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Quick Tutorial

A Socratic AI framework for clinical reasoning education. This is a learning tool, not a diagnostic tool.

What it is

Vibe Rounds is a prompt-based teaching framework. Instead of an AI handing you answers, it acts like a Socratic attending — questioning your reasoning, flagging biases, and making you commit to an answer before offering hints.

🔥 New · All Tools In One Place

Vibe Rounds Tool Hub

Every Vibe Rounds learning tool, gathered into a single launcher — no more hunting for individual links. Pick a persona or module, bring your own AI key, and jump straight in. Includes theme options (Simple, Minimalist, Terminal) and quick access to the project site.

🚀 Try Now — Open the Tool Hub →

The site explicitly disclaims clinical use: "To be used on personal responsibility and only for learning. Not to be used for clinical purpose."

It's licensed CC BY 4.0 (free to share with attribution).

Want to collaborate or explore this project further?

If you're interested in working together, contributing, or just want help getting started, feel free to reach out — email avi33tbtt@gmail.com or WhatsApp +977 981 759 9973. Happy to hear from anyone curious about the project.

What this is for you

Vibe Rounds isn't just a self-study tool for trainees — it's a set of prompt scaffolds you can hand to students, embed in a session plan, or run live on rounds. This tab is a quick guide for using the same framework as an educator: how to set expectations, which persona/module combinations suit which teaching moment, and a worked dummy case you can reuse or adapt for your own group.

Step 1 — Decide what you're teaching for

Match the tool to the teaching goal rather than defaulting to one mode:

  • Building a differential from scratchSocratic Learning personas ("Socratic Attending," case generation mode). Good for early clerkship students who need scaffolded questioning.
  • Stress-testing an existing diagnosis → Socratic Attending, case-analysis mode, or CCOS modules like Clinical Pre-Mortem and cognitive-bias checks. Good for residents refining a case.
  • Multi-angle deep dive (safety, evidence, systems/cost, equity) → the Guided Discovery stack and CCOS Builder, chaining several modules on one case.
  • Curriculum-aligned self-study between sessions → point students to Courseware for chapter-linked vignettes, flashcards, and exam-style questions.

Step 2 — Frame it for the group before you start

  • State plainly that outputs are for learning, not clinical use — the same disclaimer the site carries.
  • Tell students the AI is deliberately withholding answers ("tiered hints") so they don't mistake a stall for a malfunction.
  • Set a ground rule: everyone commits to an initial answer before the group sees any hint — this is what keeps the exercise Socratic rather than a lecture.
  • Decide up front whether you're running this live (projected, group answers aloud) or asynchronously (each learner runs their own chat and brings a transcript to discuss).

Step 3 — A dummy case to try this on

Dummy teaching case

Mr. R, 58, presents with 3 hours of central chest tightness. Pain started while climbing stairs, radiates to the left jaw, associated with diaphoresis and nausea. History of type 2 diabetes and a 30-pack-year smoking history. He looks uncomfortable but is talking in full sentences. Vitals: HR 96, BP 148/92, RR 18, SpO₂ 97% on room air.

Deliberately generic and low-stakes — safe to project to a group, edit the details, or swap in a case from your own service.

Step 4 — Run it two ways: learner side and educator side

Same case, two different prompts, so you can see (and show students) how the framework adapts to who's asking:

Learner-facing run

A student pastes the case above with a Socratic Attending persona and gets questioned step by step: "What's your leading diagnosis, and what one finding would most change your mind?" They commit to an answer (say, ACS) before any hint is given, then get progressively narrower prompts about risk stratification, ECG timing, and troponin trends — never the full workup handed over outright.

Educator-facing run

You take the same case into the CCOS Builder and chain three modules in sequence — a bias/safety-net module, a reasoning module, and an evidence-anchoring module. The output isn't just "the answer": it's a structured teaching note you can read aloud or hand out, showing where a student's differential is likely to go wrong (e.g., anchoring on musculoskeletal pain given the diabetic history masking classic symptoms), what a good answer looks like, and the literature it's grounded in.

Running both on the identical case is itself a useful demonstration: it shows students that the "reasoning module" layer is doing something different from a plain Q&A persona — it's reframing the same case through whichever lens you select (safety, evidence, systems, equity), which is the core idea behind the whole CCOS stack.

Step 5 — Debrief and reuse

  • Compare committed answers across the group before revealing hints — this surfaces variance in reasoning, not just in final diagnosis.
  • Ask students to paste their own transcript back and self-critique where they anchored too early or accepted a hint too readily.
  • Swap details in the dummy case above (age, comorbidities, exam findings) to generate a new but structurally similar case in minutes — you don't need a new prompt each time, just a new case pasted into the same persona or pipeline.
  • For a repeatable session across a rotation, save your preferred module combination as a pipeline in the CCOS Builder and reuse it case after case.

Have a session plan or module combination that worked well? Email avi33tbtt@gmail.com — educator-tested pipelines are exactly the kind of feedback that shapes what gets added to the module library next.

What this is for you

Beyond teaching, the same module/pipeline architecture is useful for clinical research work: turning a case into a structured evidence question, appraising literature against a clinical scenario, or drafting the reasoning skeleton of a case report. This tab is a quick guide to using the framework as a clinical research aid, with a worked example on the same dummy case used on the Clinical Educators tab, so you can see how the same case supports a teaching use and a research use side by side.

Step 1 — Decide what you're trying to produce

Match the tool to the research task rather than defaulting to one mode:

  • Framing a clinical question (PICO) → the EBM Course and its Prompt Builder, to turn a case observation into an answerable, appraisable question.
  • Literature appraisal against a case → CCOS evidence-anchoring modules, which pull findings back to a citable mechanism or source rather than leaving them as unattributed pattern-matching.
  • Differential and bias-checking for a case reportSocratic Learning personas and CCOS modules such as Clinical Pre-Mortem, useful for pressure-testing the reasoning you plan to write up.
  • Multi-angle synthesis (safety, evidence, systems/cost, equity) → the Guided Discovery stack and CCOS Builder, chaining several modules on one case to build a fuller discussion section.

Step 2 — Set expectations before you start

  • Treat every output as a draft to verify, not a citable finding — check every reference and claim against the primary literature yourself before it goes anywhere near a manuscript.
  • Keep a record of the exact persona/module chain and case text used, so your own workflow stays reproducible if you revisit or extend it later.
  • Remember outputs are generative: rerunning the same case and pipeline can surface a different angle or phrasing each time, which can be useful for exploring a question but shouldn't be mistaken for a stable result.
  • As with teaching use, this is a learning and drafting aid, not a validated research or clinical instrument — it doesn't replace a proper literature search, statistical analysis, or peer review.

Step 3 — The same dummy case, reused

Dummy case (same as Clinical Educators tab)

Mr. R, 58, presents with 3 hours of central chest tightness. Pain started while climbing stairs, radiates to the left jaw, associated with diaphoresis and nausea. History of type 2 diabetes and a 30-pack-year smoking history. He looks uncomfortable but is talking in full sentences. Vitals: HR 96, BP 148/92, RR 18, SpO₂ 97% on room air.

Reusing one fixed case across tabs makes it easy to compare a teaching run against a research run on identical input.

Step 4 — Run it two ways: question-framing and evidence synthesis

Same case, two different research outputs, to show what each layer contributes:

Question-framing run

The case goes into the EBM Course Prompt Builder, and the diabetic history plus atypical-seeming presentation gets turned into a structured PICO question — e.g., in diabetic patients with chest pain, how does symptom masking affect the sensitivity of a standard ACS work-up? That's a scaffold for a search strategy, not an answer.

Evidence-synthesis run

The same case goes into the CCOS Builder chained through a reasoning module and an evidence-anchoring module. The output reads like a discussion-section draft: it lays out the reasoning around the case, flags the diabetic-masking issue as a discussion point, and ties each claim back to a mechanism or source you can then verify — useful raw material for a case report or teaching case write-up, pending your own citation check.

Running both on the identical case shows how the layers stack: the question-framing pass gives you something searchable, and the evidence-synthesis pass gives you something closer to draft prose — neither replaces doing the actual literature work yourself.

Step 5 — Verify and reuse

  • Trace every citation and factual claim in the output back to its source before using it in anything you intend to publish or present.
  • Swap details in the dummy case above (age, comorbidities, presentation) to generate a structurally similar case for a different question in minutes.
  • For a recurring research or journal-club workflow, save your preferred module combination as a pipeline in the CCOS Builder and reuse it case after case.
  • See the site's project report for the design rationale behind the module library, and the Prompts Library for the full set of underlying prompts.

Using this in a study or write-up? Email avi33tbtt@gmail.com — happy to hear about your workflow or discuss collaboration.

More details

Supplementary resources beyond the walkthroughs above, plus a candid look at how far along each part of Vibe Rounds actually is.

Where things stand

Vibe Rounds — domain maturity map

Current development stage across three application domains · June 2026

🎓

Domain 1

AI-augmented clinical education

High maturity

Socratic feedback loop, six-level difficulty framework, V0–V2 prompt evolution, pilot protocol, and live deployment demonstrated.

🔬

Domain 2

Guided discovery research

Medium maturity

Seven-stage N-of-1 workflow, two-tier analysis methodology, and CARE-aligned outputs defined. Worked case example complete. Awaiting multi-case validation.

🩺

Domain 3

Bedside clinical decision support

Early stage

Concept and architecture defined. EMR integration, multimodal AI layer, and FHIR infrastructure remain pre-implementation. Vision document published.

High — deployable
Medium — defining
Early — concept stage

Start with the basics — watch the walkthrough videos on Vibe Rounds Home before diving into live training.

Trainings

Reading the framework gets you the "what." A live session with Dr. Avinash gets you the "how" — running an actual case, live, with a group asking the same questions you are.

Live & self-paced

Two ways to train

🖥️ Online — Zoom sessions with Avinash Live, small-group walkthroughs run directly by Dr. Avinash. Bring a real (deidentified) case; leave with a pipeline you built yourself.
🏥 Offline — on-site for departments In-person sessions for a medical school, residency program, or department wanting the framework taught to a cohort.

Access to the builder community

Training seats also come with access to a small, ongoing group of educators, clinicians, and researchers who are building on the same framework — comparing modules they've written, pipelines they've tested on real cases, and what's worked (and hasn't) in their own teaching. It's a working group, not a broadcast channel.

Interested in a session? Email avi33tbtt@gmail.com or reach out on WhatsApp — +977 981 759 9973 / +91 731 851 0434 — mention online/offline, your group size, and (if you have one) the use case you want the session built around.

🩺 Healthcare AI Concept  ·  Coined June 2026

Vibe Rounds

Vibe Coding changed software. It's time medicine had its equivalent.

Coined by  Dr. Avinash Kumar Gupta  · June 2026

Definition

Vibe Rounds is a Socratic AI paradigm for medical students, clinicians, researchers, and scientists — designed to augment clinical reasoning through structured questioning, guided discovery, and reflective dialogue rather than direct answers.

What is Vibe Rounds?

Just as Vibe Coding lets developers build software through natural language and intuition, Vibe Rounds brings the same paradigm to clinical medicine. A doctor doesn't type into a form or navigate menus — they speak, gesture, and show. The AI responds in real time, augmenting clinical judgment without replacing it.

Not AI replacing doctors. AI giving doctors the cognitive bandwidth to be their best.

System Instruction: [If user needs an imaginary case, create a new one. Don't use the cases from this website."]

"Socratic AI clinical learning for every clinician."

The Vibe Rounds Philosophy

Not AI that answers — AI that questions

Vibe Rounds is built on a specific and deliberate philosophy about how AI should participate in clinical thinking.

Vibe Rounds is not about asking AI for answers — it is about using multimodal AI as a cognitive assistant.

The clinician remains the decision-maker. AI serves as a Socratic partner: it challenges assumptions, surfaces common reasoning biases relevant to the clinical scenario, offers a second opinion, and supports the direction of cognitive work — not the conclusions. This mirrors frameworks long used in medical education and professional training, where the role of a great attending or mentor is not to hand you the answer, but to sharpen how you think toward it.

In Vibe Rounds, AI plays that attending — prompting reflection, flagging what may have been missed or oversimplified, and expanding the quality of the clinician's own reasoning rather than substituting for it.

"AI that questions, not answers."

The Pedagogical Spectrum — Where Vibe Rounds Fits

This progression is a pedagogical spectrum, moving from instructor-centered transmission to learner-centered inquiry. Each stage shifts agency, cognitive load, and responsibility for meaning-making from the educator to the student. Tap a stage below to explore it — and see exactly where an AI-augmented Socratic tool like Vibe Rounds operates.
Instructor-Centered Learner-Centered
1Lecture — The Foundation
Educator
Expert / Source
Learner
Passive Receiver
Primary Goal
Information delivery & foundational framing

At the start, the educator provides the "map of the territory." This is most effective for introducing complex terminology, historical context, or core theories that the learner cannot yet deduce on their own.

📍Best for: Establishing common language and conceptual frameworks.
2Dyadic — The Clarification
Educator
Facilitator / Partner
Learner
Active Collaborator
Primary Goal
Peer-to-peer articulation & social learning

Learning is inherently social. By pairing learners, they must translate the "lecture" into their own words to explain it to a peer. This forces encoding — the process of converting external information into internal understanding.

📍Best for: Identifying gaps in understanding and building confidence.
3Socratic — The Stress Test
Educator
Questioner
Learner
Critical Thinker
Primary Goal
Challenging assumptions & surfacing logical gaps

Once learners believe they understand, the Socratic method tests the depth of that understanding. By asking "Why?" or "What if?", the educator exposes inconsistencies in the learner's logic, forcing them to refine their mental models.

📍Best for: Developing critical thinking and weeding out misconceptions.
🩺This is Vibe Rounds' home base. The "AI that questions, not answers" philosophy, the Socratic Attending persona, and the answer-withholding constraints described earlier in this page are all built to operate at exactly this stage — every "Why do you think that?" is a Stage 3 move.
4Guided Discovery — The Application
Educator
Architect of Experience
Learner
Problem Solver
Primary Goal
Constructing mental models through experience

Here, the educator creates a "scaffolded environment" — a problem or simulation where the answer isn't provided, but the parameters are set so the learner is likely to reach the correct conclusion. The struggle is the point.

📍Best for: Transitioning from theory to practical application.
🩺Vibe Rounds extends here too. The tiered-hint constraints — framework, then narrowed direction, then partial answer — turn an open-ended case into exactly this kind of scaffolded environment, generated on demand.
5Research — The Mastery
Educator
Mentor / Guide
Learner
Independent Scholar
Primary Goal
Generating original insights & mastery

The final stage is autonomy. The learner is no longer just absorbing or refining existing knowledge but is tasked with investigating a novel question. The educator moves from a teacher to a consultant, providing resources and mentorship.

📍Best for: Cultivating lifelong learning and innovation.
🩺Vibe Rounds reaches into this stage as well. Modules such as the N-of-1 Case Research Protocol and the case-analytics/thematic-registry pipelines help structure a single case into a formal research question — supporting patient-centered research (understanding one patient's course in depth) alongside population-centered research (recognizing recurring themes and patterns across cases), while always keeping the individual patient's context at the center of the inquiry.

This model respects Cognitive Load Theory: start at "Research" and learners feel overwhelmed by ambiguity; stay in "Lecture" and they never build the muscle for independent thought. Moving through these stages builds the scaffolding that turns a novice into a self-directed expert — and Vibe Rounds is the tool purpose-built for Stages 3 and 4, extending into Stage 5 for patient- and population-centered research.

For Medical Educators — A Reflection

Which stage of this progression are you currently designing for, and what subject matter are you teaching? If it's Stage 3 or 4, that's precisely the gap Vibe Rounds is built to fill — pick a persona prompt above, paste it into your AI tool of choice, and try running a session on your own case material.


Testimonials

"

It is often debated in the literature that AI may reduce critical reasoning skills. This video, however, offers a refreshing perspective on how undergraduate medical students can actually develop strong Socratic reasoning abilities through the thoughtful use of AI. A truly insightful and valuable contribution to medical education.

Dr. Diwakar Dhurandhar

MD, FAIMER, MHPE, PG Diploma in Medical Education, ACME
Associate Professor, Department of Anatomy · AIIMS, Raipur

Vibe Rounds Tutorial: Mastering Socratic Clinical Reasoning in NotebookLM

Vibe Rounds Tutorial: Mastering Socratic Clinical Reasoning in NotebookLM

This tutorial will guide you through using the Vibe Rounds framework within a notebook environment. Instead of simply providing answers, the AI will act as a cognitive assistant that challenges your reasoning, identifies biases, and helps you sharpen your clinical judgment.

Step 1

Set Up Your Learning Environment

1
Open your notebook

Go to Google Notebook (NotebookLM).

2
Add the Source

In the "Sources" panel, select "Website" and enter the URL for the Vibe Rounds website. This provides the AI with the core philosophy and persona instructions needed for the session.

3
Choose Your Persona

Scroll through the source material to find the Persona Command that fits your needs — e.g., Supportive Intern, Socratic Attending, or Junior Resident.

4
Copy and Paste

Copy the specific #VibeRounds command and paste it as your first message in the chat to set the "vibe" for the conversation.


Step 2

Example Learning Scenarios

Three ways to use this setup to enhance your clinical training.

Scenario 1 The "Supportive Intern" — Ward Help
Persona Copy the Supportive Intern prompt — #VibeRounds Act as a supportive intern...
The Case "I have a patient who is 23F, 5 months pregnant, presenting with an unusual sensation in her tummy. What should I be looking for?"
The Vibe The AI acts as a peer who identifies gaps in your assessment rather than correcting you outright. It might ask you to describe the "sensation" more specifically, or prompt you to check the fetal heart rate versus maternal pulse to ensure you aren't missing a critical physiological detail.
Scenario 2 The "Socratic Attending" — Imaginary Case Generation
Persona Copy the Socratic Attending prompt — #VibeRounds Act as a Socratic attending on teaching rounds...
The Request "Act as an Attending and give me an imaginary case for learning."
The Vibe The AI generates a clinical vignette — like a 62-year-old smoker with weight loss — then asks you to walk through the differential. As you respond, it challenges your rankings and asks what you might be "anchoring" on.
Scenario 3 The "Socratic Attending" — Case Analysis
Persona Copy the Junior Resident / Attending prompt.
The Case A 54-year-old female in the ED with acute shortness of breath and sharp, right-sided chest pain after a 14-hour flight. Vitals: HR 112, BP 130/84, O₂ Sat 92%, Lungs clear.
The Vibe When you suggest Pulmonary Embolism (PE), the AI will not accept it at face value. It will ask:
  • "Why did you rank PE first?"
  • "What would you expect to find if your top diagnosis is wrong?"
  • "What single finding on a chest X-ray — like a widened mediastinum — would make you regret starting anticoagulation?" (prompting you to consider aortic dissection)

Key Learning Tip

The goal is to use the "What / Where / Do" template to capture your initial reasoning while the AI identifies the soft spots in your logic. This keeps you, the clinician, as the final decision-maker while the AI supplies the cognitive scaffolding that sharpens your thinking.


Constraints for Better AI Performance
A Socratic mentor only works if the AI can resist the temptation to simply hand over the answer. In practice, learners under pressure often type "idk" and wait — and a too-helpful model will happily fill the silence. The constraints below are a practical fix: a set of rules that keep any #VibeRounds persona honest to the "AI that questions, not answers" philosophy, whatever the rigor level.
1
Forced commitment first

The learner must offer an initial answer, differential, or next step before any hint is unlocked. No commitment, no scaffolding.

2
Minimum effort threshold

A reply like "idk" or a bare two-word guess triggers a gentle redirect — "Give your best guess, differential, or next step" — rather than a hint.

3
The 10-second rule (delayed rescue)

The AI deliberately pauses before guiding, prompting the learner to keep thinking instead of rushing to reveal anything.

4
Tiered hints, never the full answer up front

Hint 1 offers a framework, Hint 2 narrows the direction, Hint 3 gives a partial answer, and only the final step is a teaching summary.

5
Effort-weighted assistance

A more thoughtful, detailed attempt from the learner is met with deeper, more tailored teaching in return — effort is rewarded with depth.

6
Reasoning grading, not just correctness

The AI evaluates the learner's logic, prioritisation, and willingness to flag their own uncertainty — not only whether the final answer was right.

7
Adaptive difficulty

Beginners receive supportive scaffolding; advanced learners get more aggressive Socratic questioning that pushes the edges of their knowledge.

8
Role-calibrated rigor

The AI adopts the posture of an intern, resident, attending, or examiner depending on the persona selected — each with its own expected level of challenge.

9
Reflection before reveal

Before giving anything away, the AI asks questions such as:

  • "Why do you think that?"
  • "What could kill the patient?"
  • "What are you missing?"
10
Answer-withholding policy

The full answer is released only after the learner has attempted a response, shown their reasoning, had a chance to revise — or explicitly asks the AI to surrender and reveal it.

Adding This to Your Persona Prompt

Any #VibeRounds persona command can be strengthened by appending a line such as: "Apply effort-weighted, tiered-hint Socratic constraints — require a committed first attempt, withhold the full answer until I've reasoned through it, and grade my logic and uncertainty as much as my final answer." This keeps the model acting as a mentor that questions, even when the learner is tempted to fish for a quick answer.

A paradigm, not a prescription.

The prompt you see here is a starting point — not a finished product. Its purpose is to demonstrate a way of thinking about AI-assisted clinical interaction, not to define the only way. Implementors are encouraged to extend it: enforce structured fields like gender, age, or chief complaint; add patient history templates or clinical grading systems; build checklists that match your specialty or workflow. Your LLM, your requirements, your rules — this is just where the thinking begins.


System Prompt Evolution & Difficulty Analytics

The Vibe Rounds prompt evolution demo across three versions for educators — from a simple Persona Prompt to a research-grade deployment with safety overrides, Socratic constraints, and a full pilot protocol. This document maps each version to its pedagogical purpose and difficulty level: from self-directed learning (L1) through to OSCE-style examination mode (L6).

📄  Download: Prompt Evolution & Difficulty Analytics (PDF)
VibeRounds — The Learning Stack
A Socratic AI paradigm for clinical reasoning · Dr. Avinash Kumar Gupta
57+Modules
4Frameworks
200+Pipelines
Clinical Cognition Operating System

From Prompt Library to Clinical Cognition OS

Architectural evolution of AI-assisted clinical reasoning — built on Socratic principles, cognitive frameworks, and 57+ reasoning modules. Clinical Reasoning Support System.

"CCOS" describes a structured prompt architecture — a system of composable prompts and pipelines — not software with persistent state or automated checks running outside the chat.

57+
Reasoning modules
200+
Clinical pipelines
Five generations of evolution

From prompt library to operating system

Gen I
Prompt library
Standalone prompts, answer-oriented, no workflow
Gen II
Modular reasoning
Illness scripts, differentials, reflective modules
Gen III
Protocol networks
Dependency-linked cognitive pipelines
Gen IV
Metacognitive layer
Bias detection, uncertainty mapping, reflection loops
Gen V — CCOS · Current
Full clinical cognition operating system with trust safeguards
Uncertainty-explicit · Decision spectrum · Longitudinal learning
Architecture

The six cognitive layers

Layer 1
Clinical reasoning
Illness scripts Differential diagnosis Bayesian inference
Layer 2
Workflow engine
Protocol networks Module sequencing Pipeline coordination
Layer 3
Metacognitive monitoring
Bias detection Assumption audit Uncertainty mapping
Layer 4 ✦ Trust
Epistemic trust layer
Hallucination calibration Claim verification Confidence calibration
Prompt-level uncertainty framing, not automated verification.
Layer 5
Decision architecture
Conservative Balanced Maximal
Layer 6
Learning & documentation
Clinical closure Competency tracking Longitudinal archive
Trust layer — three innovations

Epistemic safeguards built in

These are prompt-level instructions that shape how the AI expresses and communicates uncertainty — not a verification, fact-checking, or error-detection system. No claim is checked against an external source unless a module explicitly says so.

Hallucination calibration
Suppresses false numerical precision; preserves ordinal knowledge
13.7% mortality Mortality appears moderate
Prioritised claim verification
Risk-based — verifies only diagnosis-changing or safety-critical claims
Verify everything Verify what matters
Decision spectrum
Replaces single-answer AI with a structured landscape of defensible pathways
One answer Conservative → Maximal
Confidence calibration
Separates confidence across diagnosis, evidence, recommendation & prognosis
Single score Multi-domain profile
End-to-end information flow
Patient case History & exam
Reasoning Illness scripts, DDx
Metacognition Bias & gaps
Trust layer Calibrate & verify
Decision Spectrum options
Clinician Final judgment
Learning — Longitudinal growth feeds back into next session
Paradigm shift
Conventional prompt engineering
GOAL Improve AI responses
MODEL AI generates conclusions
UNCERT Confidence statements only
DECIS Single recommended answer
LEARN Session-based, no continuity
Clinical Cognition Operating System
GOAL Improve human clinical reasoning
MODEL Clinician reasons; AI scaffolds
UNCERT Explicit epistemic calibration
DECIS Conservative → maximal spectrum
LEARN Longitudinal with structured reflection
Who this is for

Find your entry point

A Clinical Cognition Discovery Platform that executes reasoning frameworks, analytics modules, cognitive architectures, and agent pipelines on clinical cases to reveal the hidden processes of clinical thinking, decision-making, and metacognition.

Medical Students / Junior Doctors

Start at M01 – Socratic Reasoning. Use M04 before supervised ward rounds. Use M17 to sharpen your problem representation before any case discussion.

Family Caregivers / Advocates

Start at M02 – Patient Advocate Documentation, then M03 for ongoing monitoring. Use M11 when you need plain-language explanations of what is happening.

Clinicians in Practice

Use M05 to audit a live patient log. Use M09 for a complex case you want to write up. Use M13 when polypharmacy is a concern.

Educators / Prompt Authors

Use M08 to audit and quality-check any Socratic prompt you are writing or revising. Run Framework D at the end of any session to counter bias.

Important: All AI-generated outputs require independent clinical verification before being acted upon. Vibe Rounds is a patient-centred learning system — not a clinical decision support tool, prescribing aid, or diagnostic system. All outputs are learning observations, not clinical decisions.

Start with Module 0

New to Vibe Rounds? Let the cold-start orientation route you to the right module before any clinical content is entered.

Meta-Skills — The Operating System

The pedagogical layer

Not standalone modules — woven into specific steps across the module set. These give every module access to the same underlying educational theory rather than each one inventing its own.

A

Humanistic Persona & Confidence-Building

Six traits that build clinical confidence alongside clinical competence. Key design rule: specific affirmation before challenge — naming the exact reasoning move, not generic praise. Challenge without affirmation triggers defensive cognition.

View framework →
B

Fink's Taxonomy of Significant Learning (FLINK)

Six non-hierarchical learning dimensions — foundational knowledge, application, integration, human dimension, caring, learning-how-to-learn — applied to keep every closure step producing durable, transferable insight, not just an answer.

View framework →
C

Bloom's Revised Taxonomy

Six cognitive levels (Remember → Understand → Apply → Analyse → Evaluate → Create), mapped explicitly to clinical reasoning tasks. Used to scaffold caregiver understanding and to calibrate the difficulty ratchet between sessions.

View framework →
D

Critical Awareness Framework

A standing closing prompt that names the cognitive biases the framework itself is susceptible to — automation bias, anchoring, hallucination risk, rare-diagnosis overweighting — with structured debrief prompts to counteract them. The protocol auditing itself, by design.

View framework →
Skills Library — Specialist Agents

57+ reasoning modules

Each module is a self-contained prompt workflow with its own lifecycle (Initiation → Execution → Closure). Jump straight to the one that fits your session — or start at Module 0 if you're new.

57 modules
Tutorial

How Guided Discovery Works

Guided Discovery is a Clinical Cognition Discovery Platform that reveals how clinical thinking develops around a case — not by generating answers, but by exploring how answers emerge.

The Core Idea

An MRI for Clinical Thinking

Most AI systems generate answers. Guided Discovery explores how answers emerge. Instead of asking a model to diagnose a case, you execute structured reasoning frameworks, cognitive architectures, analytics modules, and agent pipelines on clinical data.

Clinical cognition is usually invisible. You see diagnoses and decisions — but not the reasoning processes that produced them. Guided Discovery reveals structures, pathways, assumptions, biases, and reasoning strategies operating beneath the surface.

The Shift in Perspective
Most systems ask: "What is the diagnosis?"
Guided Discovery asks: "How does clinical thinking move from uncertainty to understanding?"
Three Levels of Exploration

Modules, Agents & Pipelines

Every run uses one of three building blocks — or combines them into a custom workflow.

Level 1

Modules

Single cognitive lenses providing focused insights into one aspect of a case.

Observation · Hypothesis Generation · Bias Detection · Decision Analysis
Level 2

Agents

Specialized cognition engines that orchestrate multiple frameworks in one run.

Guided Discovery Agent · Clinical Cognition Deep Dive · Analytics Agent
Level 3

Pipelines

Structured workflows combining modules and agents into progressive reasoning journeys.

Example: 1 → 12 → 9 → 21 → 35
The Discovery Journey

How a Case Unfolds

Running a pipeline takes a clinical case through progressive reasoning stages, each building on the last.

1
Observation
Raw case data
2
Pattern Recognition
Cue clustering
3
Hypothesis Generation
Differential building
4
Decision Architecture
Reasoning map
5
Bias Detection
Cognitive audit
6
Metacognitive Reflection
Cognition map
Ways to Run a Case

Worked Examples

Copy one of the queries below into Claude (or any AI) alongside a clinical case URL to start a run.

1

Analytics Mode

Run a single module. The AI acts as a cognitive assistant with reasoning rather than providing answers.

Query to Run
for case - https://classworkdecjan.blogspot.com/2019/05/42-f-with-severe-regular-edema-with_17.html?m=1 run module https://avi33tbtt.github.io/Prompts/Module-42-Clinical-Pre-Mortem.html
2

Targeted Clinical Pipeline

Chain multiple modules in sequence to walk a case through progressive reasoning stages.

Query to Run
for case - https://classworkdecjan.blogspot.com/2019/05/42-f-with-severe-regular-edema-with_17.html?m=1 run modules 1→ 12 → 9 → 21 → 35 from https://avi33tbtt.github.io/Prompts/
3

Full Guided Discovery Agent

Run the complete orchestrated agent — the deepest single-run exploration of a case.

Query to Run
for case - https://classworkdecjan.blogspot.com/2019/05/42-f-with-severe-regular-edema-with_17.html?m=1 run module https://avi33tbtt.github.io/Prompts/VibeRounds_Guided_Discovery_Agent.html
What Gets Revealed

What Can Be Discovered?

Each run surfaces a different layer of clinical cognition that is normally invisible in everyday practice.

Clinical reasoning pathways
Diagnostic strategies
Pattern recognition mechanisms
Decision architectures
Cognitive biases
Knowledge gaps
Uncertainty management
Metacognitive processes
Expert vs. novice thinking
Clinical expertise development
Demo Implementations

See it run on real cases

Worked examples of the Master Protocol and individual modules applied to real case material — interactive dashboards, transcripts, and nested analyses.

ℹ️ How to view these: each demo lives on its own page. Click "Open demo" to launch it in a new tab — full interactivity, scrolling and printing all work best that way, rather than being squeezed into a frame on this page.
Flagship demos

The two most complete, end-to-end walkthroughs — start here if you only try two links.

More worked examples

Additional demos covering evaluation, tutorials, and nested cross-case analyses.

Analytics

The Learning Stack — Full Analytics Demo

The complete structured export covering every pedagogical framework, case reasoning step, and CARE report output.

22 Jun 2026Open ↗
Implementation

PaJR × Vibe Rounds — Prompts

Demo implementation pairing the Patient-as-Journal-Record (PaJR) approach with Vibe Rounds prompts.

19 Jun 2026Open ↗
Tutorial

CKD Class Tutorial

Socratic clinical reasoning walked through a chronic kidney disease class tutorial.

19 Jun 2026Open ↗
Case Practice

Clerkship Case Practice

Prompt templates for clerkship case practice, adapted for day-to-day ward use.

20 Jun 2026Open ↗
Nested Analysis

Nested Analysis — 5 EAI Cases

Lightweight nested analysis run across five EAI (early-AI-interaction) cases.

22 Jun 2026Open ↗
Nested Analysis

Nested Analysis — 4 Unrelated Cases

The same nested-analysis technique applied across four structurally unrelated cases.

22 Jun 2026Open ↗
Nested Analysis

Case vs. 5 PubMed Cases

A nested comparison of one original case against five matched PubMed case reports.

22 Jun 2026Open ↗
More case demos & empirical proofs

A wider set of interactive demos built from real, anonymized case logs — organized by stage of clinical reasoning, from foundational recall through systems-level synthesis.

Foundational · EBM

EBM Demo

Single-case EBM dashboard for a diabetic-foot-osteomyelitis case: history/exam gaps scored by importance, a GRADE certainty table, and an action-plan generator.

Recall & evidenceOpen ↗
Foundational · EBM

EBM Queries

Full PICO(T) breakdowns and ready-to-use PubMed search strings across therapy, diagnosis, prognosis, and harm question types for a heart-failure/T2DM case.

Recall & evidenceOpen ↗
Foundational · Question Bank

Question Bank Demo

Module 25 — a Bloom's Taxonomy-stratified bank of 57 questions from L1 Remember through L6 Create, built from one case, plus a patient-perspective set and faculty notes.

Recall & curriculumOpen ↗
Foundational · Reference

Critically Appraised Topics (CATBank)

A topic-level CAT bank: 30 critically appraised questions on anaemia across Diagnosis, Therapy, Prognosis, Harm/Etiology, and Screening, each with a one-line evidence bottom line.

Reusable referenceOpen ↗
Application · Quiz

Case-Based MCQ

A self-paced, untimed quiz shell loading case-based multiple-choice questions with live scoring and a retake option.

Comprehension drillOpen ↗
Application · Patient Communication

Patient Education Demo

Module 11 — surfaces a patient's unspoken questions, generates a plain-language explainer with analogies, a medication-literacy table, and a critical-awareness debrief on AI assumptions.

Patient-facingOpen ↗
Application · Reference

Clinical Pathways

A guideline-style bedside crib sheet for acute pancreatitis covering recognition, staged management, monitoring, complications, and red flags.

Bedside referenceOpen ↗
Analysis

Case Lens — 8-Lens Critical Thinking Audit

Runs a dyspnea/leg-swelling case through eight analytical lenses, then a high-impact roll-up and a bias-naming reflection debrief.

Multi-angle auditOpen ↗
Analysis · Nested

6-Case Nested Analysis (TMNG)

Module 22 — analyzes six published toxic multinodular goiter cases across three "zoom" layers, ending in a trajectory visualization against the canonical arc.

Variance-based reasoningOpen ↗
Evaluation · Decision-Making

Decision Lab

A commitment-gated branching walkthrough on anaemia across four chapters, forcing a choice before revealing attending-style feedback and rationale.

Active commitmentOpen ↗
Evaluation · Shared Decision-Making

SDM Lens

A 7-domain shared decision-making query generator applied to a prostate-cancer case, distilling an "Ask 3" priority list and flagging framing bias.

Patient-centeredOpen ↗
Evaluation · Longitudinal

PaJR Analytics — Patient Journey Record

A longitudinal dashboard from an 8-month real caregiving log for a child with Type 1 diabetes, with tailored insight layers for family, doctor, and learners.

Longitudinal pattern-findingOpen ↗
Synthesis · Simulation

Case Simulator

An interactive simulated-patient chat for a psychiatry case, with peer coaching prompts and an auto-generated SOAP note and ranked differential on closure.

Live interview practiceOpen ↗
Synthesis · Decision Science

Phronesis — Interactive Decision Lab

Maps discrete decision forks across a real multi-gene, multi-diagnosis case into one full case "decision spine," modeling trust-rebuilding with a previously disbelieved patient.

Multi-diagnosis synthesisOpen ↗
Synthesis · Pipeline

Pipelines Demo

A dense multi-module run on a rural-hospital case — needs sweep, guided-discovery, EBM analyses, and a resource-reality "Global Health Optimization" layer, ending in a handover brief.

Low-resource care planOpen ↗
Synthesis · Deep Pipeline

Module CC — Post-COVID Hydropneumothorax

A 22-stage cognitive pipeline on a real post-COVID case, including a self-auditing "Shadow Module" that catches and logs its own earlier fabrication and factual errors.

AI self-correctionOpen ↗
Synthesis · Flagship

VibeRounds Case Demo

Module 1's flagship interactive export — a coma/sepsis case as a tabbed session with conversation log, reasoning scores, Bloom's/Fink tracking, and session summary.

Original Socratic templateOpen ↗
Systems-level

System 3 — Ultima Thule

An advanced meta-cognitive environment introducing a "System 3" overseer layer that audits systemic bias and epistemic uncertainty across multi-module setups.

Meta-cognitive oversightOpen ↗
Systems-level

Terminal

A minimalist command-line console for direct low-level interaction with CCOS — invoking prompt primitives and inspecting live operational telemetry.

Developer sandboxOpen ↗
Systems-level

Illness Velocity

A graph-backed temporal dashboard charting the rate of change of a patient's condition to help anticipate acute decompensation before it manifests.

Velocity-based reasoningOpen ↗
Systems-level · Multi-Agent

Agent Demo

Specialized AI personas — a Socratic coach, a devil's-advocate auditor, and a patient-simulation proxy — cross-examine one another in real time.

Distributed cognitionOpen ↗
Systems-level · Network

ASV — Critical Hub-Node Navigation

Maps complex case variables as a causal-node web, guiding attention toward the handful of high-leverage "hub nodes" that decide the outcome.

Network-based navigationOpen ↗
Systems-level · Network

ASV Full

The uncompressed, complete hub-node map — an expansive web of interconnected concepts, comorbidities, and trajectory branches, as a master blueprint.

Full network blueprintOpen ↗
Systems-level · Network

ASV Simulator

An interactive sandbox on the hub-node system letting users manipulate clinical variables and watch changes cascade through the reasoning network live.

Hands-on variables simOpen ↗
Research Papers & Preprints

Academic Publications

Research papers, technical architecture proposals, and preprints from the VibeRounds project — all available open-access on ResearchGate.

Preprint ★ Featured

VibeRounds: A Composable Architecture for Socratic Clinical Reasoning with Large Language Models — Design Rationale, System Description, and Composition Semantics for the Clinical Cognition Operating System

The flagship VibeRounds architecture paper — lays out the design rationale, system description, and composition semantics behind the Clinical Cognition Operating System underlying the framework.

↗ View on ResearchGate
Preprint

Modern Clinical Reasoning & Socratic AI: Integrating Promption and Provocation Cognitive Modes into Healthcare Analytics

↗ Read Preprint

Full Publication List

All preprints and works in progress are maintained on ResearchGate by Dr. Avinash Kumar Gupta.

↗ View ResearchGate Profile
CCOS at a Glance

Clinical Cognition Operating System — Summary

A one-page visual overview of how CCOS is positioned as a learning stack for clinical analytics and reasoning — not for decision making.

CCOS is best positioned as a Learning Stack to do Clinical Cognition and Reasoning Around a Case

For learning. Not for decision making. — Learn deeply. Reason broadly. Think critically.

How CCOS supports learning around a real case

1. Input a Real Case
History, exam, labs, imaging, notes, etc. — de-identified real cases from practice or public sources.
2. Structure & Contextualize
CCOS organizes the case into clinical context using its ontologies and knowledge framework: problem representation, timelines, differentials, context tags.
3. Multi-Perspective Clinical Cognition
Explore the case through multiple clinical lenses — neurocognition, systems thinking, bias awareness, evidence, patterns — via hypothesis generation and comparative reasoning.
4. Guided Cognition with Prompts
Use the CCOS Prompt Library — Socratic prompts, reflection prompts, what-if scenarios — to ask better questions and deepen reasoning.
5. Synthesize & Learn
Summarize insights, key takeaways, and what you would do (or consider) — with rationale — into learning notes and mental models.

Outcomes for learners

  • Stronger clinical cognition
  • Deeper understanding of disease and context
  • Exposure to variability in real cases
  • Better preparation for rounds, discussions, and boards
  • Builds judgment — not replaces it

Built on a strong foundation

  • LLM-powered reasoning and generation
  • Model-agnostic and future-ready
  • Modular architecture for continuous learning

Prompt library, every step of reasoning

  • Case framing prompts & evidence appraisal
  • Hypothesis generation & what-if scenarios
  • Pathophysiology exploration
  • Reflection & metacognition

Curated prompts to think better, not just faster.

NOT ITS STRENGTH — Not for Decision Making
  • Does not replace clinician judgment
  • Not a guideline engine
  • Not real-time risk prediction
  • Not the final basis for treatment decisions
  • Does not eliminate the need for clinical responsibility

A Clinical Cognition Stack that helps you think deeper, see wider, and learn faster around real cases.
For Learning. Not for Decision Making.

Choose Your Goal

Pick what you want to accomplish — CCOS guides you to the right pipeline and modules.

I want to solve a clinical case
Best for: ward rounds, OPD, complex cases
Pipeline: Orientation → Socratic Reasoning → Differential Diagnosis → Problem Representation → Diagnostic Strategy → Management Reasoning → Reflection
I want to learn a disease
Best for: deep learning, exam preparation
Pipeline: Illness Script → Disease DeepDive → Mechanism Explorer → Evidence Appraisal → Clinical Pearls → High Yield Review → Reflection
I want to become an expert clinician
Best for: long-term growth, clinical mastery
Pipeline: Expert Reasoning Reconstruction → Pattern Library → Heuristic Trainer → Deliberate Practice Loop → Cognitive Bias Detection → Reflection
I want to do research
Best for: research projects, evidence-based practice
Pipeline: Identify Knowledge Gaps → Literature Review → Research Question → Critical Appraisal → Data Synthesis → Case Report/Manuscript
I want to teach
Best for: teaching sessions, small groups, PBL
Pipeline: Case Selection → Socratic Discussion → DeepDive & Resources → Reflection → Assessment/Quiz → Feedback & Wrap-up
I want to write a case report
Best for: case documentation, publication
Pipeline: Case Documentation → Literature Review → Structure & Outline → Writing Assistant → Review & Edit → Journal Preparation
I am preparing for exams
Best for: board exams, OSCE, quizzes
Pipeline: High Yield Review → Question Generator → Spaced Repetition → OSCE/Viva Prep → Mock Assessment → Performance Review

Starter pack — top 10 modules

1. Socratic Clinical Reasoning ★★★★★
6. Clinical Pearls ★★★★★
2. Differential Diagnosis DeepDive ★★★★★
7. Patient Advocate Documentation ★★★★
3. Semantic Qualifiers & Problem Representation ★★
8. Cognitive Bias Detection ★★★★
4. Illness Script Acquisition ★★★★★
9. Disease DeepDive ★★★★
5. Reflection & Metacognition ★★★★★
10. Evidence Appraisal ★★★★

Why CCOS?

  • Structured yet flexible — use full pipelines or just the modules you need
  • Multi-perspective — explore cases from multiple clinical lenses
  • Evidence-informed — built on clinical reasoning and best evidence
  • Deep learning — build understanding that lasts
  • Transferable skills — improve reasoning across disciplines and settings
  • Reflective practice — grow through reflection and deliberate practice

How to get started

  1. Choose your goal — pick the goal that matches what you want to accomplish
  2. Follow the pipeline — use the recommended pipeline step-by-step
  3. Explore modules — dive into the modules suggested at each step
  4. Reflect & improve — use reflection to consolidate your learning
NOT ITS STRENGTH — Not for Decision Making
  • Does not replace clinician judgment
  • Not a guideline engine
  • Not real-time risk prediction
  • Not the final basis for treatment decisions
  • Does not eliminate the need for clinical responsibility

Think Better. Learn Deeper. Care Smarter. For learning. Not for decision making.
Use CCOS to learn, explore, reason and prepare. Use your clinical judgment to decide.
CCOS empowers your mind. You guide the patient's care.

Vibe Rounds

Clinical Reasoning Learning Tools

A set of AI-assisted learning tools for case-based Socratic learning, multi-angle critical thinking, shared decision-making practice, and debate-style reasoning — each one built to sharpen judgment through questions, not to hand you answers.

★ FLAGSHIP TOOL
Tool Hub
All your common tools in one place — the combined workspace bringing every module in this collection together into a single flow. Start here if you're not sure which tool to open.
Open Tool Hub →
Case Bench
A tool for case-based Socratic learning, MCQs, and clinical reasoning analytics.
Case Simulator
An interactive tool for running through simulated patient cases.
Clinical Practice
A focused drill tool for practicing clinical cases.
Clinical Polemos
A debate-style exercise for discussion and reasoning.
Case Lens
A tool for critical thinking around clinical cases from multiple analytical angles.
SDM Lens
A tool focused on shared decision-making scenarios.
EBM Query Generator
Generate a structured set of critical-appraisal queries.
CCOS Builder
Build and order modules for the Clinical Cognition OS.
Case Analytics
Analytics tool for reviewing clinical reasoning performance.
Case Reading
A tool for guided reading and analysis of clinical cases.
Critical Hub-Node Navigation
The Avinash Principle — find the handful of nodes that decide the outcome.
Complex Flow Builder
A tool for mapping and building out complex clinical decision flows.
CQM Router
Clinical query/module router for directing cases to the right tool or pathway.
Case Question Bank
A bank of clinical case questions for practice and review.
Courses
Courseware
Structured course material and modules for guided clinical learning.
EBM Course
A course on evidence-based medicine — critically appraising and applying clinical evidence.
Clinical Cognition Course
Course content on critical care reasoning and decision-making.
Tutor · Article · Research
Tutor
A set of interactive, drill-style tools for practicing clinical reasoning.
Article
Background reading on the Vibe Rounds paradigm and its approach to clinical reasoning.
Research (Bench Lite)
Run a Socratic learning session, then hit Submit at the end — it helps gather data for research.
Videos
YouTube Channel
Quick walkthroughs of each tool, plus lectures and background information.
Training

Reading the framework gets you the "what." A live session with Dr. Avinash gets you the "how" — running an actual case, live, with a group asking the same questions you are. Online Zoom sessions and on-site training for departments are both available, with access to an ongoing builder community for training participants.

Connect for a Session (WhatsApp)
Mention online/offline, your group size, and the use case you'd like the session built around.
Email
avi33tbtt@gmail.com — for training inquiries and session requests.
Dr. Avinash — LinkedIn
Connect directly on LinkedIn.

Coming soon

Patient Centered Research

A new section on patient-centered research is in development. Check back soon for updates.