Veterinary AI Brief

Join us in this episode of the Veterinary AI Brief as we explore how veterinary professionals are actively transforming their practices with AI tools. From building custom workflows to improving communication and patient care, our guests share their journeys, projects, and practical tips for adopting AI in veterinary medicine.
Main Topics:
Real-world AI applications in veterinary clinics
Building and customizing AI tools without coding expertise
Improving client communication and team workflows
Practical steps for beginners to start experimenting with AI
Future opportunities in proactive AI-driven patient management
In this episode:
How Dr. William Lane leveraged platform tools like Notebook LM and Node-based workflows to streamline clinical tasks
Dr. Carly Little's innovative communication mentorship program using AI transcripts and feedback
Dr. Sam Lewis's development of automated patient records and hospital dashboards
Insights on navigating the learning curve and building impactful tools without extensive coding
Strategies for starting small, iterating, and tackling problems unique to your practice
Timestamps:
00:00 - Introduction to the episode and guest backgrounds
00:29 - The importance of structured AI workflows in veterinary practice
00:52 - Practical AI projects: From journal searching to patient record automation
01:33 - The impact of custom dashboards and communication tools in clinics
02:11 - Platforms and tools: Notebook LM, Node workflows, Replit, Cursor, Base44
02:36 - Building AI solutions without programming skills: Learning and iteration
03:27 - Developing team-wide and client-facing AI integrations
04:43 - Practical benefits: Patient care, staff efficiency, and client satisfaction
05:42 - Transitioning from reactive to proactive AI management
06:40 - How non-technical vets can start their AI journey
07:09 - Building and customizing AI tools to fit practice needs
08:11 - Project examples: Urgent care boards, pet portals, communication scoring
09:24 - The evolving role of veterinarian as builder of tailored solutions
10:02 - Overcoming the technical learning curve and resource strategies
11:23 - The power of starting small and iterating progressively
12:56 - How AI enhances team collaboration and client transparency
14:10 - Key insights: Cost-effective, flexible, and domain-specific AI tools
16:18 - Future outlook: Proactive, real-time AI interventions in veterinary care
17:45 - Adopting a problem-centric mindset to drive meaningful AI solutions
19:00 - Practical advice for non-technical vets: Use AI as a partner, not a coder
20:18 - The importance of iteration and patience in AI projects
21:23 - Building trust and custom solutions that fit your practice
22:45 - Making AI tools accessible and scalable for veterinary teams
24:10 - The role of AI in improving hospital workflows, diagnostics, and client communication
26:04 - Final takeaways: Ask what you need, start small, and build iteratively

Unlock the future of veterinary medicine with AI-driven breakthroughs proven to enhance diagnostic accuracy, reduce workloads, and transform clinical workflows. In this episode, we explore how cutting-edge research from Lancet's MASAI trials reveals AI's game-changing potential—catching 29% more cancers without increasing false positives and slashing radiologist workloads by nearly half. But what does this look like for vets? Is there a realistic path to integrating these advances into everyday practice?Join us as we break down the implications of AI in diagnostics, from human health to animal care. We delve into how machine learning models are helping detect early metastasis, streamline report writing, and elevate clinical decision-making—all while highlighting the critical importance of vet responsibility and trust. Our conversation with Dr. Tam of Colorado State University reveals why these innovations aren't just scalable for human health—they could redefine how we approach veterinary cancer screening, imaging, and workflow automation.

The Veterinary AI Brief is back — and a lot has happened. In this episode, Robert Sanchez, Aaron Amassecar, and Dr. Adam Little unpack three seismic developments shaping the future of veterinary medicine.
First, VMX takeaways: Instinct's acquisition of ScribbleVet, what it means for the scribing landscape, and why the "bolt-on AI" approach to practice management systems may already be outdated. Aaron gives an insider's perspective from Covet on why dedicated AI copilots are pulling away from PIMS-native tools.

Then, the big one: new frontier AI models from Anthropic and OpenAI have unlocked something called agentic engineering — and it's collapsing the barrier between idea and execution. Robert shares how he built a personal AI assistant over the holiday break that handles email triage, Salesforce data entry, meeting follow-ups, and more. The implications for practice owners, veterinarians, and the entire SaaS ecosystem are massive.

Finally, the rise of OpenClaw — autonomous AI agents that work 24/7, interact with each other, and are already generating real revenue. It's weird, it's wild, and it might be the closest thing to AGI we've tasted yet.

Whether you're a practice owner wondering how AI reshapes your business model, a veterinarian curious about building your own tools, or an industry leader trying to stay ahead — this one's essential listening.

It's our holiday "step-back" episode: what actually mattered in veterinary AI in 2025—and what's most likely to hit practices hard in 2026. With special guest Jon Ayers, Robert, Adam and Aaron map the rapidly changing landscape: the breakout adoption of AI scribes, the "app explosion" happening around (not inside) PIMS platforms, and why the next year will be less about "tech toys" and more about AI as labor—tools that behave like employees and move spend from software budgets into staffing/COGS. We also get blunt about the reality in clinics: you only have so much change-management budget. So the question isn't "What's the coolest new tool?"—it's "What 1–3 changes will measurably improve throughput, capture more calls, and upgrade the pet owner experience without blowing up your workflow?" In this episode: Why many practices should not switch PIMS in 2026—and what to do instead How scribes became the fastest "new tech" adoption in vet med (and what that signals next) The PIMS platform dilemma: be the ecosystem enabler or get labeled the bottleneck The coming wave: AI receptionists, online booking, and next-gen client communications A practical way to "pick your shots" in 2026 so change doesn't stall everything The bigger stakes: pet-owner economics, access to care, and why regulation may need to evolve If you want a clear, actionable lens for evaluating the flood of tools—and choosing the moves that actually change outcomes—this is the one.

In this episode of the Veterinary AI Brief, co-hosts Robert Sanchez, Dr. Adam Little, and Aaron Massecar dive into the latest advancements in AI technology and its implications for the veterinary industry. The discussion kicks off with a focus on Google's release of Gemini 3, a groundbreaking AI model that promises to revolutionize the field with its multimodal capabilities. The hosts explore how these developments are set to transform veterinary practices, from enhancing diagnostic tools to improving client communication.
Participants
Robert Sanchez, Adam Little, Aaron Massecar
Key Takeaways:
Google's Gemini 3 is a game-changer in AI, offering state-of-the-art capabilities that surpass previous models.
The integration of AI in everyday applications like Gmail and Google Docs is set to enhance efficiency and user experience.
AI's role in veterinary medicine is expanding, with potential applications in diagnostics, client communication, and practice management.
The rapid adoption of AI tools in the veterinary industry highlights the demand for innovative solutions that improve workflow and patient care.
Chapters:
[00:00] Introduction and Welcome
[05:12] The Impact of Google's Gemini 3
[15:45] AI in Veterinary Diagnostics
[25:30] Enhancing Client Communication with AI
[35:50] The Future of AI in Veterinary Practice Management