scribes
While 2024 was the year of the ambient revolution in health systems, over 40% of physicians still work in private practice and may not have the same accessibility to enterprise solutions. Fear not, as both OpenEvidence and Doximity have excellent freemium scribes.
Pro tip: Do not use these on live patients unless sanctioned by your administration. If live use isn’t allowed, run simulated visits with colleagues.
4. Presentation Magic
I stumbled upon Gamma earlier this year. It's essentially an AI tool that generates presentations, one-pagers, and websites from simple text prompts and draft materials. For academic clinicians needing creative juice to spice up Grand Rounds decks, this is a game-changer.
5. Agentic Assistants
ChatGPT, Gemini, Claude, Perplexity, Grok etc...each has strengths, each has weaknesses. You should try them all. Beyond general Q&A, I’ve experimented with scaling domain expertise by building GPTs. They are also incredibly useful as editorial assistants.
Pro tip: Model arbitrage is real. If you don’t like the output from one LLM, paste that draft into another platform and ask it to refine it. 🔄
6. Clinical Decision Support (CDS)
For now, OpenEvidence is is the clear leader because of the tight alignment with evidence-based-medicine practices that were hardwired into our brains. Keep in mind, none of these tools connect directly to EHR data. The clinician is still the API, bridging the insight to and from the patient record.
Key Point: Experimenting ≠ deploying in live clinical environments. Be mindful of your health system policy as it pertains to any PHI. That being said, you don't need permission to learn, prototype, test, and build in closed or simulated environments. In my opinion, clinicians who understand the capabilities and limitations of these tools before enterprise adoption will become vastly better partners in digital transformation.
Now I’m curious: What am I missing? Are you experimenting with tools that clinicians should know about? Drop them below👇
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