A colleague told me something recently that I keep thinking about.

She said, unprompted, that she appreciated seeing both sides of my AI conversations. Not just the output. The full thread. My prompts, the AI’s responses, the back and forth, the dead ends, the iterations. She said it made her trust me more.

This piece is an example of that. The conversation that produced it exists. A raw transcript would be longer, messier, and significantly less useful than what you’re reading now. What you’re reading is the annotated version, the part where judgment entered the artifact. That’s not a disclaimer. That’s the argument.

I’ve been transparent about using AI in my work from the start. Partly because I wrote a book on data ethics and hiding it felt wrong. Partly because I’ve spent 25 years watching technology adoption go sideways when the human dimension gets treated as an afterthought. But her comment made me realize something more specific was happening when I showed the conversation rather than just the output.

It’s worth unpacking why.

An old problem, a new incarnation

In the 1990s, Harvard Business School professor Dorothy Leonard introduced the concept of “deep smarts” in her book Wellsprings of Knowledge: the experience-based expertise that accumulates over decades of practice, the kind of judgment that lives in people’s heads and doesn’t reduce to documentation. She also introduced a companion concept that has stayed with me: core competency as core rigidity. The very depth that makes expertise valuable also makes it hardest to transfer. Experts often can’t fully articulate what they know because they’ve stopped experiencing it as knowledge. They experience it as just seeing clearly.

Leonard’s work was about organizational knowledge transfer: how companies preserve institutional wisdom when experienced people retire or leave. That’s been a challenge since the first consultant ever billed an hour. What’s different right now is that the tools to actually solve it have arrived simultaneously with the largest demographic wave of executive retirement in American history.

What’s interesting about this particular moment is that the same dynamic is now showing up at the individual level in how practitioners interact with AI. The tacit knowledge at stake isn’t a retiring VP’s intuition. It’s your own judgment, your own expertise, your own hard-won understanding of what a project or organization actually needs. And the question isn’t how to transfer it before you walk out the door. It’s whether you can see it clearly enough to know when the AI is substituting for it.

The instinct gets it backwards

The natural impulse is to clean up the AI interaction before sharing anything with a collaborator, a team, or a stakeholder. Show the polished output, not the messy process. You don’t want them thinking you just handed your work to a machine.

That instinct produces a disingenuous outcome.

When you hide the process, the people you’re working with have no way to evaluate how the work was made, what judgment calls went into it, or where your expertise ended and the AI’s pattern-matching began. You’ve made the process invisible. And invisible AI processes erode trust, slowly and quietly, over time.

The instinct to hide is also, if we’re honest, a little defensive. It assumes the people in the room can’t tell the difference between AI output and practitioner judgment. Most of them can. And the ones who can’t yet will figure it out. Hiding the seams doesn’t make the work more credible. It just defers the reckoning.

The deeper problem: It’s not just about appearances

Here’s what took me longer to see.

Hiding the process doesn’t just affect how others perceive you. It erodes your own clarity about where your expertise is actually operating.

To understand why, it helps to be precise about what AI actually is. AI is a pattern matcher, a deeply sophisticated one, trained on more human-generated content than any single person could read in a thousand lifetimes. That’s its power (core competency) and its limitation (core rigidity) simultaneously, and the two are inseparable. The very scale that makes it extraordinary is also the boundary that defines what it cannot do. It is extraordinarily good at producing the most likely next thing given what came before. What it cannot do is know what you actually need, when the obvious answer is the wrong one, or when the stated goal isn’t the real goal. It has no judgment about context, relationship, or organizational reality. It has patterns. Incomprehensibly vast ones. But patterns.

That distinction matters because of what happens when you stop paying attention to it.

I’ve watched it happen in my own work. You share a draft with someone and they’re impressed. They quote a formulation back at you, something that sounds sharp and considered. And you realize, tracing it back, that the formulation came from the AI. Not because the AI invented it, but because you said something rougher and less precise earlier in the conversation, and the AI reflected it back in cleaner language. The idea was yours. The AI gave it a polish you then forgot to account for. The person quoting it back thought they were seeing your judgment. They were seeing your thinking laundered through a pattern matcher and returned to you at higher resolution.

That’s the subtler version of the problem. Not that AI invents things. It’s that it can reflect your own thinking back with more confidence and clarity than you put in, and that gap is easy to mistake for the AI contributing something it didn’t.

When you route everything through a polished output layer, you stop noticing the moments where you pushed back, redirected, rejected the first three versions, reframed the question entirely. Those moments are where your judgment lives. They’re the difference between using AI and being used by it. It’s Leonard’s core rigidity problem, applied inward: The very fluency that makes AI feel useful can make your own expertise invisible to you.

When the process stays hidden, the knowledge stays local and static. When it’s visible, it becomes something you and the people around you can actually work with and build on. The reason transparency benefits your audience is the same reason it benefits you: It keeps the scope of your judgment visible and therefore expandable. That’s not just an ethical argument. That’s the amplification mechanism.

Which is also what makes the upside real rather than consoling. When you stay in the process rather than just collecting outputs, work that would have taken days now takes hours. Your thinking gets sharper because you have to articulate it precisely enough for the AI to be useful. The people developing fastest right now aren’t the ones offloading the most. They’re the ones using AI as a thinking partner and staying in the conversation.

Here’s the paradox at the center of it: The more clearly you see the AI as a pattern matcher, the more human you have to be in working with it. The more human you are, the more useful the output. The tool doesn’t replace the practitioner. It reveals them.

Transparency isn’t just an ethical practice. It’s a cognitive one.

Radical AI transparency in practice

I’ve started calling this radical AI transparency. Not a policy, not a compliance framework, not a disclosure checkbox. A practice. Something you can actually do Monday morning.

Here’s how it shows up concretely:

Have the conversation before you need to.

Before you’re deep in a project or collaboration, surface how you use AI and genuinely explore how others do. Not as a disclosure (“I want you to know I use AI tools”) but as a real exchange. What are you using? What do you trust it for? Where are you still skeptical? The comfort level and sophistication in the room will vary more than you expect, and knowing that before you’re mid-deliverable matters.

This is also how you build the psychological foundation for showing your work later. If the people you’re working with have never heard you talk about AI before and you suddenly share a full chat thread, it lands differently than if you’ve already had the conversation.

Track the full threads.

This is partly an orchestration problem and I won’t pretend otherwise. There’s cutting and pasting involved. The tools haven’t caught up to the practice yet, which is itself worth naming honestly when the topic comes up.

A few approaches that help: a running document per project where you paste key threads as they happen (not retroactively, you’ll never do it retroactively), dated and labeled by what you were working on. Claude and most other major AI tools now offer conversation export, which produces a complete record you can archive. The low-tech version, a single shared document per engagement, is underrated for its simplicity.

The reason to do this isn’t just for sharing. It’s for your own reference. Being able to go back and see what you asked, what the AI produced, what you changed and why, builds a record of your judgment over time. That record is professionally valuable in ways that are hard to anticipate until you have it.

Annotate before you share.

Not every thread is self-explanatory to someone who wasn’t in it. Context is everything, and raw transcripts without context are a lot to ask anyone to parse.

A sentence or two before the thread begins. A note at the moment where the direction changed. A brief flag on what you rejected and why. This is where your voice enters the artifact, and it transforms a raw AI exchange into a demonstration of judgment. The annotation is the work. It’s where you show what you saw that the AI didn’t, what you knew that the prompt couldn’t capture, and what made the third version better than the first two.

This is also where the most useful material for future reference lives. Annotations are the deep smarts layer on top of the raw exchange. They’re what makes a conversation a record.

Be real about the errors.

AI makes mistakes. It conflates, confabulates, and hallucinates. It gives you the confident wrong answer with the same tone as the confident right one. It misses context that any competent person in the room would have caught.

These aren’t bugs to apologize for or hide. They’re the clearest window into what the tool actually is. AI makes mistakes in a specifically human way because it was trained on human output. Think of it as rubber duck debugging at professional scale. The AI is a duck that talks back, which is useful and occasionally misleading, which is exactly why you have to stay in the room. When you’re transparent about the errors, and even a little good-humored about them, you’re teaching the people around you something true about the technology. That’s more useful than pretending it’s a black box that either works or doesn’t.

The people who build the most durable trust around AI are usually the ones most comfortable saying: “The first version of this was wrong and here’s how I caught it.”

The bigger picture

What I’ve described so far is an individual practice. But the same principles scale.

Teams and organizations adopting AI face a version of the same problem. The impulse to treat AI outputs as authoritative, to make the process invisible to colleagues and stakeholders, to optimize for the appearance of capability rather than its actual development, produces the same trust erosion. Just at greater scale and with less ability to course-correct.

The teams that will navigate AI adoption well are the ones that treat transparency not as a risk to manage but as a methodology. Where the process of building with AI, including the corrections, the overrides, the moments where human judgment superseded the model, is part of how the organization learns what it actually believes and values. That’s Leonard’s knowledge transfer problem at institutional scale, and the practitioners who understand both dimensions will be the ones leading those conversations.

That’s a much larger conversation. But it starts with the same Monday morning practice.

Show the conversation. Not just the output.

What you’re actually demonstrating

When you show your AI conversations, you’re not demonstrating that you needed help.

You’re demonstrating that you understand what you’re working with. AI is a pattern matcher, trained on more human-generated content than any single person could read in a thousand lifetimes. What it cannot do is know what you need. That requires judgment, context, relationship, and the kind of hard-won expertise that doesn’t reduce to pattern matching, no matter how good the patterns are.

You’re demonstrating that you know the difference between the pattern and the judgment. That you were present enough in the process to know when to push back, when to redirect, when to throw out the output entirely and start over. That you understand, precisely, what the tool can and cannot do, and that you stayed in the room to do the part it can’t.

That’s a meaningful professional signal. It says: “I am not confused about what AI is. I am not outsourcing my judgment. I am using a very powerful pattern matcher as a thinking partner, and I know which one of us is doing which job.”

That’s the work. That’s always been the work.

The tool just makes it visible now. That’s not a threat. That’s an opportunity.

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Claude is a large language model developed by Anthropic. Despite having read more human-generated content than any person could consume in a thousand lifetimes, it still required significant editorial direction, at least three rejected drafts, and occasional reminders about em-dashes. The full conversation transcript is available upon request. It is longer, messier, and significantly less useful than what you just read. Which was rather the point.

Welcome back to Moderator Minutes. This is Part 2 of our series on Community Care in Online Spaces.

In Part 1, we explored how norms shift, how those shifts create friction, and how the ways we respond to that friction can either build or erode community. We asked you to sit with a question: is it working? And we talked about the difference between reacting and responding, between correcting and connecting.

This month, we’re going one layer deeper. Rather than looking at what we do when friction arises, we want to look at what drives us there in the first place. What is it about seeing something distressing that makes us want to act immediately, and what happens when that impulse meets the realities of navigating online spaces?

A note before we begin: the posts in this series are denser than our usual Moderator Minutes. We’ll be drawing on work from several writers and activists who have spent years thinking about these patterns, and we’ll include a reading list at the end for those who want to go further. We don’t expect anyone to read all of it. We do hope the ideas here give you something useful to sit with.

The Impulse to Act

When we see something awful happening, most of us are moved to act. The worse it is, the stronger the pull. This is not a flaw. It is, in many ways, one of the better things about us. The desire to do something in the face of harm is the engine behind every mutual aid network, every crisis response, every act of solidarity that has ever mattered.

But there is a difference between urgency and intention. Urgency says: something must be done, now. Intention asks: what am I trying to achieve, and will this action get me there? When we act from urgency alone, without pausing to examine our goals, we may not know whether our actions meet them. Worse, we may not recognize when our actions actively prevent them.

This is not a new observation. In 2013, writer and organizer Ngọc Loan Trần published an essay called “Calling IN: A Less Disposable Way of Holding Each Other Accountable.” Trần, a queer, disabled, Việt/mixed-race activist, wrote it after attending a large racial justice conference, a room full of people who shared values, who understood the stakes, who all “got it.” And what Trần observed was that those same people, in that shared space, had lost compassion for each other.

That observation is worth sitting with. It was not a room full of people who didn’t care. It was a room full of people who cared enormously, acting from urgency rather than intention, and in doing so, causing harm to the very community they were trying to protect.

Trần coined the term “calling in” to describe an alternative: accountability rooted in relationship rather than punishment. The idea took hold, and over the following decade, a lineage of writers and practitioners built on it. We will be drawing on several of them throughout this post.

The reason we start here is that this pattern, good people, strong values, urgency without intention, is not limited to conferences or activist circles. It is the pattern we see in our reports. It is the pattern many of us enact in our own timelines. And it is the pattern that, left unexamined, erodes the communities we are trying to sustain.

The Pressure to Do More

The urgency we just described does not exist in a vacuum. It is fed by something deeper: the persistent feeling that whatever we are doing, it is not enough.

Consider an example. Say you have spent your week writing posts to help people: sharing mutual aid links, amplifying crisis response information, sending messages of care to people in vulnerable or targeted communities. You have been doing real, tangible work. Then you log in and see a wave of news, or an online harassment campaign, or another round of something terrible, and the question surfaces: am I doing enough?

Let’s mirror something from Part 1 and sit with our feelings for a moment.

Do you feel like you are doing enough, with what is happening in the world, right now?

Whatever your answer is, stay with it a little longer. Feel your way through why you do, or don’t, feel that you are doing enough.

This is not a rhetorical exercise. How you answer that question shapes how you behave online. When the answer is “no” (and for many of us, the answer is almost always “no”) it creates pressure. That pressure comes from two directions. It comes from inside: the internal monologue that tells us we should be doing more, doing it better, doing it differently. And it comes from outside: from communities, from trusted voices, from the implicit and sometimes explicit message that if you are not visibly fighting, you are complicit.

Both of these pressures can be valid in their origin. But when they compound, they produce a specific and damaging result: we stop being able to see the work we are already doing. The posts we wrote, the care we extended, the quiet labor of showing up consistently, all of it disappears under the weight of what we haven’t done. And once we can no longer see our own contributions, we become desperate to do something that feels visible, immediate, and unmistakable.

In 2016, writer and activist Maisha Z. Johnson named a version of this pattern in her essay “6 Signs Your Call-Out Isn’t Actually About Accountability,” published on Everyday Feminism and later republished by YES! Magazine. Johnson, whose background includes work with Community United Against Violence, the nation’s oldest LGBTQ anti-violence organization, described what happens when holding each other accountable drifts into punishing each other. She drew a distinction between acting out of love for our communities and acting out of fear and pain. The behaviors can look similar from the outside, both involve publicly naming a problem, but they come from different places and produce very different outcomes.

What Johnson was naming is something many of us will recognize if we are honest with ourselves. There are times when we call something out because we have a clear goal: we want a specific behavior to change, and we believe our words will contribute to that change. And there are times when we call something out because we are exhausted, because we are afraid, because the pressure to do something has become unbearable and this is the something that is available to us. The second is not accountability. It is release. And while the release is understandable, it is not the same as the work it replaces.

Where We Feel Power

There is a concept in psychology called “locus of control.” It describes where we believe power over our lives sits, inside ourselves, in our own actions and choices, or outside ourselves, in forces beyond our control. The term comes from the work of psychologist Julian Rotter in the 1950s, and it has been widely studied since.

We want to be careful with this concept, because the traditional framing carries a bias. The conventional view treats an internal locus of control, the belief that your actions shape your outcomes, as the healthier orientation. But this framing was developed within a Western, individualist perspective, and it has a significant blind spot. For people from marginalized and targeted communities, the feeling that external forces control your outcomes is often not a distortion. It is an accurate reading of the situation. Discrimination, structural oppression, and systemic inequity are real forces that genuinely constrain what individual action can achieve. Scholars studying locus of control in the context of marginalized populations have noted that what looks like a “less healthy” external orientation may in fact reflect a realistic assessment of the limitations that racism, discrimination, and socioeconomic conditions impose.

So we are not using this concept to suggest that feeling powerless is itself a problem to fix. For many of us, the feeling of lacking control is grounded in reality, and naming that is important.

What we do want to examine is what happens next. What we do with that feeling.

Here is an analogy. Imagine you volunteer at a soup kitchen. In relatively stable times, the work feels meaningful. You can see the people you are helping. The scale of the need, while real, feels approachable. Your contribution feels like it matters.

Now imagine the same soup kitchen during an extreme crisis, a climate disaster, an economic collapse, a wave of displacement. The lines are longer. The need is greater. The news is relentless. You are doing the same work, or more, but it no longer feels like enough. The scale of the crisis dwarfs your individual contribution, and the gap between what is needed and what you can provide becomes a weight you carry home with you.

The work did not become less valuable. But your relationship to it changed.

This is what happens in online spaces when the world feels like it is on fire. Even if you are showing up consistently, posting resources, supporting others, extending care, the relentless news cycle and the visible enormity of harm can make all of it feel like nothing. And when your sustained, quiet work feels like nothing, the pull toward something louder becomes very strong.

This can lead to an unhealthy relationship with the negative feelings that accumulate. You may not be able to stop an oppressive force. But you can shout about it. You can name and shame. You can find a target and direct your frustration somewhere, anywhere, because the alternative, sitting with the feeling that you cannot individually fix what is broken, is unbearable.

The shift is subtle, and it is worth naming precisely: the goal stops being “change this specific thing” and becomes “make this feeling go away.” That is the moment where the impulse to act stops serving the community and starts serving our own need for relief. And as we discussed in the previous section, that is not accountability. It is release wearing its clothes.

Misdirected Action

Once that shift has happened, once the goal has quietly become relief rather than change, the question of where we direct our energy starts to matter in a different way.

Not all calling out is the same. There are differences in context, in scale, and critically, in the power held by the person on the receiving end. When we are acting from intention, we tend to account for those differences naturally. We think about who we are talking to, what we want to achieve, and whether this specific action in this specific context will move us toward that goal. When we are acting from urgency and exhaustion, those distinctions collapse. Everything feels equally urgent. Everyone feels equally responsible. And the energy has to go somewhere.

Consider this example. A large company does something harmful. The CEO makes a decision that affects thousands of people. You are angry, and that anger is justified. But the CEO is not on your timeline. The person who is on your timeline is the company’s social media manager, posting the corporate line because that is their job. They did not make the decision. They likely have no authority in the hierarchy that produced it. They may privately disagree with it. They need to buy food and pay rent, and this is the job they have.

There is a reason this feels like a distinction without a difference in the moment. When a person speaks, we naturally assume they are speaking with their own voice, that their words represent their own thoughts, their own positions, their own authority. That is how individual speech works. But corporate speech breaks that assumption. The social media manager is voicing something that was shaped by people they may never have met, reflecting decisions they had no part in making. They are a conduit, not a source. And yet, because we hear a person speaking, we instinctively assign them the ownership that comes with speech. The CEO, the social media manager, the customer support agent, all of them register as “the company” in a way that erases the vast differences in their actual authority. This is natural, but it is not accurate. And when we act on it without examining it, we direct real force at people who have no capacity to give us what we want.

If you spend your afternoon arguing with that social media manager, or ten social media managers across ten companies, you have not changed the company’s behavior. You have not reached the decision-maker. You have not decreased the harm. You have worn yourself out, and a person who was not responsible for the harm has absorbed the force of your frustration.

There is also an alternative that is easy to miss. You can call out the company without engaging with its social media account at all. You can post about what the company did, name it clearly, tag a handle or use a hashtag if you want visibility, and then not respond when the company account replies. The social media manager or their team may be tasked with responding to mentions. That does not obligate you to continue the conversation. You have said what you needed to say. You do not owe anyone a thread. Posting about a company and arguing with its lowest-ranking representatives are very different actions, and only one of them preserves your energy for the work that actually matters.

This is not a moral judgment. It is a practical observation. When we stop distinguishing between targets based on their actual power and responsibility, we spread our energy across surfaces that cannot absorb it productively. It feels like fighting. It is not the same as building.

Kai Cheng Thom, a Chinese-Canadian trans woman, writer, social worker, and conflict resolution practitioner, wrote directly about this dynamic in her book I Hope We Choose Love: A Trans Girl’s Notes from the End of the World. Thom observed that in social justice communities, “accountability” had increasingly become a script, a performance of the correct response rather than a genuine path toward repair. The question she posed was pointed: are we more committed to the feeling of calling out than to the work of resolving conflict?

Thom was writing from inside queer and trans communities, about dynamics she had experienced firsthand, and her observation carries a challenge that applies well beyond those communities. If accountability has become a performance, if we are following the script because the script makes us feel like we are doing something, then we need to ask what the performance is replacing. And whether we would be willing to do the harder, quieter, less visible thing instead.

That question is not comfortable. It is also, we believe, necessary. Because if the patterns we have described in this post are recognizable to you, the urgency, the pressure, the powerlessness, the misdirected energy, then you are already familiar with how exhausting they are. You already know that they are not sustainable. And you may already suspect that there is something better available, even if you are not sure what it looks like.

That is what we want to talk about next.

Channeling Energy Constructively

Everything we have described so far, the urgency, the pressure, the collapse of distinctions, the drift from accountability into release, shares a common feature. It is all individual. It is one person, overwhelmed, trying to address systemic harm through individual action, burning through their own reserves in the process.

This is not a coincidence. The patterns we have been describing are, in large part, the result of trying to do collective work alone.

Leah Lakshmi Piepzna-Samarasinha, a disabled queer writer and longtime disability justice activist, offers a different frame. In their book Care Work: Dreaming Disability Justice, Piepzna-Samarasinha describes a concept they call “care webs,” networks of mutual support that are not built in response to a crisis, but maintained as ongoing infrastructure. A care web is not one person showing up heroically in a moment of need. It is a group of people who have already done the work of figuring out who can do what, who needs what, and how they will sustain each other over time.

The distinction matters for what we are talking about here. When you are operating alone, one person, one timeline, one set of reserves, every new crisis draws from the same finite well. The pressure to do more is a pressure on you, personally, and when you cannot meet it, the failure feels personal too. The urgency becomes yours to carry. The powerlessness becomes yours to manage. And the misdirected action we described earlier becomes almost inevitable, because individual urgency demands individual action, and individual action at that scale does not work.

A care web changes the unit of action. Instead of asking “what can I do about this?” you are asking “what can we sustain together?” Instead of measuring your contribution against the scale of the crisis, a measurement that will always come up short, you are measuring it against what your web has agreed it can hold. The soup kitchen does not become less overwhelming because you joined a care web. But your relationship to the overwhelm changes, because you are no longer the only person responsible for responding to it.

This is not abstract. In online spaces, care webs can take forms that many of you will recognize even if you have not used the term. A group of people who coordinate to amplify mutual aid posts so that no single person has to carry the full weight of visibility. A set of friends who check in with each other before responding to a provocative thread, not to police each other but to ask: are you okay? Is this the thing you want to spend your energy on right now? A community that has explicitly discussed what it is building together, so that when the next crisis arrives, its members have a shared framework for deciding how to respond rather than each person reacting alone.

What these examples share is that they move the question from “am I doing enough?” to “are we building something that can sustain us?” That shift does not eliminate the urgency. It does not make the world less frightening. But it changes the relationship between the individual and the work. It makes the quiet, sustained labor, the posts, the check-ins, the mutual aid, the showing up, visible again as contributions to something larger, rather than invisible drops in an endless ocean.

This is what we mean by channeling energy constructively. Not the absence of anger. Not the suppression of urgency. But the practice of directing that energy into structures that can hold it, that can receive it and convert it into something that outlasts the moment. A post about a company’s harmful behavior, written with clarity and shared once, is channeled energy. A thread that spirals into hours of argument with people who have no power to change anything is not. A check-in with someone in your community who you know is struggling is channeled energy. Doomscrolling until you find a target for the feelings you cannot sit with is not.

The difference is not always obvious in the moment. That is why the infrastructure matters more than any individual decision. If you have already built the web, if you have people who will check in with you, if you have a shared understanding of what you are building together, then the moment of crisis is not the moment where you have to figure all of this out alone. You have already done that work. And the work you did counts.

Sitting With It

We started this post by asking you to go one layer deeper, to look not just at how you respond to friction, but at what drives you there. We have covered a lot of ground: the gap between urgency and intention, the pressure that makes our own work invisible to us, the ways powerlessness channels itself into misdirected action, and the difference between acting alone and building something that can sustain us.

We want to close by returning to the question we asked earlier in this post, with a small shift:

Where is your energy going, and is it creating what you want for yourself and your community?

If you have been sitting with that question as you read, you may have noticed something. The answer may not have changed. But the way you are looking at it might have.

If your energy is going toward things that leave you exhausted without moving you closer to what you want, for yourself or for the people around you, that is not a signal to try harder. It may be a signal that you are carrying something alone that was never meant to be carried alone. It may be a signal that your reserves are depleted and that what you need is not more action, but more support. It may be a signal that the structures around you, the care web, the shared understanding, the people who check in, are not yet built, or need tending.

None of that is a failing. All of it is an invitation.

In our next Moderator Minutes, we will be looking at what happens when these ideas meet friction in real time: how to set and hold boundaries in online spaces, and how to de-escalate when things are already moving fast. If this post was about understanding where your energy goes and why, the next will be about protecting it when it matters most.

Our community discussions have moved to Zulip since the last Moderator Minutes. We are still inviting people in by hand, so if you would like to join us, ping us in our Discord and we will get you added.

As always, processes grow over time, and this conversation is no exception.

Further Reading

References

Ngọc Loan Trần, “Calling IN: A Less Disposable Way of Holding Each Other Accountable” (2013). Published on Black Girl Dangerous. Also archived on TransformHarm.org.

Maisha Z. Johnson, “6 Signs Your Call-Out Isn’t Actually About Accountability” (2016). Published on Everyday Feminism. Also republished by YES! Magazine.

Kai Cheng Thom, I Hope We Choose Love: A Trans Girl’s Notes from the End of the World (2019). Arsenal Pulp Press. Here is a review on Plenitude Magazine.

Leah Lakshmi Piepzna-Samarasinha, Care Work: Dreaming Disability Justice (2018). Arsenal Pulp Press. Here is a review on Autostraddle.

Leah Lakshmi Piepzna-Samarasinha and Ejeris Dixon, eds., Beyond Survival: Strategies and Stories from the Transformative Justice Movement (2020). AK Press. Here is a review on Autostraddle.

If you’d like to read more

On calling in and calling out: Loretta Ross has spent the decade since Trần’s essay turning “calling in” into something teachable, drawing on five decades of organizing. Her TED talk is about fifteen minutes and a good place to start. Her book Calling In: How to Start Making Change with Those You’d Rather Cancel (Simon & Schuster, 2025) develops a five-part continuum of responses (canceling, calling out, calling off, calling on, and calling in) with practical guidance on when each one fits.

On online harassment and digital safety: Each of these is most useful when you read it before you need it. They cover overlapping ground in different registers, so it is worth knowing which is closest to your situation.

• PEN America’s Online Harassment Field Manual: written for writers, journalists, artists, and activists, particularly those who are women, BIPOC, or LGBTQIA+. What makes it distinct is that it is organized by your role in the situation, whether you are being targeted, witnessing someone else being targeted, or running an organization where staff is, rather than as one undifferentiated guide. (This resource appears to have geo restrictions.)
• Games and Online Harassment Hotline Digital Safety Guide: originally written by Jaclyn Friedman, Anita Sarkeesian, and Renee Bracey Sherman, all of whom had been targeted themselves. It is the most granular of the three on specific tactics like doxxing prevention and hate raids, and it is especially direct about how well-meaning allies can inadvertently amplify harassment by engaging on a target’s behalf. The hotline itself closed in October 2023, but the guide is still online.
• EFF’s Surveillance Self-Defense: the deepest of the three on technical infrastructure (encryption, secure messaging, device security, network circumvention). The “Security Scenarios” section lets you pick a situation that matches yours (activist, journalist, abortion access worker, LGBTQ youth) and follow a tailored learning path rather than starting from scratch.

On activism, organizing, and community safety more broadly: The Commons Social Change Library is the broadest of the resources in this section. Run by movement librarians in Australia, it curates over 1,500 free, openly accessible materials from movements around the world, organized into collections on campaign strategy, community organizing, working in groups, justice and diversity, and creative activism. Where the resources above are sharply focused, the Commons is where you go when your question is harder to name in advance.

Guest:

• Grant Dasher, ex-CISA, ex-Google, Distinguished Engineer, Google (again)

Topics:

• Why is the  "Secure-by-Design" movement gaining so much momentum now, and is it a response to the failure of "bolted-on" security, or just a natural evolution of cloud maturity?
• In a future Secure-by-Design world, is identity the only perimeter that actually matters anymore? Or is this a cliche?
• As we move toward a world of autonomous agents, how does our approach to machine identity need to change? Are we just talking about more complex Service Accounts, or do we need a fundamental shift in how we authorize "intent"
• What is your  advice  to people who want to move fast and cannot wait for Secure by Design / Default  AI to be decided by consensus or IETF, NIST or OASIS committee?
• We love the argument that modern AI agents are effectively repeating the mistakes of 1960s payphones - mixing the data plane and the control plane. What is your rebuttal? How do we build "Agentic Security" that doesn't fall for 60-year-old traps?
• Customers are torn between their Zero Trust implementations and their AI adoption. Is Zero Trust now "legacy," or is it the prerequisite for everything we're trying to do with AI agents?  
• Is there Zero Trust for AI? Is this a fake buzzword or technical reality?

Resources:

• Video version
• EP256 Rewiring Democracy & Hacking Trust: Bruce Schneier on the AI Offense-Defense Balance
• EP133 The Shared Problem of Alerting: More SRE Lessons for Security
• EP85 Deploy Security Capabilities at Scale: SRE Explains How
• Google SRE books
• "Atomic Accidents" book (yes, really)

Download audio: https://traffic.libsyn.com/secure/cloudsecuritypodcast/EP274_not260_CloudSecPodcast.mp3?dest-id=2641814

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You see an outfit you love, but it’s not just the jacket you want—it’s the entire vibe. What if you could search for it all at once? In this episode, host Rachid Finge sits down with Product Manager Harsh Kharbanda to explore the next generation of Circle to Search, now available on Pixel 10.

Discover how new multi-object recognition allows you to search an entire scene, from deconstructing a full outfit with 'Find the Look' to identifying every fish in an aquarium. Learn how advanced AI is making it easier than ever to satisfy your curiosity and shop for the whole picture, not just a single piece.

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Hosted on Acast. See acast.com/privacy for more information.

Download audio: https://sphinx.acast.com/p/open/s/63e39eb02e631f0011a284ac/e/69eb54d11e1e8123645864a1/media.mp3

Scott and Wes break down what makes CSS truly manageable—from preventing style leaks and embracing fluid layouts to choosing the right methodology, whether that’s utility CSS, component-scoped styles, or CSS modules. They also dive into practical tips like leveraging CSS variables, layers, scoping, and tooling to keep your stylesheets clean and scalable.

Show Notes

• 00:00 Welcome to Syntax!
• 01:31 Understanding CSS Manageability
• 01:44 This CSS doesn’t leak to other parts of website.
• 03:41 This CSS is easy to maintain.
• 05:54 This CSS is reusable.
• 06:10 Global Solutions Instead of Local Solutions.
• 07:12 Flexibility and Adaptability in CSS
• 09:36 Fluid Typography and Responsive Design
  • fluid-type
• 12:09 Variables and Consistency in CSS
• 13:40 Brought to you by Sentry.io.
• 14:14 Values vs Variables.
  • Project Wallace.
• 18:19 Choosing the Right CSS Methodology
• 18:48 Utility CSS and Atomic CSS
• 22:35 Exploring StyleX and Other Approaches
  • Syntax Ep 650.
• 25:14 Panda CSS.
• 25:37 Component Scoped CSS: A Preferred Approach
• 29:08 The Evolution of CSS Modules
• 34:03 Global CSS: Best Practices
  • Josh Comeau’s CSS Reset.
  • Scott’s Graffiti UI.
• 38:22 Harnessing CSS Variables
• 41:33 Understanding CSS Layers
• 43:52 The Power of CSS Scoping
• 46:16 Enforcing CSS Standards with Tools

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Download audio: https://traffic.megaphone.fm/FSI5518908653.mp3