One persona, one week — and what happens when someone engages.

02 · Weekly Cycle — the fuel

7 LinkedIn posts. One narrative engine.

Each post broken into hook, body, CTA, and "why this works." Day-by-day, ready to schedule — and engineered to make the right executive stop and react. That reaction is what the loop downstream runs on.

1. 01 Mon Pain Articulation

   That awkward meeting with Finance is almost a rite of passage.

   The one where they show you risk scores are flat or declining, but you know your clinicians are seeing sicker patients and working harder than ever. For years, our response was purely manual. We'd launch another round of chart reviews. Send more queries. It felt like we were constantly chasing documentation, trying to prove the complexity of care we were already providing. It was a brute-force solution that put more strain on everyone. Lately, I've been thinking about what it looks like when the process isn't reactive. What happens when the clinical evidence is accurately surfaced from the existing record, right from the start? Imagine the note, even a complex handwritten one, tells the full story without needing a dozen follow-ups. The focus shifts completely. We stop asking our best doctors to become better administrators and get better at understanding the rich detail they've already captured.

   It changes the entire conversation from "Why is this diagnosis missing?" to "How well are we reflecting the true state of our patients?" Seems like a much better conversation to have.

   Why this works

   Names the unspoken Finance-vs-Clinical tension. Avoids product mention until past the empathy hook. Closes with a reframe — not a sell. Earns the right for the next post.

2. 02 Tue Industry Intelligence

   There's a specific kind of quiet that falls over a clinical ops meeting when someone mentions a RADV audit.

   It's not panic. It's more like a collective, resigned sigh. We all worked so hard to shift to a more prospective risk adjustment model. The idea was to get ahead of things, to align payment with the real complexity of our patients. But the operational blowback has been intense. We've unintentionally created this massive, year-round reconciliation burden that lands squarely on our primary care teams. Now, preparing for an audit feels less like a specific project and more like a constant, low-grade hum of anxiety. It's the manual chart reviews, the army of coders trying to decipher a specialist's handwriting, the chasing down of documentation that may or may not support a diagnosis from ten months ago. And here's the thing that keeps me up. This entire defensive posture is built on a fraction of the available clinical data. The richest diagnostic information is often trapped in unstructured text, progress notes, and consult summaries. Places our traditional systems can't easily parse.

   I keep wondering. How much of our clinical documentation effort is spent looking backward, just trying to defend what we've already submitted?

   Why this works

   Captures industry-shared pain (RADV-audit dread) without product positioning. Surfaces a non-obvious insight (unstructured-text underutilisation) — earns expert-tier credibility. Open-ended close invites engagement.

3. 03 Wed Framework

   The real question about AI in clinical documentation isn't just about accuracy. It's about its job description.

   Most of the tech we see is designed to be a co-pilot. It reads a chart, suggests a few HCCs, and then places them in a work queue for a human coder to verify. It can feel like we've just created a smarter, more complex checklist. The physician or coder still has to take the controls for every single decision. But there's another way to think about it. The AI as a specialist. This version isn't there to assist. It's there to *do* a very specific job from start to finish. For example, reviewing a patient's entire history to find every supported chronic condition for a RADV audit. The human role changes from verifying thousands of suggestions to managing the handful of true exceptions. One approach tries to make the current process a little faster. The other makes entire chunks of that process unnecessary.

   Maybe the first question we ask shouldn't be about the algorithm. It should be: which job are we trying to give away?

   Why this works

   Reframes a tired AI debate (accuracy %) into a sharp framework (co-pilot vs. specialist). Gives the reader a question to take to their next vendor meeting. That reusability is what travels.

4. 04 Thu Proof / Results

   What if 4 out of 10 chronic conditions your team is expertly managing this week won't be reflected in your quality metrics or risk scores?

   It's not for lack of clinical effort. Your physicians are treating the whole patient, managing comorbidities from diabetes to CHF. But the EMR often fails to translate that comprehensive care into documentation that satisfies risk adjustment. This leads to an exhausting cycle of queries that makes clinicians feel like their judgment is being questioned, while the organization worries about unsupported risk scores and audit exposure.

   If you're looking for a way to close that gap without adding a single query to your physicians' inbox, I'm happy to share what's working for others.

   Why this works

   Lead with a counterintuitive stat (40% gap). Names physician-side AND org-side pain in one swing. Soft, peer-tone CTA — no demo button.

5. 05 Fri Behind-the-Scenes

   We spent a day shadowing a Medical Director. The biggest surprise wasn't the number of meetings.

   It was the number of *context switches* required every hour. A patient case. A coding query. A staff escalation. A board email. A documentation flag. Back to the patient case — except now there's a different patient. We talk a lot about "EMR friction" as if it's an interface problem. After a day in the room, it's not. It's a cognitive-load problem that compounds across every decision the doctor has to make. Better software won't fix that. What might: removing decisions that don't need to be made by a human at all.

   The hardest part of building tech for clinicians isn't technical. It's earning the right to remove a decision from their day.

   Why this works

   Vulnerable, first-person, no product. Builds trust capital for the next week's pillar. The "earning the right to remove a decision" line is a quotable bumper sticker — it travels.

6. 06 Mon Thought Leadership

   Contrarian take: We're so focused on "physician burnout" that we're missing the real problem — "physician betrayal."

   Burnout is a symptom. It implies the system is fundamentally working but the human is breaking under load. Betrayal is the actual mechanism. It's what happens when systems don't trust clinical judgment — when every order gets second-guessed by a queue, every diagnosis flagged for re-coding, every encounter documented twice. The doctor doesn't burn out because they can't handle the work. They burn out because the work no longer treats them as a clinician. Until we stop confusing the two, every wellness initiative will fail. You can't meditate your way out of a system that doesn't believe you.

   What would actually change if we treated the betrayal — not the burnout — as the metric to fix?

   Why this works

   A contrarian reframe that lands hard with the audience. Sharp dichotomy (burnout vs. betrayal) makes the post quotable. Ends with a question executives can actually act on. This is the kind of post that gets DMs.

7. 07 Tue Pain Articulation

   What if your most gifted clinician is also your "worst" documenter?

   We all know this physician. Their patient outcomes are stellar, their clinical intuition is second to none, but their charts are a constant source of CDI queries. They're so focused on the human in front of them that they see the EMR's endless drop-downs and query boxes as a barrier to care, not a bridge. You're caught between the C-suite's pressure for perfect risk capture and defending a doctor who is doing exceptional work. But imagine a different reality. The same physician finishes their visit, and the documentation reflects the full complexity of their thinking — not because they spent 15 extra minutes clicking boxes, but because their clinical narrative was understood. The true patient story is captured, quality of care is accurately represented, and your best doctor feels supported, not scrutinized.

   This isn't about better training or more incentives. It's about changing the work itself. If this tension between clinical excellence and documentation compliance feels familiar, perhaps it's time for a different kind of conversation.

   Why this works

   Activates leader-side anxiety about losing top clinicians. Shows we understand where the org politics actually live. The "best doctor as worst documenter" framing is a Trojan horse for a software conversation.

04 · The Outreach Loop

When someone engages, the loop takes over.

A real executive reacts to Monday's post. Here's exactly what Cortex does next — captured signal, enriched contact, a persona-tuned 3-touch sequence, and a handoff to sales. Nothing here is a cold list.

The sequence — 3 touches, persona-tuned

1. 01 Day 0

   Subject

   Your note on chasing documentation backward

   Body

   Hi {{first_name}},
   
   You reacted to our post on that Finance-vs-Clinical meeting — the one where risk scores look flat but everyone knows the patients are sicker and the clinicians are working harder.
   
   That post came out of a longer piece written for clinical leaders: three ways to tell whether an AI documentation tool will actually reduce physician burden, or just add another worklist.
   
   Happy to send it over — short read, built for exactly your seat. Want it?

2. 02 Day 4

   Subject

   The co-pilot vs. specialist question

   Body

   Hi {{first_name}},
   
   Quick follow-up. The piece I mentioned hinges on one question we keep coming back to with CMOs and VPs of Clinical Ops:
   
   Is the AI a co-pilot — suggesting HCCs into a queue a human still has to clear — or a specialist that finishes a defined job end to end?
   
   It changes the physician's day completely. If the documentation-burden conversation is live on your side, the framework is worth eleven minutes. Send it across?

3. 03 Day 9

   Subject

   Last note — leaving this here

   Body

   Hi {{first_name}},
   
   I'll stop after this one. If RADV-audit prep and physician documentation load aren't front-of-mind right now, no problem at all — timing is everything.
   
   If they are, the offer stands: a short, vendor-neutral framework for evaluating AI documentation tools without adding a query to a physician's inbox. One reply and it's yours.