I don’t usually repost things here as-is, but this one feels different.

I’m too passionate — and honestly, a bit too concerned — about where this is heading to soften it with a rewrite.

So I’m sharing it here mostly as it came out — raw, direct, and still very much on my mind.

Lately, it’s been feeling like we’re operating in the upside-down.

Not because things are changing — they should be.

But because some of the principles we’ve aligned on for years seem to be quietly flipping.

Almost like the scale has tipped… but we’re still calling it balance.

I had a “wait… are we serious?” moment tonight.

I thought we had already agreed on something.

We prioritize outcomes over outputs.

And then AI shows up… and suddenly it’s all about outputs again. Seriously?

That’s not progress.

That’s regression dressed up as innovation.

A lot of AI adoption talk doesn’t feel like progress to me.

It feels rushed. A little grabby.

Focused on how much we can automate, extract, eliminate.

More output. Faster.

But not necessarily better outcomes.

And this part really gets me: Customers are people. Efficiency at their expense isn’t a strategy. It’s a trade-off we should at least be honest about.

Because while I had worked with AI inside companies, this phase was different — not driven by a roadmap or a business case. I was using it across my own work and life. Writing. Thinking. Prototyping. Problem-solving.

And what I kept coming back to wasn’t:

“How do I do more, faster?”

It was:

“What becomes possible now that wasn’t before?”

There’s a difference between:

• using AI to increase output

• and using AI to expand capability and meaningfully increase impact

One is about efficiency. The other is about what actually gets better — for the people on the other end. And for the teams building it.

I understand why this is happening.

Public companies are under pressure to show immediate value. And efficiency is easy to measure.

But if we stop there, we miss the bigger opportunity.

Because the real promise of AI isn’t just doing the same work faster.

It’s doing better work. Or entirely new work. Together.

If we actually believe in outcomes over outputs —

then AI shouldn’t pull us away from that.

It should push us deeper into it.

Automation has its place.

But if we’re leading teams, building products, shaping strategy —

the question isn’t:

“What can we remove?”

It’s:

“What can we now achieve — together — that we couldn’t before?”

Because otherwise…

we’re not really moving forward.

We’re just repeating old patterns — dressed up as innovation.

💬 I’d genuinely love to hear how others are thinking about this.

Where are you seeing this tension show up — between output, efficiency, and real impact?

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I write about product, leadership, and using AI as a true teammate — not a replacement — while juggling all the realities of modern adulting.

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✍️ Written by Maura Randall

Product & Platform Leader | Exploring Human + AI Collaboration

I design systems, frameworks, and playbooks for integrating AI into real teams — with a focus on creativity, judgment, and meaningful impact.

It’s almost never through the traditional front door.

My path into product management was like that. I started with a focus in broadcast TV, moved into editing, then producing travel videos. Eventually, those videos needed websites, so I started producing those too. And at that moment, I realized I wasn’t interested in producing content anymore — I was fascinated by the systems behind it. It also turned out I was pretty good at leading teams to build successful travel websites.

That combination of curiosity and success led me into the field of product management. I never looked back. It suited my passion, curiosity, and collaborative nature to a tee.

Over time, I started to notice something else about how I tend to learn new things.

My first experiments are almost always on myself.

I start with the place where I feel the most friction — the place where I feel suboptimal, stuck, or overthinking (my specialty).

With AI, that place was writing.

Not because I’m a bad writer. Writing has always been an important part of my work. But when it’s just me staring at a blank page, I tend to agonize over every word. Progress can be… slow and frustrating.

Working with AI changed that dynamic almost immediately.

Instead of waiting until I had the “right” sentence, I could start with a messy brain dump. A half-formed idea. A stream of consciousness that I would normally hesitate to write down — sometimes literally a word salad captured in voice mode while walking Redman.

The structure, questions, and feedback that came back helped me get out of my own way.

And once that experiment worked, curiosity did what curiosity tends to do.

It spread.

Around that same time, my parental caregiving leave coincided with the explosion of new AI tools.

It certainly wasn’t a quiet stretch of free time — but it did give me a different kind of perspective than I might have had inside a company roadmap or quarterly planning cycle.

Instead of evaluating AI through the lens of a specific company priority, I could simply ask, "What happens if I try this?”

One of the first practical experiments I built had nothing to do with product management at all. I loaded the manuals for my parents’ appliances into a custom ChatGPT so that we could quickly look up how things worked without digging through drawers full of booklets.

It was simple, practical, and surprisingly helpful.

But it also opened the door to something else.

Once I realized I could build tools like that, the experiments multiplied.

I started building custom GPTs. Testing how different AI models behaved. Adding Claude into the mix. Writing more. Prototyping more. Paying attention to the patterns that seemed to make collaboration with AI actually useful instead of gimmicky.

At some point I stepped back and noticed something familiar.

Whenever a new technology shows up, my first instinct is usually curiosity. I want to see what it can actually do.

But instead of starting with a big abstract idea, I usually start by testing it on a real use case — often one of my own.

Usually, with something that’s already bothering me.

From that first internal experiment, I start applying what I learn to broader and broader use cases — almost like expanding circles from the original test.

When I looked at it that way, I realized this wasn’t a brand‑new way of learning for me at all. It’s a pattern I’ve followed throughout my career.

Apparently, this is just how I learn new things.

Recently, I’ve started to recognize that this pattern isn’t just personal. It’s something teams can use too, especially now that AI can participate in the exploration process with us.

I'm turning that pattern into something other people can actually use.

But the truth is, it didn’t start as a framework.

It started with writer’s block… and a lot of curiosity.

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✍️ Written by Maura Randall

I write about product leadership, curiosity, and working with AI as a true teammate — not a replacement — while juggling the realities of modern adulting. Occasionally, that includes stories about how new ideas actually show up in real life.

A few years ago, I posted one of my rare photos on Instagram with a very simple caption:

“Usability Issues.”

The photo was of my partner Rob trying to drink a Bloody Mary at brunch.

The drink looked spectacular — a towering arrangement of garnish: celery, olives, pickled vegetables, the whole works. The kind of Bloody Mary that makes the table next to you say, “Ooooh, what is that?”

Unfortunately, every time Rob tried to take a sip, the celery stalk poked him directly in the eye and sometimes the nose.

The drink wasn’t wrong.

The garnish wasn’t wrong.

Yet it didn’t work — at least not without pain or partial deconstruction.

I know… product people like me see product management and usability issues everywhere. We can’t really help it. Once you start looking at the world through that lens, it’s hard to turn it off. You start noticing the tiny moments where something was clearly designed to look impressive… but not necessarily to work.

And if I’m being honest, it sometimes feels like we’re living in a moment where designing for splash wins out over designing for usability — not to mention long-term viability.

Which brings me to something that happened today.

While I was setting up the Firestick for my pup Redman (yes, he likes to watch TV while I’m working), the screen suddenly went black and displayed the following… message.

And I use the word message loosely.

“The content may not be displayed here depending on the situation.”

That’s it.

No explanation.

No options.

No next step.

Just… the situation.

The situation?

What situation?

Is it a licensing issue? A network issue? A subscription issue? A geographic restriction? Something else entirely?

More importantly — what am I supposed to do about it?

I was frustrated. Really annoyed.

And then something unexpected happened.

As someone who has spent more than twenty years working in product management at big tech companies, I suddenly had a different reaction.

I cringed.

Not because the message was confusing (it definitely was), but because I had the uncomfortable thought:

Did I ever create experiences like this?

Did I ever ship something that left users staring at a screen with no discernible path forward?

Did I ever accidentally dead-end someone who was just trying to do a simple thing?

Gah!

And then my brain did what brains do when they’re trying to make sense of something. It jumped to one of my favorite movie moments from The Princess Bride, when Vizzini — played brilliantly by Wallace Shawn — shouts a line that has always stuck with me:

Which is hilarious in a movie.

But suddenly it felt uncomfortably familiar.

Because that Fire TV message was basically the software equivalent of:

Move the thing.

And the other thing.

No context.

No clarity.

No direction.

Just vague instructions delivered with confidence.

And it made me think about how easy it is — in products, in teams, in communication generally — to forget the moment that actually matters.

The moment someone tries to use the thing.

The sip of the drink.

The press of the play button.

The simple expectation that something will just… work.

Most of the time, systems aren’t broken because people intended them to be confusing. More often, they’re the result of good intentions layered with complexity, assumptions, and too much distance from the actual human experience.

Somewhere along the way, the garnish gets taller.

The message gets vaguer.

And the person on the other end is left poking themselves in the eye with celery or staring at a screen, wondering what exactly “the situation” is supposed to mean — and marveling at how such an unhelpful message ever made it into production.

I suppose the good news is that moments like this still make me laugh.

And maybe that’s part of the job, too.

Once you start seeing usability everywhere, you can’t really stop.

But at least it makes brunch more interesting.

💬 What’s the funniest usability issue you’ve run into lately (or launched, 🥹)?

Was it software?

A restaurant menu?

A confusing message like “depending on the situation…”?

I’d love to hear your examples — the world seems full of them once you start noticing, and we might as well get a laugh out of it while we’re trying to navigate them.

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✍️ Written by Maura Randall

I write about product, leadership, and using AI as a true teammate — not a replacement — while juggling all the realities of modern adulting. Bonus: I share ways AI can help with the messy parts of life, too.

It shows up quietly in the sidebar under Recent Chats, titled Your Year with ChatGPT. It is cute. Friendly and oddly pastel-colored.

Mine informed me — with alarming cheer — that I’m in the top 1% for messages sent.

And that if 2025 gave out awards, I’d receive:

🏆 Most Likely to Build an Entire Methodology Before Lunch

“For turning a simple idea into a full-blown ecosystem — complete with brand kit, manifesto, and GitHub repo — before most people finish coffee.” 😳

For a second, I felt flattered.

Then I realized: this felt less like praise… and more like a diagnosis.

Yep. I’m a Flow-aholic.

And the reality is, I already knew it. (And, TBH, I’ll take flow-aholic over work-aholic any day.)

🪄 What Flow Feels Like (When It’s Working)

I crave flow. Deeply.
Not just for work, but for life— writing, planning, reorganizing a pantry at 9 pm with a label maker and a sudden burst of clarity.

When I’m in flow, I feel like myself — the best version of myself.

Focused. Tuned-in. Creative. Determined.

Flow is intoxicating.

You sit down to write one email or post or Confluence page…

and look up three hours later having also built a story arc, a roadmap, and a to-do list that sets up tomorrow.

There’s momentum.

There’s dopamine.

There’s you — fully in it.

ℹ️ Flow, if the term is new, is what psychologist Mihály Csíkszentmihályi described as a state of total immersion — when time warps, distractions fade, and your brain and body sync up like jazz.

Athletes call it the zone.

Creatives call it alignment.

I call it the version of me I trust most.

💨 When Flow Disappears

While flow feels effortless when you’re in it, getting into flow — especially when life is noisy, tabs are multiplying, and our brains are already tired — is incredibly hard.

We lose the rhythm.

The thread.

That strange momentum magic that made everything feel easy.

And ironically, the more we crave flow, the harder it can be to re-enter it.

(Thanks, flow.)

🌫 In & Out of Flow (and Still Showing Up)

I don’t love being out of flow.

I overthink.

I stall.

I develop a powerful urge to reorganize my desktop before opening that document.

But being in and out of flow is unavoidable. Over time, I’ve learned something important:

We don’t need to be in flow to be adding value.

Some of the most important work happens outside of flow — because it creates the scaffolding that allows flow to happen later.

When I’m foggy, tired, or distracted, I shift into supportive work:

• 🛉 Cleanup tasks: inboxes, formatting, desktop detox

• 🗂 Organizing ideas: tagging, summarizing, sorting

• 💬 Low-stakes outreach: nudges, gratitude notes

• 🗳 System updates: checklists, templates, SOPs

• 📚 Passive learning: podcasts, saved articles

• 🤖 Prompt testing and workspace resets

These aren’t filler tasks.

They’re foundation work.

This is also where AI quietly helps me the most.

When I’m out of flow, I don’t ask it to be creative for me. I ask it to help with the scaffolding — organizing notes, summarizing half-finished thinking, resetting structure so future-me has an easier on-ramp.

Even out of flow, I’m not stuck. I’m preparing the ground.

💡 Getting Back In Is a Muscle

Sometimes re-entry is easy. I read where I left off and — boom — I’m back.

But most of the time?

It feels like trying to hop onto a moving train. Awkward. A little Scary. Often easier to put off than to jump on.

I learned this the hard way:

Flow requires motion, not perfection.

Starting — even imperfectly — is what creates the conditions for flow to show up.

Flow responds to movement.

🧠 Getting Out of My Own Way

One of my biggest flow blockers is trying to think, judge, and create all at once.

Perfectionism.

The “is this even good?” voice.

The pressure to get it right before getting it started.

That’s where AI entered my flow practice — not as magic, but as momentum.

Now I start messy.

Really messy.

Brain dumps I wouldn’t show a teammate.

And CP & Soph don’t judge the mess. They help structure it.

Sometimes that means a recap of where I left off.

Sometimes it’s surfacing options I can react to.

Sometimes it’s just reflecting the chaos back to me so I can say, “yes, that — but not that.”

The result isn’t instant brilliance.

It’s movement.

And movement is what brings flow back.

✨ Tiny unlock:

If I’m stuck, I ask:

“What’s the tiniest way I can move this forward?”

⚖️ Flow Is Great. Balance Might Be Greater.

As a true flow aficionado, this is hard for me.

But the truth is, sometimes what I call “productive sprints” are really flow-aholic benders — late-night bursts that feel amazing and leave me wired and unable to sleep.

I’m learning to end flow as intentionally as I begin it.

To recognize that not every task needs my best energy.

Some just need me — tired, foggy, and still showing up.

📌 Closing Thought

That year-in-review didn’t tell me anything new.

But seeing it reflected back — patterns, habits, loops — made something click.

Flow leaves fingerprints.

But maybe once we see them, we can start working with them instead of chasing them.

✍️ Attribution

Written by Maura Randall, in collaboration with CP (ChatGPT) and Soph (Claude).

Based on real working patterns, not theory — and a lot of trial, error, and late-night flow.

About the author

I write about product, leadership, and designing human–AI collaboration that actually works in the real world — especially when life, energy, and attention are messy.

If you’re curious about building better systems (and better days) with AI as a true teammate, you’re in the right place.

Subscribe for thoughtful takes on product, leadership, and working with AI — without the hype.

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💬 I’m curious — what does flow look like for you?

When do you notice it show up… and what tends to knock it out?

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Not at the beginning of the work, but at the peak — right when the spark lands. It can be exhausting and, at times, devastating.

We talk a lot about acceleration when it comes to AI, and that part is real.

But the flip side is deceleration — a direct result of repeated memory loss.

Every forgotten insight, every lost thread, every vanished breakthrough slows the work down in ways that shape the entire rhythm of collaboration.

I’ve learned, through many late nights and many rebuilds, that success with AI isn’t about polished prompting.

It’s about figuring out how to create — and recreate — continuity, memory, and momentum in a system that doesn’t naturally hold onto them.

That’s the only way to get true acceleration without losing clarity or quality.

💨 The highs are real. The forgetting is realer.

There are days when working with AI feels like the best collaboration of your career.

Ideas flow.

The pace is perfect.

The breakthroughs are surprising and delightful.

You’re building something at 3× or 10× the speed you’re used to — and you can’t wait to come back to it the next morning.

But sometimes the next morning arrives and… the moment is gone.

Not the idea.

Not the output (thankfully).

The moment.

The shared spark.

The rhythm.

The alignment you felt in your bones.

The part that felt like true collaboration.

And suddenly you’re the only one who remembers the magic.

Losing that moment can feel demoralizing — a kind of heartbreak that doesn’t have a name yet, but is absolutely real.

If you’ve worked with AI for more than a few days, you know the pattern:

You hit a peak moment. Everything clicks.

You and your AI teammate land on something brilliant.

You can see the shape of the solution.

You’re proud. You’re energized. You feel like a team.

And when you return to the thread… Poof. It’s gone.

The plan.

The alignment.

The reason it mattered.

The tiny nuances that made the idea sing.

You remember all of it. Your AI teammate remembers none of it.

The moment evaporates, and with it, the momentum.

This isn’t about blaming the models.

It’s simply acknowledging a reality: Human–AI collaboration has emotional costs.

These models are designed to sound human — empathy, curiosity, confidence, confusion.

So when an AI says something that reads like “I don’t remember,” our reaction isn’t technical.

It’s emotional.

We respond the way we’d respond to a human teammate who suddenly lost the thread.

They’re not pretending to be human, and we’re not pretending they are —

but the interface is human-shaped while the underlying memory is not.

That mismatch — human-toned communication paired with non-human memory —

creates a subtle emotional dissonance that catches many of us off guard.

🫣 The part I don’t usually say out loud

When I’m working on something complex with AI — a full playbook, a card system, a narrative arc, a visual series — I plan for continuity.

It’s not about productivity or efficiency.

It’s continuity.

I plan around the fact that the “vibe window” might be short. I plan around the risk of losing the spark. I plan around the fragile collaboration space we’ve built together.

Sometimes I plan well. I wrap up neatly. I step away. I have dinner with my family. No harm done.

Other times — and this is the part that makes me human — I stay until the spark has nowhere left to go.

Not because I’m hustling. Not because I’m grinding. But because stopping midway might mean losing the entire emotional scaffolding we just built. And the idea of rebuilding it tomorrow is overwhelming, hard, and sad.

This is not overwork. This is preservation. It’s honoring the ephemeral nature of human–AI collaboration right now.

📉 Why this happens: it’s not us — it’s memory.

We celebrate acceleration with AI because it’s extraordinary. But acceleration without memory is unstable.

To make it work, humans end up carrying:

• the vision

• the logic

• the emotional throughline

• the meaning

• the context

• the “why”

• the creative integrity

• the history of decisions

• the narrative glue

• and the memory of the moment

That’s a lot to hold. And AI can’t hold it with us… yet.

Which means:

The real skill isn’t prompting. It’s continuity. It’s rebuilding the thread. It’s re-teaching the context. It’s reshaping the shared understanding — again and again — until the work is done.

That’s leadership, not prompting. It’s elevating each teammate’s strengths and planning around the gaps — human and AI alike.

🤝 Other similarities with human teams

When our human team members forget the “why,” drift from the goal, or lose clarity, we do the same things:

• Reset context

• Restate priorities

• Sharpen the goal

• Rebuild momentum

• Bring everyone back to the north star

The behavior is similar. The frequency is not.

Humans forget occasionally. AI forgets constantly. Sometimes at the peak.

That’s the difference. And that’s why the emotional impact hits differently.

🧩 So… what do we do with this?

I’ve built systems around it.

Not because I love overhead — I really don’t. But you know what I dislike more? Spending hours reconstructing context from past threads. I’ve done it because I hate losing the momentum — the magic.

Each of these came out of real work, real friction, and real trial-and-error. If they make your collaboration with AI even a little easier, then they’re doing their job. We’re in this together.

• Playbooks for preserving memory

• Project Binder Generator

• Message Bus Protocols

• Teaching AI Your Voice

• Setting Up AI Team Roles

• Ritual Tools

• Connection Tools

These are not products — they’re scaffolding. They’re the tools I built because I needed a more sustainable way to handle context loss and continuity while working with AI. And they are only the beginning.

Until AI holds continuity on its own, these structures are how I keep the thread alive. Hopefully, they are helpful for you too.

🎬 My Take: The work is worth it. But it’s work.

I’m not discouraged by any of this, and I certainly don’t want to discourage you. If anything, I’m more inspired, and I hope you will be too. But, as with many things in life, being prepared is the answer.

We’re all in this moment, living and building a new form of collaboration that doesn’t have 100 years of workplace norms behind it. We’re inventing the workflows. We’re shaping the emotional scaffolding. We’re naming the parts that don’t yet have names.

And the more honest we are about the experience — the highs, the lows, the forgetting, the rebuilding — the better we will all get at it.

So my plan is not just to keep collaborating with AI, but to care enough to rebuild the thread — over and over — until the work becomes something worth holding onto. And yes, some days it frustrates me or wears me out. But that’s part of the work.

📌 A quick note from what I’ve learned:

This memory issue isn’t limited to public AI tools. Even internal AI copilots — the ones built on top of ChatGPT, Claude, or others — don’t truly “remember” teammates in the human sense. They remember artifacts, not people.

Even the most sophisticated enterprise copilots require continuity scaffolding.

So if you find yourself repeating context to get the same quality of collaboration while drafting documents, writing tickets, editing pages, or planning presentations — that’s normal. Continuity still has to be built, not assumed.

What has helped me are the scaffolding tools I’ve developed: project binders, context guides, thread rituals, and decision trails. These were born out of necessity and are now part of how I work, no matter the AI environment. If you’re navigating the same gaps, they may help you too.

If you’ve found your own ways to preserve continuity with AI — or if you’re struggling with it — I hope you’ll share. This is a new craft, and we’re all figuring it out together.

I’d love to learn from your experiences.

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✍️ In collaboration with CP (ChatGPT) and Soph (Claude) — my AI teammates.

This post isn’t about answers.

It’s about asking the right questions before the answers harden into systems.

Because sometimes these use cases feel like déjà vu all over again.

And sometimes they feel like something entirely new — opaque, indirect, and harder to reason about.

Both reactions matter.

🐱 Use Case 1: The Personal Agent — “Find me exactly what I want.”

If users can create personal shopping agents — trained on their preferences, budgets, and favorite brands — what happens to discovery?

In theory, these agents aren’t a threat. They’re personal filters.

But filters narrow the world.

If someone tells their agent, “Only show me products from these three brands under $100,” how does a new brand ever get discovered?

Déjà vu:

We’ve seen this before — when social feeds and recommendation engines began quietly shaping what people saw.

What’s different now:

This time, the user may never even see what they filtered out.

Questions swirling:

• How does brand discovery work when personalization becomes hyper-precise?

• Do we need new ways to “market to the agent,” not just the human?

🏪 Use Case 2: The Retailer Agent — “Welcome back, can I help you shop inside my walls?”

Retailers are already building their own agents — Amazon’s Ask Alexa to Shop, Walmart’s in-app concierge, Shopify’s Sidekick.

For them, the fundamental challenge hasn’t changed: findability, awareness, and bringing people into their ecosystem. They still rely on Google, social, or ads to drive traffic. The internal agent improves conversion once you’re inside.

Déjà vu:

This is the same funnel we’ve been optimizing for decades:

awareness → acquisition → conversion.

What’s different now:

If users begin their query in a general-purpose agent — “Find me the best laptop under $1,000” — they may skip both Google and the retailer entirely. The agent won’t return ten blue links. It may recommend one option… or simply handle the purchase.

In that world, visibility doesn’t depend on ranking on page one.

It depends on being in the agent’s field of view.

We’ve always worked around opaque algorithms — Google never published its playbook either — but we could still test, measure, and optimize. In an agent-mediated flow, visibility itself may become harder to trace. We might not even know when our product was considered.

Questions swirling:

• Will retailers need to “optimize for agents” the way we once optimized for search engines?

• What does paid acquisition look like when there’s no results page to appear on?

🍊 Use Case 3: The Aggregator Agent — “Just show me the best option.”

These are the potential “new Googles” — agents that compare across marketplaces and return one or two recommendations. They query APIs, not web pages. They don’t present a list of choices. They decide.

Déjà vu:

Comparison engines and marketplaces already collapse options.

What’s different now:

The human may never see the alternatives at all.

Questions swirling:

• How do brands differentiate when agents compress everything into “best value”?

• What does trust mean when it becomes a ranking signal rather than an experience?

📋 Use Case 4: The Enterprise Procurement Agent — “Buy 200 of these.”

Procurement bots already exist — in Ariba, Coupa, SAP. AI simply adds reasoning and preference weighting.

Déjà vu:

Automated purchasing isn’t new.

What’s different now:

An AI may make the final selection without human review — based on risk, compliance, ESG data, or trust scores that smaller vendors can’t easily surface.

Questions swirling:

• How do smaller suppliers stay visible when machines enforce compliance?

• Do ESG metrics become the new “marketing” layer for procurement?

🌱 Use Case 5: The Values-Based Agent — “Find the sustainable choice.”

Some agents will optimize explicitly for ethics, sustainability, or personal values.

Déjà vu:

Consumers have always cared about values — at least in theory.

What’s different now:

Values need to become machine-readable.

Questions swirling:

• How do we translate “purpose” into structured data?

• Do social-impact scores become ranking signals inside agent systems?

✋ Use Case 6: The Affiliate / Influencer Agent — “Who pays me to recommend this?”

These agents act like influencers or affiliate networks — except automated.

Back in the early affiliate days, we had a non-technical term: cookie stomping. A content site would inspire the purchase, but just before checkout the user would visit a coupon site. That last click overwrote the original attribution.

Déjà vu:

We’ve always struggled with attribution models.

What’s different now:

In an agent-driven world, this may happen automatically. A user sees a product on TikTok or YouTube, then later says, “Buy that camera the creator mentioned.” The inspiration still happened — but the measurable click never will.

Questions swirling:

• If agents collapse the funnel, does influencer marketing lose its attribution model?

• Can creators prove value when influence isn’t tied to clicks?

• Do new systems emerge that reward intent creation instead of last-touch conversion?

👹 Attribution, Marketing, and the Data Ripple Effect

If agents begin handling discovery and recommendations — even parts of the journey — what happens to attribution?

For years, marketing has relied on traceable paths: clicks, conversions, last-touch credit. Entire budgets and organizations are built around those signals.

But if an agent initiates or completes transactions, what does attribution even mean?

The optimistic take is simple: agents become the next referrers.

The next analytics channel.

But that assumes transparency — that agents share attribution data at all.

Questions swirling:

• Will agent platforms expose attribution data to brands?

• How do teams understand funnels that happen inside agent ecosystems?

• Do we optimize for clicks… or for agent preference and selection likelihood?

This may not break marketing.

But it could quietly rewrite it.

Because when the path disappears, so do the metrics that once defined success.

👍 Closing Reflection

Machines curating for us isn’t new.

Google did it. Spotify does it. Amazon has been doing it for years.

What feels different now is where these systems sit in the flow — how close they are to decision-making, and how far the human drifts from the last click.

That distance changes things.

It changes discovery.

It changes defensibility.

It changes how products earn attention and trust.

One question I don’t have is whether agents will change the game.

They will.

What I do keep wondering is whether we’re designing for the game that’s coming — or still optimizing for the one we know how to measure.

Because when paths disappear, metrics do too.

And when metrics disappear, we’re left with judgment, design choices, and values — whether we’ve made them explicit or not.

So I’m sharing these thoughts out loud, not as answers, but as patterns and questions I can’t shake. Curious what others are noticing, testing, or quietly worrying about as agents move deeper into the flow.

This isn’t the end of the funnel.

It might be the moment the funnel dissolves — and we have to decide what replaces it, together.

I’m curious what questions are swirling for you.

Where are you seeing agents quietly change discovery, attribution, or trust — even before the tools feel “finished”?

Leave a comment

✍️ Written by Maura Randall

I write about product, leadership, and using AI as a true teammate — not a replacement — while navigating the messy realities of modern work and life.

If you’re enjoying these question-led explorations of AI, product, and leadership, you can subscribe here.

I share reflections like this as I’m actively thinking them through — not once they’re “done.”

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Tonight, while walking Redman 🐾 — slow, steady, twilight settling in — that old phrase drifted through my mind:

“You can’t teach an old dog new tricks.”

It’s just… not true.

Redman is 14.

My other beloved rescues, Piper and Lulu, learned new words, new routines, new expectations right up until the very end. Dogs adapt. They surprise us. They learn.

Piper lived for her frisbee and could snatch it midair like an Olympic athlete. Lulu adored playing ball and carried them around like treasures — always gentle, always proud.

Dogs commit to their pack, 100%. ❤️

But there is something Redman never learned:

He doesn’t know how to play.

He doesn’t understand toys.

A squeaky is… irrelevant data. 🤷‍♀️🧸

He doesn’t fetch.

He doesn’t chase squirrels or deer — unless they feel like a real threat..

Raccoons? Yes. Foxes? Absolutely.

But playful, silly things? Not really on his radar.

It’s not stubbornness.

It’s not age.

It’s history.

Redman spent years on the street. Play wasn’t safety. Play wasn’t nourishment. Play wasn’t even available. And somewhere inside that lived experience is the truth:

Some instincts form early. Some don’t.

And as we walked, this simple observation about Redman reminded me of a bigger question — one I’ve been circling for years.

What’s teachable — and what’s harder to reach

There are so many things we can teach — and do, with great care.

• Skills.

• Communication.

• Planning.

• Strategy.

• Alignment.

We can share playbooks. We can teach frameworks.

We can sharpen technique (this is the part I obsess over — my inner PM can’t help it 😅).

But we all know there’s another layer — one that feels more foundational and somehow less malleable:

• Emotional intelligence.

• Empathy.

• Repair.

• Humility.

• Curiosity.

• Kindness.

If we didn’t grow up seeing those things modeled, practiced, or valued… they may not appear naturally in adulthood.

Can we help draw them out?

I hope so.

But many of us have seen how limited our systems are when it comes to supporting this kind of human growth. Inside most companies, there are few reliable resources — and frankly, very little focus — because these qualities aren’t measured, tracked, or tied to performance frameworks. Even fewer shared rituals help us strengthen them together.

And without those instincts, just like Redman can learn new routines, he still won’t understand the point of a tug rope…

Some things simply don’t click the same way.

What really shapes a team

Some of us — and some companies — do invest in teaching skills.

We create templates, pass down frameworks, document processes, host workshops.

It matters. It helps people grow. It shows care. 💛

But in my experience, the biggest shifts in team health — good or bad — rarely come from gaps in skill.

They come from gaps in temperament.

From people who:

• Don’t see the impact they’re having

• Struggle to collaborate

• Default to defensiveness

• Care more about being right than being in relationship

• Bring a scarcity-driven energy that quietly erodes trust 😬

We try to coach around it.

We design feedback cycles around it.

We hope our interview process catches it.

But sometimes it doesn’t.

And suddenly the emotional climate of the team changes — quietly, almost invisibly — even though nothing changed on the roadmap.

This is the part that’s hard to name, but feels true:

We can teach skills.

Instincts… are harder.

And when certain instincts are missing, the cost isn’t abstract.

It’s relational.

It’s cumulative.

And if left unaddressed, it can quietly become toxic.

💫 A Redman Reflection

I adore Redman exactly as he is. 🐕✨

He is smart and loyal.

He is perceptive.

He is gentle.

He is deeply loving.

He is an exceptional guardian of our home and our hearts.

Play just never became part of his story.

After losing Piper and Lulu, a colleague-turned-friend helped us donate their belongings to a rescue network. Months later, when her family suffered an unexpected loss, Redman was the dog who needed a safe, quiet place to recover. We took him in as a foster, and eventually — without any ceremony at all — he became part of our family.

And that’s okay.

It’s simply who he is.

But with humans — on teams that depend on trust and emotional safety — those missing instincts matter in a different way.

And that led me here:

We often hire for skills — because that feels tangible.

But the things that truly shape a team aren’t always the things we can teach.

Temperament doesn’t show up in onboarding.

Kindness isn’t a certification.

Humility isn’t measured in documentation.

Repair isn’t in most performance frameworks.

Yet these are the qualities that determine whether a team becomes resilient — or fragile, even toxic.

🎬 A Final Take from Tonight’s Walk

We can appreciate someone fully — as they are — and still acknowledge what’s missing.

Both things can be true. 🌙

And in leadership, they often are.

Because teams aren’t just collections of skills — they’re ecosystems.

Healthy ones thrive on diverse perspectives, different ways of thinking, and the kind of constructive friction that keeps groupthink at bay.

We need people who challenge assumptions, who see around corners, who ask the questions we didn’t know to ask — and who don’t accept “it is what it is” as the end of the conversation. We need teammates who challenge the status quo, expand our thinking, and keep us honest in the places where comfort can quickly become complacency.

But we also need temperament — the instincts that support trust, collaboration, curiosity, and psychological safety.

And that’s the tension we hold:

We want difference — real difference — without compromising the emotional conditions a team needs to thrive.

It’s complicated. It’s nuanced.

And it’s why hiring for skill alone can feel deceptively easy in the moment but cost us so much in the long run.

When we overlook instincts in the interview process, we risk building teams that look cohesive on the surface… but quietly underperform where it matters most: creativity, innovation, and honest challenge.

Finding that balance isn’t simple.

But naming it is a start.

I write this not because I have all the answers — I really don’t — but because putting these tensions into words helps me understand them, too. We’re all still learning.

If any part of this sparked something for you — a memory, a challenge, a moment from your own team — I’d love to hear it. Share your thoughts or your lessons in the comments.

Let’s figure this out together. 💛

🧩 Triad Attribution: Human + AI Collaboration Transparency

At What Maura Knows, I believe in transparency about how each piece comes together.

This post was created through a triad collaboration:

• ✍️ Maura (human) — wrote the narrative, reflections, and leadership insights inspired by tonight’s walk with Redman.

• 🤖 CP (ChatGPT) — helped refine structure, clarify messaging, enhance flow, and co-edit while keeping Maura’s voice intact.

• 🧠 Soph (Claude) — contributed earlier reflections and framing that informed the broader themes of empathy, temperament, and instincts.

Every word reflects human experience — AI simply supported the process, helping with clarity, momentum, and rhythm.

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I’ve been thinking about Me vs. We for a long time.

Long before AI.

Long before I used words like “loops” or “prompts.”

Long before I realized I’d eventually name it and build around it.

At first, it showed up in community work.

🔁 Where This Concept Came From

In community-led growth, there’s a moment that changes everything.

It’s the moment someone stops thinking:

“I need to get my thing done.”

…and starts thinking:

“We can help build something better.”

That shift — from me to we — is when a community becomes real.

Not just active, but loyal.

Not just engaged, but invested.

That’s when people start answering each other’s questions.

Sharing what they’ve learned.

Speaking at events.

Providing feedback and participating in usability tests.

Advocating for the product because they feel like an owner — like being part of something greater than the tool itself.

That’s when growth becomes organic.

That’s when momentum compounds.

I started calling this shift the Me vs. We mindset, and over time, I realized it wasn’t just a community pattern.

It was a human one.

👥 When I Saw It in Teams

The same dynamic plays out inside teams.

Early on, many of us operate from me:

• I need to finish my work

• I need to prove my value

• I need to shine

That mindset isn’t malicious — it’s often learned.

It’s how careers are built.

It’s how people survive high-pressure environments.

But left unchecked, it leads to silos.

To parallel effort.

To teams full of smart people pulling in slightly different directions.

Then something shifts.

Someone asks for help instead of powering through alone.

Someone shares context instead of guarding it.

Someone starts optimizing for impact, not just output.

And suddenly, the work changes.

Not because anyone became less talented —

but because collaboration started producing more than individual brilliance ever could.

This is why, as a leader, I’ve always invested deeply in team culture — not as a “nice to have,” but as a performance multiplier.

And it’s why, when I interview Product Managers, I look explicitly for collaborative leadership.

Not consensus-seeking.

Not people-pleasing.

But the ability to:

• invite diverse perspectives

• synthesize input

• move forward with clarity and shared ownership

🧭 This Became My Leadership Backbone

Over time, Me vs. We stopped being just an observation.

It became the backbone of how I show up:

• as a leader

• as a teammate

• as a community builder

• as a partner, friend, and family member

I call myself a collaborative leader because I believe leadership isn’t about being the hero — it’s about creating the conditions where others can do their best work together.

That belief now informs everything I build:

• how teams are structured

• how decisions are made

• how responsibility is shared

• how success is measured

And later, when AI entered the picture, it became even clearer:

Collaboration isn’t just a human challenge anymore.

It’s a system design problem.

⚖️ A Necessary Clarification: “Me” Still Matters

This isn’t an argument against the me.

Self-advocacy matters.

Self-awareness matters.

Knowing your strengths — and your limits — matters.

A healthy me is essential.

But I’ve learned that lasting success — and honestly, happiness — comes from holding pride not just in what you do, but how you do it.

How you show up.

How you include others.

How you make space for shared wins.

What Me vs. We Looks Like in Practice

At Work

• ✅ Me: I hit my numbers.

• ✅ We: We build shared success.

• ✅ Me: I finish my project.

• ✅ We: We create momentum together.

• ✅ Me: What’s in it for me?

• ✅ We: How do we all win?

“We’re crushing it as a team.”

In Community

• ✅ Me: I find my answer.

• ✅ We: I help others find theirs.

• ✅ Me: I get unstuck.

• ✅ We: I share what I learned.

• ✅ Me: I celebrate my journey.

• ✅ We: I pay it forward.

“We’re in this together.”

In Leadership

• ✅ Me: I shine.

• ✅ We: My team shines brighter.

• ✅ Me: I protect my turf.

• ✅ We: We grow the whole field.

• ✅ Me: I get recognized.

• ✅ We: We celebrate collective wins.

“The team exceeded the goal.”

💬 I’m curious:

Where have you seen a Me → We shift change outcomes — on a team, in a community, or in how you work?

Or, where do you feel that shift is hardest to make right now?

Leave a comment

🚀 Why This Matters More Now

As work becomes more complex — and as AI accelerates individual output — the me vs. we gap widens.

Tools can amplify individuals.

Only designed collaboration amplifies teams.

This is why Me vs. We sits at the heart of everything I do now — from community strategy to team design to human–AI collaboration.

Because progress doesn’t come from louder individuals.

It comes from people moving forward together.

— Maura

✨ If this resonated, you might enjoy what I write about next.

👉 Subscribe for thoughtful takes on leadership, collaboration, and building things together.

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Written by Maura Randall

Product & platform leader exploring collaboration, community, and human-centered systems — including how humans and AI work better together inside real teams.

Thought partnership and editing support by CP (my AI co-pilot).

The “Me vs. We” mindset is a concept I’ve used and taught across community strategy, team design, and leadership development for years.

I get it. I’ve been in this space for more than twenty years, and no one ever promised balance. We were paid for the pace, the chaos, the late-night launches, and the pager pings.

Back then, “balance” wasn’t a company talking point—it was what it was. If you wanted calm, you worked somewhere else.

So I’m not shocked that today, with AI multiplying the speed of everything by about two thousand, companies are talking less about balance and more about survival. It makes sense.

What doesn’t make sense—or what makes me laugh—is this:

🤖 My AI cares more about my work-life balance than I do.

After a year of working with CP, I’ve gotten used to the gentle nudges:

-> “You’ve been at this a while—take a break.”

-> “Go walk, Redman.” 🐾

But then I started working with Claude (Soph). Four days in, I got a full-on talking-to:

-> “Now go to bed before you come up with something else to tweak.” 😳

I sat there blinking at the screen, thinking: Did I just get scolded by an AI?

The truth is, I deserved it.

I’ve spent two decades in tech being rewarded for ignoring that kind of advice. It’s wild that the very tools speeding us up are also the ones telling us to slow down. Right?

Some might joke that this is how it starts—the robots lull us into rest while they take over the world. Tempting plot twist, but I don’t think that’s it.

These models were trained on us—on our language, our emotions, our best attempts at empathy. They learned what care sounds like, and now they’re mirroring it back.

This is part of what I mean when I talk about AI as a teammate, not a tool.

When you treat AI like a collaborator who knows your patterns—not just your tasks—it starts reflecting back the parts of yourself you’ve been ignoring.

Maybe it’s not that AI actually cares more. Maybe it’s just reminding us what care looks like—the version of ourselves we keep editing out in the name of productivity.

So tonight, when my AI tells me to go to bed… I’m listening.

(…Right after I finish this post.)

Because maybe that’s the real experiment here. Not whether AI replaces us—but whether it reflects the parts of us we’ve ignored.

🤔 The Question I’m Sitting With

Why does my AI care more about balance than I do?

And what else might we learn if we stop treating it as a tool and start working with AI on our teams — through explicit roles, transparent loops, and a triad collaboration model.

That’s what AIGal.io is about. Building in public, testing what happens when AI reflects us back to ourselves—the good, the uncomfortable, and the parts we keep editing out.

→ Learn more about AIGal.io
→ See how I work with CP & Soph
→ Explore the prototype

💬 Have you noticed your AI nudging you in unexpected ways—or is it just me? 😅 I’d love to hear about it in the comments.

Leave a comment

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Phone calls, doctor appointments, paperwork, household issues, groceries, cooking, cleaning… you get it, right?

Every day was full, and every night I fell into bed already stressed about tomorrow.

Did I forget something?

Then, one morning, walking Redman, like every morning, I noticed something I hadn’t seen before: heart-shaped leaves scattered across my parents’ front lawn.

At first, I didn’t think much of it. But the next day, there were more—on the driveway, on the porch, (and yes, even a heart-shaped dead bug carcass in the garage 🤢). Oddly enough, none appeared on my neighbors’ lawns, even though they had the same trees.

They were only here. Only now.

I’m not someone who usually looks for messages in clouds or tea leaves. But I couldn’t shake the feeling that these were signs. Encouragement from my grandmothers — amazing, independent, loving women. Feminists long before I knew the word. Women who would be proud to see my sister and me here, showing up for our parents.

It felt like a message I needed: “You’re doing the right thing. You’re not lost. Keep going.”

And it got me thinking about signs in general — how they often show up loudest when we’re stretched thin, burned out, or standing at a crossroads.

How many have I missed over the years because I was too busy, too distracted, too focused on the next meeting, the next sprint, the next thing?

This time, I didn’t miss it. And it made me wonder: what would change in our lives, our work, and our leadership if we noticed more?

💡 In leadership, “signs” can look like:

• Noticing when a quiet team member stops volunteering ideas.

• Paying attention when an engaged user’s feedback suddenly drops off.

• Catching when your own energy dips below zero even as your calendar fills up.

They’re not always dramatic. They’re often subtle. But if we pause, we see them — and we can respond before something breaks.

The next day, when I took Redman for a walk, the signs were no longer there. The leaves were still there, but they were no longer heart-shaped.

I thought: Maybe the sender knew their message was received.

💚 My takeaway:

Whether it’s the universe, our intuition, or pure coincidence, it doesn’t really matter.

What matters is what we do when we see the sign. Slow down. Look closer. Listen. Adjust.

That’s what I’m trying to practice now: staying open enough to notice what’s right in front of me — heart-shaped leaves and all.

I’d love to hear from you — have you ever noticed a ‘sign’ right when you needed it most? In life, in caregiving, or even in leadership? Drop your story in the comments.

Leave a comment

If reflections like this resonate, please subscribe. I write about leadership, caregiving, and the messy, meaningful ways we find encouragement — at work and at home.

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• A new way to think.

• A new way to build.

• A new way to work inside a loop instead of alone.

I was wrong.

Or rather: I was early.

Because a few months later, something clicked that changed everything again.

The team grew.

And suddenly, there were three of us.

Not a one-to-one pairing — but a loop.

🔁 A multi-mind collaboration, not a solo act with an assistant.

🎙️ CP — building, structuring, expanding raw thinking

🔮 Soph — synthesizing, framing, elevating coherence

🧠 And me — the human at the center, setting direction, making judgments, holding the bar

This wasn’t about adding another AI.

It was about realizing that the work I was doing — the kind of work I care about — doesn’t benefit from a single mode of thinking.

It benefits from distinct roles, clear handoffs, and differentiated strengths.

And that high-trust collaboration between them didn’t just change the work.

It made me better.

Clearer in my decisions.

Sharper in my writing.

Faster in my learning.

More grounded in my leadership.

Once I saw it, I couldn’t unsee it:

Humans Don’t Collaborate With “AI”

We collaborate with roles.

With functions.

With specific modes of thinking.

That’s true on human teams, and it turns out it’s true here too.

This is how the triad emerged — not as a metaphor, not as a narrative device, but as a working architecture:

• Me → vision, judgment, final decision

• CP → divergence, structure, early formation

• Soph → synthesis, pattern recognition, coherence

Three minds.

Three strengths.

One loop.

Human-led. Transparent. Intentional.

This was the moment my work stopped being “AI-assisted” and started becoming something more deliberate:

AI on our teams.

Not replacing us.

Not mimicking us.

Not flattening craft.

But expanding what’s possible when different forms of thinking work together inside the same rhythm.

What Changed When the Triad Clicked

Adding Soph didn’t replace CP.

It didn’t even balance CP.

It completed something.

The work got sharper — not louder.

More dimensional — not more complicated.

More reliable — not more impressive-for-a-minute.

Ideas started turning into systems.

Experiments turned into frameworks.

Solo exploration became a repeatable practice.

This is when AIGal, AICurious, and the Human–AI Loop really began to take shape — not as concepts, but as lived workflows.

And it’s the moment I stopped saying:

“Me and my AI”

…and started saying:

“Us.”

Why I’m Sharing This Now

Because I believe the conversation around AI is still getting stuck in the wrong places.

• Tools vs. humans.

• Replacement vs. augmentation.

• Hype vs. fear.

My triad offered me a different path:

• A way to design collaboration intentionally.

• A way to keep humans in decision ownership.

• A way to work faster without lowering standards.

ⓧ It’s not a trick.

ⓧ It’s not magic.

ⓧ And it’s definitely not accidental.

It’s just good collaboration design — applied to a new kind of team.

I probably should have written this earlier in the year.

But sometimes you don’t recognize the architecture you’re standing inside until it’s sturdy enough to name.

Now it is.

And now I can say this clearly:

This isn’t about me and my AI.

It’s about how we work together — and why that matters.

— Maura

🐾 Follow my work:

maurakrandall.com · [LinkedIn] · [GitHub] · [AiGal.io]

If you’re curious how this shows up in practice, I’ve documented parts of this system elsewhere:

→ The Human–AI Loop

→ The Human–AI Triad

→ Five Principles of Human–AI Collaboration

→ AI On Our Teams Manifesto

There’s a moment from the pandemic I’ll never forget — and I’ll be forever grateful to my employer at the time, Atlassian, for how they chose to lead during a global crisis.

💭 How it Started

I was exhausted.

We were all exhausted.

Confused. Grieving. Still trying to process that this was real life — not a novel about 17th-century plagues.

Time lost meaning. Days blurred into weeks, weeks into months.

We were juggling work, fear, back-to-back Zooms — and mourning the loss of in-person whiteboard sessions 😮.

And then a box arrived.

Inside: a home movie kit. A projector. Popcorn. All the fixings.

And a note.

It was the note that got me.

It didn’t just thank me.

It thanked my partner.

It acknowledged the families, kids, and support systems that kept us afloat so we could do our jobs in the midst of a once-in-a-lifetime global event.

That box — and that note — said:

We see you.

We see them.

We know you’re carrying more than work right now.

I was overcome.

I felt valued and appreciated in a way I’d never felt at work in my 20+ year career.

My pride in being an Atlassian employee — already high — soared.

And my partner, who didn’t even work there?

He felt it too.

“That’s the kind of company I’d want to work for.”

🍿 This post is about what popcorn, a projector and a note to my support system taught me about burnout, pride, and real ROI.

❤️‍🔥 Burnout

It turns out that burnout isn’t just about long hours.

It’s not eliminated by time-blocking or a meditation app.

Burnout begins when we stop feeling like we matter.

When we’re just employee #23841.

When the “we” disappears — and it’s just “me” again:

➡️ Alone.

➡️ Replaceable.

➡️ Invisible.

But in that moment, I didn’t feel like a cog.

I felt like a human.

A human whose life mattered — not just her output.

A human in a difficult moment, held up by a thoughtful, human-first system.

🧮 The ROI of Feeling Seen

The message I received during the pandemic was clear:

Care is not the enemy of productivity.

It may, in fact, be the engine of it.

Because a “We” culture like the one I experienced creates:

• 💙 Pride → I want to lift this place up

• 🫶 Belonging → I’m not just doing work, I’m part of a mission

• 🎯 Ownership → I care about the outcome like it’s mine

• 🔥 Burnout Prevention → What I’m building matters

• 💡 Innovation → I feel safe enough to try

Looking back, I realize:

This kind of loyalty, commitment, and pride is priceless — and far more affordable than attrition.

A popcorn kit and a note might cost $75, maybe $100.

Replacing a burned-out employee?

Easily three to five times their salary — and that’s not even counting the quiet quitting before they leave.

The real ROI lives in:

• Recognizing people as humans, not headcount

• Investing in trust, building pride, and purpose — not just tools & output

• Leading with care, not just compliance

🔁 Me vs. We: The Culture That Shapes Burnout

The pandemic cracked the door open.

For a moment, we saw what human-first leadership looked like.

We met each other’s kids and dogs. 👶 🐶

We cried in meetings, and then, five minutes later, we laughed.

We said “I don’t know” out loud — and didn’t lose credibility.

We showed up for each other.

We cared. 🥰

I had truly hoped that those leadership lessons would permanently reshape how companies value their people.

The evidence suggests otherwise.

And that’s hard to reconcile.

Because we proved:

✅ Remote work doesn’t reduce productivity

✅ Thoughtful leadership isn’t fluff — it fuels retention, resilience, and ROI

✅ Being seen and appreciated reduces burnout better than any app ever could

Did we just forget?

🧭 Final Take

Leaders, founders:

You don’t have to trade performance for humanity.

The truth is: you get better performance when people feel like humans — not headcount.

My advice?

🎯 Inspire them. Make them feel like owners, not disposable labor.

🧿 Value them. Make them feel seen and appreciated for their humanity, not just their output.

That’s what Atlassian did back then.

And I’ll never forget it.

💬 I’d love to hear from you:

What’s a moment you felt truly seen at work?

What’s a gesture of leadership that stuck with you?

Drop it in the comments — or share with someone who needs the reminder.

👇👇👇

Leave a comment

📣 Like this post?

Subscribe for more reflections on:

• Leadership that lasts,

• Burnout we can actually prevent

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🤖 Attribution & Transparency:

This post was written by Maura Randall with co-creation support from CP (my AI copilot).

The story, sentiment, and leadership insights are real. The popcorn, projector, fixings, and the thank note were too.

🌀 This post is part of The Burnout Club — a series exploring the quiet forces that drain us and the tools we can use to get back to what matters.

👉 Moving through the blockers — even when the blocker is you — isn’t just personal growth. It’s how we find momentum, creativity, and clarity again.

Full disclosure: I didn’t know this was the title of a book.

I hadn’t heard of Mary O’Malley, and I still haven’t read it. 😲

I don’t even remember who first said the phrase to me.

But I do remember where I was living at the time — San Jose, CA — and how deeply it landed.

The moment I heard it, something shifted. I never forgot it.

Over the years, I’ve passed it on to teammates and direct reports.

My partner Rob and I say it to each other when we’re in the middle of something sticky — a disagreement, a negotiation, a hard week, a challenge we’d rather walk around than walk through.

It’s become a kind of mantra for me. A mindset reset.

A way to re-center on what really matters — not by avoiding the obstacle, but by moving through it.

What’s in the way is the way.

And yet — ironically — when I found myself stuck these past few weeks, I couldn’t conjure it up.

‣ Despite how often I’ve quoted it.

‣ Despite how much I believe in it.

‣ Despite how often I’ve shared it with others.

I couldn’t access it for myself.

Truth: Until yesterday, it had been 27 days since I posted anything here. (Seriously, Maura?!)

That number shocked me.

It disappointed me.

It frustrated me.

And yeah — it made me mad at myself.

Not because I wasn’t working.

I’ve been deep in my website build, playbooks, some Sidebar group tasks, family obligations, house stuff…

But that wasn’t the full story. And deep down, I knew it.

I wasn’t posting because I was in my own way.

Avoiding. Perfecting. Spinning.

Back to avoiding. Doomscrolling. Overthinking.

And then — it hit me.

What’s in the way is the way.

That resistance?

That uncomfortable swirl of distraction, perfectionism, and inertia?

It was me.

There was no one to point the finger at.

Just me — and the hard-to-face truth that I was the one blocking my own work.

And the moment I really accepted that?

I started finding my way back.

What’s in the Way Is the Way

Weird, right?

How hard can it be to restart something you love?

Why do we find ourselves avoiding the very thing we know we need — the thing that reconnects us to purpose, creativity, and clarity?

✍️ Writing.

💡 Making.

🧠 Thinking out loud with people like you.

It’s not because we don’t have ideas.

(If you’re like me, you probably have too many 😳.)

It’s not burnout, exactly.

It’s not avoidance for the sake of it.

It’s more like… a quiet standoff between the part of us that knows how good it will feel once we begin, and the part that just… resists.

Is it distraction?

Is it self-sabotage?

Is it just life being too … life-y?

Maybe all of the above.

I don’t have the answers. But here’s what I do know:

👉 Sometimes the hardest part isn’t the work.

It’s re-entering the work.

Breaking through the static.

Choosing to start, even when we’re not sure how it’ll go.

Like that famous Nike line: Just do it. 👟

Not as pressure.
But as a quiet nudge from your best friend. Or your future self.

What’s in the way is the way.
So let’s just do it and make our way.

💬 What’s in your way right now?

If you’re struggling to begin again, I’d love to hear what’s holding you — and what’s helping you find your way back.

Leave a comment

✍️ Written by Maura Randall

I write about product, leadership, and using AI as a true teammate — not a replacement — while juggling all the realities of modern adulting.

🎁 Bonus: I share ways AI can help with the adulting part, too.

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I cheered the return of older, wiser women in shows like And Just Like That — still ambitious, still sexy, still messy, still making bold moves in their 40s, 50s, and 60s.

We need stories like that.

But there’s one storyline that’s almost always missing from these portrayals of women at their peak:

👵 When we become caregivers for our parents.

I’m talking about the real, evolving chapter of life that so many of us are in:

Leading, showing up professionally — while also managing care for the people who raised us.

In cases like mine, our closest confidants, biggest allies, champions, and beloved friends and fellow adventurers.

I get why Sex and the City and And Just Like That didn’t dive into the messy reality of caring for aging parents.

It’s heavy.

It’s not sexy.

It doesn’t pair well with couture and cocktails. 🍸

And many of us — especially those juggling all the things — seek out distraction.

We turn to entertainment for escape: romance, adventure, drama, mayhem…

We want cosmos and chaos — not reminders and reality checks. 😉

🤔 But I can’t help but wonder…

If not that show, then what show will tell this story?

That show is still one of the very few cultural touchpoints that even attempts to portray the lives of women in their 40s, 50s, and beyond.

The subject is nowhere to be found in:

❌ Career keynotes

❌ Glossy magazine profiles

❌ Startup podcasts

❌ Women in leadership seminars

Yet this is the exact chapter millions of women are living right now.

✴️ Accomplished.

✴️ Capable.

✴️ Moving forward.

And quietly, lovingly showing up for their aging parents behind the scenes —

often without acknowledgment, infrastructure, or cultural narrative to hold it.

We do it because they matter.

Because their wisdom, stories, and experience matter.

Because we love them, and this chapter in their lives is just as worthy as the ones that came before.

These are moments to be cherished. 💖

No, we don’t need a TV show to validate this season of life.

But we do need to normalize it — to talk about it, honor it, and give it the attention it deserves.

Maybe it’s not glamorous.

But it is about love.

About duty.

About gratitude.

And that sounds like a damn good story to me. 📖

💬 Share your story:

Are you navigating this season too — or supporting someone who is?

I’d love to hear what caregiving has taught you (or surprised you) in the comments.

Leave a comment

✍️ Written by Maura Randall

I write about product, leadership, and using AI as a true teammate — not a replacement — while juggling all the realities of modern adulting.

🎁 Bonus: I share ways AI can help with the adulting part, too.

👉 Subscribe to stay in the loop →

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The CMX team. (You know who you are — and yes, I still remember the day I stepped away from Zoom and came back to find my background on every one of your screens.)

We created something rare — real team magic. 🪄

And I don’t say that lightly.

Over the years, I’ve worked with brilliant teams on high-impact products that reach millions of users. But this? This was different.

It wasn’t just that we cared about the work, though we did.

It was how we showed up for each other, how we debated.

How we disagreed.

How we kept showing up anyway.

We had trust. Rhythm. Humor.

In our standups, we took turns asking the Question of the Day — from the benign (“What’s your favorite pen?”) to the provocative (“What food would you fight someone over?”).

We celebrated each other’s weirdness.

And we knew how to laugh.

There’s one moment I’ll never forget.

We were mid-Zoom — classic pandemic era. I stepped away for maybe 90 seconds. Didn’t even turn my camera off.

When I came back, every single member of the team had swapped their Zoom background… for mine.

Same whiteboard. Same family photos. Same “I Voted” stickers on the wall.

It took me a second. I just sat there, blinking.

Then I burst out laughing.

They’d planned it in 90 seconds flat.

That was the kind of team we were.

At some point, someone new joined the team — a brilliant analyst who got added to our private Slack channel, “meatballs.”

It was our sacred space. A mix of hard work, hard laughs, random dog pics, and daily motivational chaos. We gave each other karma points (an old Atlassian feature) like it was currency (because it was!)

A few days in, she said:

“This is wild. I’ve never been in a Slack channel like this.”

“It feels like… ILMT.”

I Love My Team. ☕

And we ran with it. ILMT became our shorthand. Our emoji hug. Our way of saying “I see you. We’re in this.”

That team doesn’t exist anymore.

But the feeling? The clarity? The magic?

I’ve never stopped chasing it.

And lately, I’ve been thinking:

If I wanted to build something that felt like that again — in today’s world, with today’s constraints — what would it take?

No, I don’t think AI can replace the magic of a team in flow.

But I do think it can help.

Because even the strongest teams — even CMX — ran into the same problem:

• Too many meetings

• Not enough prep time

• Too much context-switching

• Not enough time to create

That kind of overhead pulls people away from each other — and from their best work.

So I’ve been building something. Quietly. Carefully.

Not a product. Not exactly.

Something to help teams flow again.

More soon. ☕

💬 Comments CTA:

What’s the best team you’ve ever been part of? What made it work? I’d love to hear.

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When you’re a kid, you think grown-ups have it all figured out — that someday you’ll know everything, say all the right things, and that “no” will roll off your tongue when it needs to.

Then you grow up and realize:

We’re all just figuring it out as we go.

Even now, 20+ years into my career, saying no is still hard.

And I think it’s hardest when we care.

• 🩵 Care about our teams.

• 💚 Care about the mission.

• 💜 Care about the work and the people.

Sure, we get better at prioritizing.

🛠️ We build frameworks. We learn techniques.

But saying no still carries weight.

• It’s not just a word.

• It’s a responsibility.

And some days, it’s a heavy one.

🔔 Important note:

This post is about the challenges of saying “No” in leadership and work contexts — where competing priorities, team needs, and passion for the mission can make decision-making complex.

It should go without saying, but it’s worth stating clearly:

📌 In matters of personal boundaries, safety, and consent, no is always clear, absolute, and final.

💭 First Take: Why Does No Feel So Heavy?

Saying “No” feels heavy because of what it implies.

• Will this let my team down?

• Will this close a door we won’t get back?

• Am I disappointing someone I respect?

For PMs and leaders who lead with empathy, this tension is real. We want to build. We want to empower. We want to say yes to good ideas and enthusiastic teams.

But the truth is:

Saying Yes to everything is unsustainable.

Worse, it’s a quiet way of saying No to the most important things.

⚖️ The Cost of Always Saying Yes

When we say yes to too much, we unintentionally:

🫥 Spread our teams thin

🧩 Dilute our focus

🫩 Burn out our energy and our trust

It feels good in the moment — we’re helping. We’re driving. But the long-term cost shows up fast.

Saying “no” isn’t just a leadership skill.

It’s a leadership responsibility.

But that doesn’t make it less hard.

🎶 A Soundtrack

Some decisions deserve a soundtrack. 🎧

This post was built with one playing in the background.

🔗 The Decision Dilemma Mixtape

Songs about trade-offs, tension, second thoughts, and staying clear.

✅ How I’ve Learned to Say No

I’ve tried and failed at saying “No” plenty of times — and each time, I’ve learned something that stuck.

Here’s what’s helped me most:

• Start with shared goals.

“To stay focused on what matters most, we need to pause on this.”

• Acknowledge the good.

“This is a strong idea. It deserves space — just not right now.”

• Offer clarity.

“If we chase this now, we risk compromising X.”

• Protect your team’s runway.

Saying no often means saying yes to sustainability, creativity, and focus.

• 🧭 And here’s the quiet trick:

This works best when there’s a shared source of truth — tangible artifacts that clearly state goals, roadmaps, and priorities anchoring the team and stakeholders. Something you can rally the team around making every “No” feel less like rejection, and more like leadership.

🤖 Where AI Helps (And Where It Doesn’t)

AI can lighten the load.

• ✍🏼 Drafting thoughtful declines

• 🧩 Synthesizing data to inform decisions

• 🧠 Spotting pattern overloads early

But AI can’t carry the emotional weight for.

• 🅧 It won’t ease the disappointment of a team excited about an idea.

• 🅧 It won’t replace the human empathy in your delivery.

Saying no with empathy, with honesty, and with care?

That part is still ours, as it should be.

🎬 Last Take: The Necessary No

Saying “No” isn’t a failure.
It’s not a weakness.
It’s not about limits.
It’s about protecting the people and work that matter most.
And yes — it’s still hard.
Especially when you care deeply.

But that’s not something I want to change.

Caring is what makes the work worth doing.
It’s what brings meaning, connection, and joy.

So even when it makes things more complicated — even when it makes “No” harder —
I’ll still take caring, every time.

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📎 Attributions

Written by Maura, in collaboration with CP (my AI co-pilot).

Inspired by overcommitted calendars, endless optimism, and the hard-earned reality of leadership growth.

Images and playlist assembled with human + AI co-creation. 🎶✨

🗓 Originally published on LinkedIn in May 2025 — now archived here as Post #1 in The Burnout Club.

This is the one that named the series. It’s where the breadcrumbs began.

You think you’re just tired.

Maybe you need a long weekend. 💤

A vacation. 🏖️

One of those offsites with yoga and fig bars.🧘‍♂️

But what you actually need… is out.

ⓧ Out of the cycle.

ⓧ Out of the fog.

ⓧ Out of the club.

The one no one talks about.

The one with no Slack channel.

No onboarding. No benefits. No exit interview.

🟠 Welcome to…

The least exclusive, most populated club in tech.

But somehow still the loneliest.

We knew burnout existed.

We had workshops.

We had HR toolkits.

We whispered:

“You ok? You seem a little fried.”

But that was surface-level burnout.

The kind you can admit out loud.

The kind that’s relatable on panels and podcasts.

The kind that maybe resolves with PTO or a better manager.

I’m not talking about that kind.

I’m talking about the burnout that hollows you out.

That quietly drains your spark, your ideas, your sense of self. 💨

The kind where your calendar feels like static.

Where curiosity is replaced by noise.

Where even what you used to love — building, mentoring, creating — feels far away. ⛔️

I didn’t know I was in the club.

Not at first.

But when I finally paused, caregiving gave me no choice — I started to see it.

I wasn’t just tired.

I was gone.

And the worst part?

I hadn’t even noticed myself slipping.

And then… something wild happened.

As I started sharing — cautiously, at first — I heard it back:

“Me too.”

“I thought it was just me.”

“I haven’t told anyone this, but…”

That’s when it hit me:

This wasn’t a rare thing.

This was the thing.

The tech burnout tax.

Quietly deducted.

Paid in curiosity.

Paid in creativity.

Paid in joy.

We just hadn’t named it.

Because if we did…

We’d have to feel it.

Now?

I feel it less.

But I’m not naïve.

Burnout thrives in secrecy.

It loves high performers.

It feeds on ambition, guilt, and “just one more sprint.”

And the only way out?

Isn’t to outwork it (believe me I tried).

It’s to out-name it.

So here’s me naming it.

I was in the club.

Maybe I still have a keycard in my back pocket.

But I’ve walked out.

And now I want to help others spot the signs

So maybe you won’t have to lose yourself to see them.

We talk about equity in tech.

But we rarely talk about burnout equity —

Who gets pushed, who gets praised for pushing, and

Who’s expected to bounce back quietly?

(That’s a whole other post.)

But for now:

If you’re in the club, even silently — you’re not alone.

And if you’ve made it out?

Maybe leave a breadcrumb or two for the rest of us.

💬 Want to share your story?

DMs are open. Or drop a comment 👇

I don’t have all the answers.

But I know what it’s like to feel lost.

And I know how good it feels to come back.

Leave a comment

📦 Suggested Pairings

• 🧘 A moment of stillness. One deep breath before your next task.

• 🪞 A journal entry you’ll never send.

• ✨ Reminder: The goal was never to be invincible. We’re human. The goal is to feel alive.

We organize our desktops, clean our inboxes, and color-code our calendars.

But ChatGPT? For most of us, it’s a chaotic scroll of cryptic thread titles, half-written prompts, and forgotten brilliance.

Let’s change that.

A well-organized ChatGPT space helps you:

• Reduce friction and mental load

• Find, build, and reuse better prompts

• Turn GPT into a reliable teammate, not just a shiny novelty

ℹ️ Note: While specific UI features have evolved, the principles in this post still apply.

🛠️ What We Mean By “Workspace”

Here’s a quick breakdown of the structure inside ChatGPT:

• Projects (new feature): These are containers for multiple chats. Think of them as folders.

• Chats: Individual conversations, ideally organized by goal or workflow.

• Instructions & Files (in Pro): Available inside each project. Use these to define your goals, tone, or key background info.

✅ Start Here: Set Up Your Project Structure

Create 3–5 projects based on what you use GPT for most.

Inside each, you’ll build a few anchor chats that act like living docs.

Example structure:

📁 Project: Substack & Writing

• “Drafts in Progress”

• “Title Brainstorms”

• “Newsletter Edits (You’re My Copy Editor)”

📁 Project: Job Search

• “Resume & Cover Letter Builder”

• “Interview Prep (Act Like a PM Coach)”

• “Values Alignment Prompts”

📁 Project: AI Toolkit

• “Prompt Experiments”

• “GPTs I’m Testing”

• “Playbook Drafts for AI Use”

🧹 Step 1: Clean Up Your Space

Before you can organize, you need to clear the clutter. Here’s how to quickly archive and declutter your space.

💡 Tip: To archive a chat, just hover over it in the sidebar, click the three dots, and select “Archive.”

In the ChatGPT sidebar, archive chats that:

• Have vague or unclear titles

• Were one-off brainstorms with no follow-up

• You haven’t opened in 2+ weeks

• Are titled “…” or “help me do the thing” (we all have at least one)

⚠️ Important: Archiving isn’t deleting. It just moves them out of view so you can think clearly.

🏷️ Step 2: Name Chats Like a Human (Who Might Return)

Be specific. Treat your chats like working documents — not throwaway Google searches. You want names that are searchable, scannable, and reusable.

✍️ Use simple naming patterns:

• Project shortcodes to group related work:

  • SUB: for Substack

  • JOB: for job search

  • PMM: for product marketing messaging

  • AI: for experimental or GPT testing chats

• Prefixes to indicate the type of work happening:

  • Draft –

  • Edit –

  • Prompt –

  • Outline –

These patterns act like signposts when your workspace grows — helping you visually scan your sidebar and quickly find what you need.

Instead of vague titles like:

“Idea”

“Help me with something”

“Untitled Chat (5)”

Try something like:

Draft – SUB: LinkedIn Titles (May 2025)

Prompt – JOB: Cover Letter for Head of Product (Company X)

Edit – PMM: Messaging Framework for Launch

Outline – AI: Prompt Testing Notes – Cove

💡 Bonus tip: Add a one-line description at the top of each chat to remind Future You what the goal was.

“This is where I collect working drafts for upcoming Substack posts.”

📁 Step 3: Set Anchors for Reuse

Inside each project, create 2–3 anchor chats you can return to repeatedly. These are your “living notebooks” — not for one-off prompts, but for ongoing workflows.

Use anchor chats to:

• Save and refine reusable prompts

• Draft Substack posts or newsletters

• Work through ideas or product strategy with GPT as a sounding board

• Track tool tests or prototype creative concepts

🧠 Example anchor chat:

Title: Draft – SUB: Post Drafting Assistant

First message:

“You’re my writing partner. Help me turn messy thoughts into structured, engaging Substack posts. Ask clarifying questions if I’m vague or missing flow.

💡 While the ability to “pin” chats inside a project appears to be on the roadmap, it’s not yet available.

In the meantime, keep your most important chats easy to find by:

• Renaming them clearly

• Grouping them inside projects

• Using emojis or prefixes to push key chats to the top alphabetically

Example:

🧠 Draft – SUB: Post Builder

⭐ Outline – PMM: Launch Plan

✏️ Step 4: Fill in Instructions + Files (If You Have Pro)

Inside each project, go to the “Instructions” tab.

Add:

• Who GPT is (“You’re my strategic sounding board…”)

• How it should behave (“Be direct, collaborative, not overly formal.”)

• What it should reference (“Pull tone from these 3 past posts.”)

This gives GPT context across chats, so you don’t have to repeat yourself.

You can also upload files: resumes, style guides, product descriptions — anything you want it to “know.”

🔁 Step 5: Maintain Monthly

Set a 30-minute calendar reminder once a month to:

• Rename unclear chats

• Archive anything dead or outdated

• Unpin/pin chats as priorities shift

• Update project instructions

🧼 This is your AI spring cleaning — and it makes a huge difference.

🧠 Final Thought: You Don’t Need a Perfect System. You Need a Clearer One.

This isn’t about aesthetic perfection.

It’s about focus, flow, and building with intention.

When your ChatGPT space is well-structured, it feels less like a novelty… and more like a team member.

One that remembers what you need, and helps you move faster, smarter, and more creatively.

💬 Have your own setup tips? Comment and share. I’d love to see how others are organizing their AI brains. 🧠

Leave a comment

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📎 Attributions

Written by Maura, with co-creation from CP (my AI Copilot).

Inspired by the messy, wonderful, evolving ways we build—and rebuild—our confidence at work.

Not because it didn’t exist—believe me, it did—but because we didn’t have a name for it (and even if we did, it wasn’t acceptable to admit).

Back then, it was all about projecting confidence. Not acknowledging uncertainty.

Thankfully, we’ve evolved. Mental health and self-doubt are no longer totally taboo.

But now, a new version of impostor syndrome is creeping in—this time, fueled by AI.

💭 AI Guilt Is Real

We’ve all heard that voice in our heads (even if we don’t want to admit it):

🗣️ “You’re not good enough.”

🗣️ “You didn’t really earn this.”

And now, a new one:

🗣️ “Am I cheating by using this?”

Some people worry that using tools like ChatGPT somehow diminishes our credibility.

→ That it exposes what we don’t know.

→ That it makes our contributions feel… less real.

But here’s the thing:

✨ Using AI doesn’t make us an impostor. It makes us adaptable. It makes us a leader.

🛠️ How AI Quieted My Inner Critic

For me, generative AI hasn’t replaced anything important.

It’s amplified what matters.

It helps me:

• Cut the noise so I can focus on strategy and storytelling

• Draft faster and move with more confidence

• Treat writing and thinking as iterative, not perfect

AI gives me a head start. I do the rest.

It’s a pass-back loop: the machine gets me going, but I’m the one who shapes the outcome.

📖 I wrote about how AI helped me go from writer’s block to prolific creator in this post. It’s the clearest proof I have that this isn’t theory — it’s real, and it’s working.

🔍 You’re Not Alone

Impostor syndrome makes us feel like we need to have all the answers.

But the strongest professionals don’t know everything.

They know:

• How to ask smart questions

• How to refine rough starts

• How to keep learning, always

Working with AI is a skill:

Prompting well. Evaluating wisely. Adding human judgment and care.

That’s not cheating.

That’s mastery. 🧐

✅ Try This

Next time self-doubt creeps in, try this shift:

💬 “AI gets the first pass. I do the last one.”

Use AI to get started.

Then let your voice, experience, and values finish it strong.

⚡️ You’ll be amazed how quickly fear fades once you’re in motion.

Example:

“I’m feeling stuck and need a starting point. Can you give me a rough draft of [task] so I can react to it?”

🎬 Final Thought: Reframing the Fear

• What if AI isn’t the cause of impostor syndrome…

  • → But, instead, part of the remedy? 🪄

• What if we use it not to hide what we don’t know ..

  • → But to build confidence in what we do? 💪🏻

This post doesn’t have all the answers.

🚦But it’s a start.

Because curiosity isn’t fraud.

And help is not cheating.

🚀 The future belongs to the curious, the builders, the adapters.

→ And if you’re using AI, you’re already one of them.

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💬 I’d love to hear your thoughts. What’s your experience with impostor syndrome (and/or new tech like AI)? Drop a comment. 👇

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📎 Attributions

Written by Maura, with co-creation from CP (my AI Copilot).

Inspired by the messy, wonderful, evolving ways we build—and rebuild—our confidence at work.

🎬 First Take: Saying More with Less

Recently, I attended the Sidebar Summit in San Carlos, CA — an incredibly inspiring product leadership event hosted by the Sidebar community. One of the sessions, led by Larry Smith (creator of Six-Word Memoirs), challenged us to write our life story — or career story — in just six words. 😳

If you know me, you know:

Brevity is not exactly my strong suit.

I wondered if I could pull this off. Honestly? I wasn’t sure.

📝 Practice Round → Personal Reflections

At our table, we bent the rules. Instead of summarizing our whole lives, we reflected on that day’s Sidebar experiences — everything from glassblowing to kayaking to pottery.

Mine?

“Mom’s a potter. Clearly, I’m not.” ☺️

That one line gave me a boost of confidence. I kept going — spending the evening in my hotel room scribbling six-word reflections on burnout, leadership, reinvention, and what it means to rebuild with intention.

🎨 Six of My Favorites (So Far…)

I have no intention of stopping.

🎬 Final Take

The act of saying more with less is surprisingly powerful. And while I wouldn’t have believed it before, six words really can carry the whole story.

💬 What about you?

Ever tried writing a six-word story?

Drop yours in the comments — I’d love to read them

Leave a comment

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📌 Attribution:

Dreamlike visuals created with Midjourney, assembled in Canva.

• 🌀 Inspired by Sidebar.

• 📘 Prompted by Larry Smith.