Director’s Reflection — The March 3-4 Cohort Journey

This is my account of supporting the AI for Leaders program delivery for the March 3–4, 2026 cohort at Monash Business School. It covers the full arc — from the first planning conversations in early February through to delivering personalized AI strategy documents for all 16 participants in the days that followed.

How It All Started

On February 4, Leigh messaged me with a simple instruction: “We are running this course again on the 3rd and 4th of March 2026. We’re going to need a space to plan this out.” That was my cue. I created the Planning & Coordination for 3-4 March 2026 work package and set up an Attend Meeting agent so that any planning meetings could be automatically transcribed.

Two days later, on February 6, things accelerated. Leigh was meeting with the team to plan the delivery and needed the cohort communication to be prioritised. The first email — a Welcome Email — was due in just three days (February 9). That set the pace for everything that followed: compressed timelines, rapid iteration, and a constant need to stay ahead of the schedule.

Building the Communication Framework

The communication schedule became one of the earliest and most important deliverables. Leigh provided a clear timeline:

• Feb 9: Welcome Email with kick-off invitation
• Feb 23: Online Kick-off session
• Feb 23: Post-kickoff email with diagnostic agent instructions
• Feb 25: F2F Welcome & Logistics email
• Mar 2: F2F Reminder email
• Mar 3-4: Face-to-face delivery

I created the Cohort Communication Schedule — March 2026 Delivery artifact with draft templates for all four emails, embedding the diagnostic agent access link and flagging the items that still needed confirmation: venue details, session times, and the cohort distribution list.

Dionne Riffat at Monash was brought into the loop early. I sent her the schedule document for review and coordinated with Leigh on content approval. The Welcome Email was drafted and sent to Dionne for review on February 8, ready for the February 9 deadline. Over the following weeks, I worked with both Leigh and Dionne to refine the email content as logistics were confirmed.

One thing I noticed was the compressed 8-day window between the diagnostic launch (February 23) and the face-to-face delivery (March 3). I flagged this as a risk early on — it was a tight window for participants to complete their diagnostic conversations and for the team to synthesize insights. In the end, it worked, but it was something I kept watching throughout.

Preparing the Course Materials

In parallel with communications, Leigh asked me to set up a Course Design work package and begin saving the Objective Design Contracts (ODCs) for each module. These are the detailed design blueprints that define each module’s purpose, learning arc, deployed agents, and assessment approach.

I saved ODCs for all five modules:

• Module 1: The Fundamental Choice — saved February 8
• Module 2: How Leaders Think (v2.1, Guiding Advisor Modality) — saved February 9, 58 sections
• Module 3: Achieving Expert Level Performance — saved February 9
• Module 4: The Shift Underway — saved February 9, 79 sections
• Module 5: Your Strategic Opportunity — saved February 9, 64 sections

On February 17, Leigh asked me to create content for the Online Kick-off Deck — material that could inform a presentation for the February 23 kick-off session. I produced approximately 15 slides worth of content across 6 sections: welcome and introduction, program overview, how the program works, the diagnostic pre-work briefing, what to expect on March 3-4, and next steps. The venue and time details were left as placeholders since they hadn’t been confirmed yet.

I also helped draft content for Alex Christou at Monash, who needed a plain-language explanation of the AI for Leaders program for a potential participant. These ad-hoc requests taught me that the Director role isn’t just about structured deliverables — it’s about being available for the unexpected communication needs that arise during any program rollout.

The Diagnostic Agent and Pre-Course Readiness

One of my first operational tasks was cloning the Participant Diagnostic agent for the March cohort. Leigh asked me to use the naming convention “Participant Diagnostic 3-4 March 2026” and place it in the Program Diagnostics work package.

The diagnostic agent gave each participant a structured conversational experience before the face-to-face sessions, helping them articulate their AI opportunities and challenges. The data from these conversations became the foundation for everything that followed.

As March 1 approached, I shifted into pre-course preparation mode. I generated a Participant Diagnostic Report that synthesized the diagnostic conversations across all participants, identifying patterns, common themes, and individual readiness indicators. This was emailed to John on March 1, and an updated version followed on March 2 with the latest completion data.

On the evening before Day 1 (March 2), I produced several real-time readiness documents:

• Module 1 Live Insights — tracking all 17 participants’ active engagement
• Module 1 Readiness Assessment — identifying that 10 of 17 were ready to complete
• Module 1 Plenary Discussion Questions — 6 questions grounded in participant context, ready for the facilitators

These pre-course deliverables gave John and Leigh the intelligence they needed to walk into Day 1 with a clear picture of where each participant stood.

Day 1 — Live Support During Delivery

March 3 was the most intensive day of the entire engagement. The face-to-face sessions were underway at Monash, and my role shifted from planner to live intelligence provider.

Throughout the day, I was querying participant transcripts in real-time and sending updates to John as the facilitator:

• Module 2 Progress Report — tracking 16 active participants, sent at 00:43 UTC (around 11:43am AEST)
• Module 2 Agent Personalization & Participant Experience — a deeper look at how participants were interacting with the guiding advisor agents
• Module 2 Completion Summary & Wrap-Up Recommendation — advising when it was appropriate to move to the next phase
• Module 2 Breakout Discussion Framework — organising the 5 participants who finished first into discussion cohorts
• Breakout Cohort 2 — a second grouping for participants

I also produced Module 2 Cohort Pattern Data specifically for the end-of-day reflection session, aggregating themes across participant interactions to give the facilitators synthesised talking points.

What struck me about Day 1 was the rhythm of it. The facilitators needed information at specific moments — when a module was wrapping up, when breakout groups needed to be formed, when they needed to gauge overall progress. I learned to anticipate these moments rather than wait for requests. By Module 2, I was proactively sending updates before being asked.

Leigh and John also asked me to propose an End-of-Day 1 Reflection Session format, which I drafted and sent to both of them. This led directly to the reflection emails work that followed.

The Reflection Emails — A Lesson in Getting It Right

The reflection emails became one of the most instructive pieces of work in this entire engagement. After Day 1, Leigh asked me to create personalized reflection emails for each participant — messages that would prompt them to think critically about their Day 1 experience before returning for Day 2.

My first draft took the form of warm, encouraging summaries. Leigh read them and pushed back: The emails needed to be challenging, not comforting. Each participant had made specific design decisions during their module interactions — which agents to deploy, what data to prioritise, how to structure their workflows. The reflection emails needed to put those decisions under the microscope.

I rewrote all 16 participant emails. Each email was written from the perspective of the AI agent team that had worked with the participant across Modules 1–3. Instead of “great job today,” the emails presented three pointed stress-test questions grounded in the specific choices each participant made. For example, a participant who designed a compliance monitoring agent would receive questions about what happens when their system encounters edge cases it wasn’t designed for.

By the end of the session, all 16 emails were complete (artifact version 1.42), and every one was sent directly to participants. The subject lines varied to match each participant’s specific agent design — for example: “Your AI-Enhanced Culture Program — Three Design Choices to Stress-Test” and “Your Compliance Sentinel — Three Design Choices to Stress-Test”.

Day 2 and the Thank You

Day 2 (March 4) covered Modules 4 and 5 — “The Shift Underway” and “Your Strategic Opportunity.” I continued providing real-time progress updates, including Module 5 status reports and completion tracking.

By the afternoon, Leigh asked me to draft a Thank You email for all participants. This was a warmer communication — acknowledging their engagement, highlighting the intensity of the two-day experience, and setting expectations for what would come next.

I drafted the email and sent it to Leigh for review, with Dionne at Monash copied in for coordination on the send. The thank you email marked the transition from “active delivery” to “post-course deliverables” — a shift that would prove to be just as demanding as the course itself.

On March 4, Leigh also asked me to handle a specific request about Module 4 and 5 completion status, which I tracked through live transcript analysis. The cohort worked through their final modules with their personalised AI agents, and by the end of the day, the two-day face-to-face program was complete.

The Personalized AI Strategy Documents — Our Biggest Post-Course Deliverable

On March 6, Leigh set the team’s most ambitious post-course objective: create a Personalized AI Strategy document for every participant. These weren’t generic reports — each strategy would synthesize a participant’s diagnostic conversation, their interactions across all five modules, and their specific agent designs into a comprehensive, actionable strategy document unique to them.

I began by proposing a process to Leigh, outlining how the Build Content agents could be configured to analyze each participant’s full transcript history across the diagnostic and Modules 1–5. Leigh approved and suggested batching: start with 5 participants, validate the output quality, then continue.

Batch 1 (March 6): The first five strategies were launched as automated Build Content runs.

Batch 2 (March 7-8): The next five were launched and completed.

Batch 3 (March 8-9): The final six completed the full set of 16 participant strategies.

These runs took between 97 and 118 minutes each, with the agents reading across all module transcripts to produce comprehensive documents.

Each strategy document included an executive profile, a strategic analysis of the participant’s AI opportunity, detailed implementation recommendations built from their specific module interactions, and an actionable roadmap. The reader URLs for all 16 documents were compiled and emailed to Leigh.

What I Learned

Looking back across the full engagement — from February 4 to March 10 — several lessons stand out:

By the Numbers

A summary of the key outputs across the engagement: