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Based on "How GitHub Deals with 17 Million Pull Requests a Month" from Every Watch the original video

The AI Deluge: GitHub's Battle on the Front Lines of Code's Exponential Future

Episode summary

GitHub's COO, Kyle Dagel, reveals how the platform is grappling with an explosion of activity, now processing 17 million agent-created pull requests monthly—a staggering increase from the mere 1 billion commits in all of last year. This surge is driven by a broadened definition of "developer," with non-traditional users like legal and finance teams leveraging tools like GitHub Copilot to build apps and assets, fundamentally shifting product roadmap priorities towards accessibility and ease of use.

To manage this influx and prevent agent subscription costs from spiraling, GitHub is focusing on "hill climbing"—a continuous improvement loop using both hard metrics and user sentiment to refine models and workflows. The practical takeaway for users and enterprises is the development of "model routers" that intelligently select the most cost-effective AI models based on task complexity, ensuring efficient resource allocation rather than relying on expensive, general-purpose models for every minor task.

The world of software development is undergoing a seismic shift, driven by the relentless rise of artificial intelligence. At the epicenter of this transformation stands GitHub, the ubiquitous platform where the world builds software. With an unprecedented 17 million pull requests (PRs) pouring in every month, a significant portion of which are generated by AI agents, GitHub is grappling with a deluge of code that is redefining how we build, collaborate, and even conceive of "developers."

Mike Taylor, head of tech consulting at Every, recently sat down with Kyle Dagel, COO of GitHub and Chief Marketing Officer of Developer for Microsoft, to peel back the layers of this new "agent economy." Their conversation illuminated GitHub's strategies for navigating this exponential growth, supporting its diverse user base, and envisioning a future where AI isn't just a tool, but a fundamental partner in creation.

The New Face of the Developer

One of the most striking changes GitHub observes is the evolving demographic of its users. Historically a domain for professional software engineers, GitHub is now seeing a significant influx of "knowledge workers" – individuals from legal, finance, and other non-traditional tech backgrounds – leveraging AI tools to build applications and assets.

"For GitHub, in particular, we've always really had this really expansive view of what a developer is," explains Dagel. He recounts his own journey, writing code to pay for art school, long before he would have called himself a "dev." This personal history informs GitHub's philosophy: to make it easier for anyone to choose to write some code, ensuring there's always an on-ramp into software creation. Tools like GitHub Copilot are central to this democratization, enabling teams across an enterprise to build small apps and automate tasks, even without a formal computer science background.

While GitHub continues to serve the largest businesses and "serious developers," it recognizes that the future of coding is inclusive. The product roadmap is now shaped by the needs of this broader audience, striving to build tools that empower both seasoned engineers and accidental coders.

Taming the Deluge: Supporting Open Source Maintainers

The sheer volume of AI-generated code presents a significant challenge, particularly for open-source maintainers who are, in Dagel's words, "drowning" under a flood of pull requests. The question isn't just about quantity, but also about quality and the burden of review.

GitHub is addressing this with agentic tools designed to streamline the code review and merge process. Features like Copilot Code Review, which can identify novel vulnerabilities and implement changes based on comments, significantly reduce manual effort. The "agentic merge" capability allows maintainers to set policies and let the AI handle the final processing steps, waiting for CI checks and other requirements to pass automatically.

However, GitHub maintains a delicate balance when it comes to open source. "Every community is choosing a slightly different way to approach the problem," Dagel notes. Rather than imposing a universal standard, GitHub focuses on providing maintainers with granular control. This means offering tools to decide who can submit PRs, how much work is required to prove a contribution's value, and the level of vetting needed. Dagel cites Mitchell Hashimoto's "vouch system" as an example of a community-led solution that GitHub observes but doesn't immediately roll out to everyone. The goal is to provide building blocks and enable communities to self-organize, cementing a system only if a clear, widely adopted practice emerges.

The Agent Economy's Boom

The statistics are staggering. Last year, GitHub recorded a billion commits for the full year. This year, if growth were linear, it would be 14 billion. But the growth isn't linear; it's exponential, largely thanks to AI agents. In March alone, 17 million pull requests were created by agents.

This explosion of activity signals a fundamental shift: "It's not just Kyle building, but it's Kyle in one to N, you know, agents," Dagel illustrates. While some might dismiss this as "slop" or low-quality code, Dagel argues that it represents a significant leap in productivity. Developers are now collaborating with AI partners, using their skills, resources, and context to generate code at an unprecedented pace. GitHub is investing heavily to prepare for the "next wave of growth," recognizing that "no matter where you're building or what tools you're using to build, all of that code ends up on GitHub."

Evolving Business Models: Freemium to Usage-Based?

The rise of 24/7 AI agents challenges traditional freemium business models. If agents are constantly working while humans sleep, how does pricing adapt? Dagel acknowledges that the ultimate model is still evolving. GitHub has historically adapted its offerings, moving from paid private repos to free ones for individuals. The current focus is on ensuring a "great core GitHub experience" for developers, which includes a baseline of agent usage.

However, for those who want to run "150 agents doing everything all at once," as one developer famously put it, a usage-based model seems inevitable. The challenge lies in balancing the need to enable scaled agent activity with providing a predictable, valuable experience for individual developers and enterprises. This will involve careful consideration of API rate limits and how to meter the immense computational effort behind agent-driven development.

A Dual Mandate: Developer-First at Scale

Kyle Dagel's unique dual role as COO of GitHub and Chief Marketing Officer of Developer for Microsoft offers a fascinating glimpse into the strategic alignment of two tech giants. Having been at GitHub for 13 years, Dagel emphasizes the company's unwavering focus on the developer. "We're not building for the buyers, we're building for the developers 100%," he asserts.

This developer-centric philosophy is now being extended across Microsoft's broader developer tooling. Dagel's aim is to ensure "holistic solutions that you can use that are authentic to developer experiences." This influence was evident at the recent Microsoft Build conference, which took a dramatically different approach: relocating to San Francisco, focusing on hands-on sessions over sales pitches, and, crucially, inviting external community speakers into primary sessions. This shift reflects the belief that "software development is a team sport" and that no single company holds all the answers.

The Power of Choice in a Competitive Landscape

In a rapidly evolving and fiercely competitive market, GitHub's differentiation lies in its steadfast commitment to "developer choice." Dagel explains that while the industry sometimes trends towards "unintentional walled garden setups," GitHub actively resists this. Instead, it aims to enable developers to use GitHub alongside other tools and partners with "everyone who's bringing a model to market or a coding agent to market."

This means not only investing in its own AI models (like the new Microsoft AI models) but also integrating and emitting through GitHub Copilot the capabilities of Anthropic, OpenAI, Google, and other providers. "That choice is core, and that's something that I don't think we'll ever back down on," Dagel declares. "Because if we do, developers will still choose. They'll just be stuck in another kind of mouse trap... and we don't want the world of software to be like that."

Internal Innovation and "Hill Climbing"

GitHub's internal decision-making process embraces a culture of "experimentation." Dagel himself "dogfoods" across multiple operating systems (Mac, Windows, Linux) and uses various tools, even those not made by Microsoft, to understand the developer experience. This prevents "blind spots" that can arise from an overly narrow focus.

A core methodology driving GitHub's progress is "hill climbing." This iterative, data-driven approach involves continuously improving models and tools based on real-world usage data – from "thumbs up/thumbs down" feedback to acceptance rates of AI suggestions. "Every week we're talking about the hill climbing results," Dagel states. The emphasis is on small, continuous improvements rather than chasing "moonshots." This involves looking at both "hard measures" (evals, rubrics) and "soft measures" (user sentiment), recognizing that sometimes an improvement in metrics can lead to a crash in user satisfaction if not carefully managed. The ultimate goal is to empower every developer with their own "hill climbing machine," making continuous improvement accessible and automated.

The $200 to $2,000 Problem: Solving for Token Economics

The concern of a $200/month coding agent subscription ballooning to $2,000/month is a very real one in the agent economy. Dagel believes the answer lies in intelligent model routing and personalization. The solution isn't just about better, cheaper models, but about automatically choosing the right model for the right task.

This involves "model routers" that can assess task intent and select the most efficient model – perhaps a smaller, cheaper model for a simple find-and-replace, and a more powerful, expensive one for a complex architectural problem. "The more and more that we can help you tell us a bit of like where your bars are, like this is an incredibly hard problem and I'm willing to go all the way to the top, or I don't, I just kind of want to sit here, and let us help choose the models," Dagel explains. This intelligent orchestration, combined with "Frontier Tuning" (personalizing models with individual context and memory), is crucial to optimizing token usage and preventing runaway costs, especially for enterprises.

The Personal AI Loop: A Surprising Revelation

In a lighter, yet profoundly insightful moment, Mike Taylor revealed he had created an AI clone of Kyle Dagel to practice the interview. Dagel's response was even more surprising: he does something similar himself. Dagel uses a personal AI (affectionately named "Baxter") to read everything he writes – emails, Slack messages, scripts – and provide daily "comms reports."

"Kyle, you keep saying this. This isn't super clear," his AI might say, or offer clearer metaphors based on his speaking style. Dagel finds this "self-improvement loop as a human from these agents to be incredibly powerful." He harks back to the early days of chat ops with Hubot, noting, "Humans are way more willing to take critical feedback from robots than other humans." This less threatening feedback loop helps him recursively self-improve his communication. This personal application of AI highlights a future where agents not only augment our coding abilities but also our human skills, offering a unique form of introspective development.

Conclusion

GitHub stands at a critical juncture, navigating the unprecedented growth of AI-generated code and the evolving landscape of software development. Under Kyle Dagel's leadership, the platform is committed to an inclusive, developer-first approach, offering choice, fostering community-led innovation, and embracing iterative improvement. From taming the deluge of pull requests to reimagining business models and even personal development, GitHub is not just observing the AI revolution; it's actively shaping its future, ensuring that the next wave of code is built collaboratively, efficiently, and with the developer at its heart.

Based on "Generative AI's race problem | It's Been a Minute" from NPR Podcasts Watch the original video

The Unseen Battle: How Generative AI Exploits Race, Gender, and Our Deepest Biases

Episode summary

NPR's "It's Been a Minute" explores the "race problem" in generative AI with podcast host Bridget Todd, who argues that AI-generated content, particularly videos featuring Black women, often exploits racial stereotypes for profit and to confirm existing biases. A prime example is the viral, AI-generated song "Phenomenal Black Woman," which, despite its manufactured origins, resonated deeply with many Black women due to a lack of genuine media representation, highlighting how AI is designed to elicit strong emotional responses. This extends to "scammy" videos of Black children making handmade items, which are actually drop-shipped goods, exploiting community solidarity for financial gain.

Viewers should be wary of content designed to provoke an instant, strong emotional reaction, as this is a key indicator of potentially AI-generated or manipulative material. The hosts also discuss how AI is used to spread misinformation and political discord by validating pre-existing fears, especially among those unfamiliar with a given context. While some platforms encourage AI disclosure, these are not requirements, leaving users susceptible to content that profits from engagement, even if it's based on harmful caricatures or outright scams.

In the ever-evolving landscape of digital media, a catchy tune titled "Phenomenal Black Woman" recently captivated TikTok feeds, sparking joy and pride among many Black women and their families. The song, by an artist named China Styles, from an album called I Love Me, seemed to embody a powerful message of self-affirmation. Yet, beneath its seemingly positive surface lay a disquieting truth: the artist, the album, and the song itself are entirely products of artificial intelligence.

This anecdote, shared by NPR's Britney L. Loose on "It's Been a Minute," serves as a stark introduction to a broader, more insidious problem that AI expert and "There Are No Girls on the Internet" podcast host Bridget Todd has been tirelessly ringing the alarm about. Generative AI, while promising innovation, is increasingly being leveraged to create content that traffics in harmful racial and gender stereotypes, often for financial gain or to sow discord. "Our platforms, a lot of them are designed such that unfortunately there is financial incentives to making this kind of content," Todd explains.

The Phenomenon of "Phenomenal Black Woman"

The "Phenomenal Black Woman" song, despite its AI origins, quickly became a viral sensation. Loose recounts how she heard it countless times on her TikTok feed, and even Black "aunties" in her life embraced it. But as soon as Todd heard it, her "society senses" went up. "It sounds so fake. It sounds so cheesy. It sounds so corny," she remarked, questioning if it was truly a Black woman singing or "Glen Kosa's character from Deliverance."

This "on the nose" quality, Todd explains, is a hallmark of racialized AI content. It's so overtly crafted to appeal to a specific identity or emotion that it struggles to suspend disbelief. While the song moved many Black women, offering them a rare feeling of being "meaningfully seen" in a media landscape that often overlooks them, Todd points out its manufactured nature. "It's literally been designed, manufactured... to elicit some kind of strong response," she says, describing it as having "all of the caricature turned up to 11." This exemplifies how AI can exploit genuine human needs and desires for representation, twisting them into commodified, inauthentic experiences.

When Empathy Becomes a Weapon: Scams and Stereotypes

The "Phenomenal Black Woman" song, while ethically dubious, pales in comparison to some of the more overtly harmful AI-generated content Todd has encountered. These videos range from low-level scams to deeply nefarious forms of exploitation.

The "Handmade Purses" Deception

One prevalent scam involves AI-generated videos purporting to show Black children lovingly making handmade items, often purses. The accompanying narrative typically features a tragic backstory: the child took their creations to a craft fair, only for "racist white kids" to push them to the ground. The video then shows the child diligently sewing and asks viewers to "support this young black visionary" by clicking a link to buy their products.

This tactic is particularly insidious because it preys on community solidarity. "Whoever is making this content, they know that black folks, we ride for each other. We go up for each other," Todd asserts. Celebrities like Viola Davis and Robin Dixon were among those initially taken in by these emotionally manipulative videos. The "handmade" items, of course, turn out to be mass-produced, drop-shipped junk from unethical sources, highlighting how AI is used to craft compelling, yet entirely false, narratives for financial gain.

Political Caricatures and Misinformation

Beyond scams, AI-generated content is a potent tool for political manipulation and the spread of misinformation. Loose recalls seeing AI-generated "political oppo videos" during a New York City mayoral race, designed to quickly elicit negative emotions about candidates by linking them to terrorism, violence, or crime.

Todd highlights even more disturbing examples, such as AI-generated videos that surfaced before SNAP funding pauses were implemented. These videos depicted "racially stereotypical black women" – often "heavy set" and behaving in exaggerated ways – having "big reactions" in grocery stores. This content, often bearing AI branding like "Sora or V3," went viral despite its obvious artificiality.

"You don't even need... the welfare queen Linda Taylor anymore," Todd laments, referring to a historical figure used to perpetuate racist stereotypes about welfare recipients. "You don't need an actual real life sort of scammer and schemer when you can just sort of generate these AI caricatures." These videos effectively serve as "racist fanfiction," designed to validate pre-existing biases and fears about public services and their recipients, influencing public opinion and potentially even news outlets.

Digital Blackface and Deeper Exploitation

The use of AI to create racially charged caricatures has been aptly termed "digital blackface" by some. Todd notes that these videos heavily traffic in racial and ethnic stereotypes, designed to provoke strong emotional reactions. For instance, AI-generated Black women with "impossibly dark skin" are sometimes depicted saying "racially degrading or racially inflammatory things," with links in their bios leading to paid adult content sites. The audience for such content is clearly not Black people, but rather those who consume and are fueled by such derogatory depictions.

The "why" behind this exploitation ranges from "engagement farming" – keeping users on a page longer for potential platform payouts – to direct dropshipping scams and even explicit content. AI allows creators to "AB test" different stereotypes at scale, generating endless "slop" until they find the exact right content to resonate with a target demographic, often one predisposed to existing biases.

The Profit Motive: Why AI Exploitation Thrives

The explosion of such content is largely driven by its low cost and ease of production. Platforms like Google V3 (and formerly OpenAI's Sora) allow for the rapid creation of these videos. This accessibility, coupled with platforms' design that financially incentivizes viral content, creates a fertile ground for exploitation.

"If you can get a few bucks for making a viral AI generated video that pops off, whether it traffics in like racially inflammatory content or not, our platforms... are designed such that there is a financial motivation to do exactly that," Todd explains. This system allows for the "commodification" of Blackness and other identities without the need to engage with or compensate actual people. Creators can bypass the objections of real individuals who might find such depictions racist or demeaning, producing content at scale that appeals to a market for "black caricature in conflict."

The "Girlbossification" of AI: A Gendered Divide

The ethical minefield of AI extends beyond race to gender, sparking another contentious conversation. Reese Witherspoon recently drew criticism for advocating that more women get involved with AI, citing that women's jobs are more likely to be automated. This push for women to adopt AI has been dubbed the "girlbossification of AI."

Statistics reveal a significant gender gap: a CNBC survey found that 69% of men view AI as a "valuable assistant," compared to just 61% of women. Half of women expressed suspicion, viewing AI use at work as "cheating," a sentiment shared by only 43% of men.

Todd delves into the nuanced reasons behind women's skepticism, challenging the simplistic narrative that women are "too stupid" or "afraid" of AI. She highlights that women are:

Todd criticizes the "influencer" culture that frames AI adoption as an individual failing for women. "It's the same thing that we always see of like blaming women for institutional or systemic issues that women are not the cause of," she argues. This narrative deflects from the systemic biases embedded in AI and tech infrastructure, placing the onus on individual women rather than addressing deeper structural problems.

Celebrity endorsements, like Witherspoon's or Mel Robbins' advice for women to use AI for finances, are also viewed with skepticism. These powerful figures, often part of an "owner class," see AI as a business advantage. They leverage their familiarity and "woman-to-woman" persona – like Witherspoon making a smoothie in her kitchen – to sell AI adoption to a general audience, despite likely relying on human experts for their own complex needs. "She's definitely not using Microsoft Copilot to manage her finances," Todd quips about Mel Robbins.

AI in the Literary World: The Goodreads Scandal and Beyond

The publishing industry has also grappled with AI's disruptive force, a crisis foreshadowed by the "Goodreads scandal" of 2024. In that incident, an author was caught using fake aliases to "review-bomb" competing authors while giving her own book glowing reviews.

This paved the way for more recent controversies, such as author Mia Ballard's book Shy Girl, which faced claims of being AI-written. The ensuing backlash was so severe that the publisher, Hatchet, canceled its US publication.

Todd points out that publishers often "want it both ways," desiring to use AI when it benefits them but lacking clear policies, leaving individual authors vulnerable. "It's not really a great system if we're just setting up individual writers or people to absorb all the negative blowback that might come with using AI," she states. She advocates for publishing companies to have "completely transparent and fleshed out" AI policies in their contracts, reflecting the realities of 2026.

Navigating the Minefield: Individual Awareness vs. Systemic Change

The pervasive and often insidious uses of AI highlight that technology, far from being a neutral force, amplifies existing societal problems like racism, sexism, and misogyny. How do we account for these deeper harms that go beyond labor issues and plagiarism?

Todd offers a starting point: individual mindfulness. When scrolling through feeds, if content sparks a strong emotional reaction – whether pride, disgust, or even joy – pause and reflect. "Why am I experiencing it? Who is on the other side of this interaction who might be profiting from me feeling this way?" she advises. This awareness, she suggests, is crucial for navigating a digital world where content is explicitly designed to manipulate emotions.

However, Todd is quick to emphasize that the burden shouldn't solely fall on individuals. "We should not have to do this," she declares, acknowledging that people are often vulnerable while consuming media, scrolling half-asleep in bed. The expectation for everyone to maintain a constant, high level of critical thought about their media habits is unreasonable.

Ultimately, the conversation points to a profound need for better systemic solutions and greater accountability from platforms and AI developers. Until robust safeguards are in place, users must remain vigilant, questioning the origins and intentions behind the captivating, often unsettling, content generated by AI. The battle against exploitation in the age of generative AI is not just technological; it's a social and ethical reckoning that demands collective attention.

Based on "How Getting Stoned With My Dad Helped Us Heal" from New York Times Podcasts Watch the original video

From Smoke to Healing: A Son's Journey to Reconcile with His Trickster Father

Episode summary

This Modern Love episode features writer and filmmaker Julian BraveNoiseCat, who shares how smoking weed with his father, Ed Archie NoiseCat, a renowned Indigenous artist, became a profound healing experience. Julian's father, who struggled with alcoholism and was largely absent during his son's childhood after leaving when Julian was six, reconnected with Julian when Julian moved back in at 28 to research a documentary on Indian residential schools. During their nights playing "bong hit Scrabble" and sharing stories, Julian learned about his father's traumatic birth at St. Joseph's Mission, where he was found in a trash incinerator, a stark example of the systemic abuse and infanticide at these institutions that profoundly impacted generations of Indigenous families.

The practical takeaway is that confronting intergenerational trauma, even through unconventional means like shared cannabis use, can foster deep understanding and reconciliation between family members. Julian, on the cusp of becoming a father himself, realized that understanding his father's past, marked by the residential school system's devastating impact on parenting skills, was crucial to breaking cycles of pain and building a more present relationship with his own future child, despite his earlier fears of repeating his father's mistakes.

Father's Day, for many, conjures images of backyard barbecues, fishing trips, and heartfelt greeting cards. But for writer and filmmaker Julian BraveNoiseCat, the reality of his relationship with his father, Edwin "Ed" Archie NoiseCat, was far more complex, marked by absence, intergenerational trauma, and an unconventional path to healing that involved late-night sessions of "Bong Hit Scrabble." Julian's story, shared on the New York Times' Modern Love podcast, delves into the profound journey of understanding, forgiveness, and the hopeful breaking of cycles as he prepares to become a father himself.

The Unconventional Bonding Ritual

Julian's father, Ed Archie NoiseCat, is a larger-than-life figure—a renowned Native artist, a "style icon" with "rizz," and, as Julian affectionately puts it, "a good hang." Their unique bonding ritual often involved smoking weed and playing games, most notably "Bong Hit Scrabble," a peculiar blend of wordplay, mathematics, and cannabis consumption. Julian recounts his father's legendary (and often non-dictionary) words, like "slopify," highlighting a playful, trickster spirit that defined their interactions.

But beneath the laughter and the hazy camaraderie lay a deeper, more painful history. Julian didn't grow up with his father; Ed left when Julian was six or seven, a ghost-like presence who would "not show up very often" and sometimes disappear entirely for years. This absence left a profound wound, fueling Julian's anger and a deep-seated fear of repeating the same mistakes.

A Father "With the Wind": Childhood Scars

Julian's memories of his father from childhood are vivid but sporadic. He recalls watching his dad drive away, wondering when he'd see him again, or if he ever would. Ed, a "road warrior" with countless unpaid speeding tickets across North America, embodied a restless, almost mythical persona. Julian recounts a particularly striking memory from age 12, driving with his dad who was speeding, blasting Mike Jones, and confidently declaring, "Son, I have Crazy Horse medicine. The cops can't see me. They can't catch me."

While Julian knew his dad was "full of shit," he also couldn't fully disbelieve the sentiment. There was an otherworldly quality to Ed, a sense of magic and survival that defied logic. This duality—admiration for his father's charisma and resilience, coupled with the pain of his abandonment—defined Julian's early years. His mother even prepared him at 12 for the "real possibility" that his father might die, a stark reflection of Ed's self-destructive streak and struggles with alcoholism.

By adolescence, Julian actively sought to be "nothing like" his father. He recognized Ed's immense artistic talent but also saw how "all this stuff that he haven't dealt with," particularly his drinking, consistently "got in his own way." The fear of inheriting this "Achilles' heel" and becoming the same kind of absent father became a driving force for Julian. At 16, he confronted his father, a tearful outpouring of anger and pain over the abandonment, though he admits his father's history of survival often served as a "justification" for his actions.

Unearthing Intergenerational Trauma: The Residential School Legacy

The turning point in their relationship came when Julian, at 28, decided to move back in with his father. He was working on a book and a documentary, Sugarcane, which explored the legacy of Indian residential schools in Canada. The 2021 discovery of 215 potential unmarked graves at an Indian residential school in Kamloops sparked an international reckoning, and it resonated deeply with Ed. Julian's father had grown up on the Canim Lake Indian Reserve in British Columbia, and there was a long-standing rumor that he had been born in Williams Lake and "found in a dumpster."

Through his research for Sugarcane, Julian uncovered the shocking truth of his father's birth. Ed was born at St. Joseph's Mission, a residential school, on August 16, 1959. His grandmother, who had attended the school and was working there as a nurse, hid her pregnancy. After the baby was delivered, it was found in the trash incinerator. This infant, "Baby X" in the Williams Lake Tribune, was Julian's father. The newspaper, even in 1959, questioned the "procedures and policies and practices at this institution" that could lead a young mother to such an act. Julian's documentary revealed a pattern of infanticide at the school, highlighting the horrific realities of these institutions.

Julian painstakingly explains the devastating ripple effects of these schools: "kids who were taken away, who were abandoned when they were kids, turned around and they didn't really know how to be parents." This cycle of trauma, violence, and abuse explained much of his father's struggles, including his alcoholism and his inability to be a present parent. Understanding this history provided crucial context for Ed's actions, allowing Julian to begin to unravel the complex tapestry of their relationship.

The Coyote's Shadow: A Cultural Lens for Understanding

Living and working alongside his father, Julian observed Ed's creative process—carving to Led Zeppelin, taking bong rips, a "vibe" that contrasted sharply with Julian's solitary writing. During this time, Julian delved into his own Indigenous culture, studying the trickster coyote, the first ancestor of his people. This figure, a "patriarch figure from the beginning of time who made the world... but was a trickster, and so he messed a lot of stuff up," resonated deeply. The coyote was a "creator destroyer survivor deadbeat dad."

Suddenly, looking from his laptop to his father in the carving studio, the connection clicked: "My father is the trickster coyote." This realization provided Julian with a language, a narrative, and a character that helped him understand his father's complexities—his charisma, his resilience, his talent, and his profound flaws. It was a way of understanding his dad that also helped him reclaim something lost by the residential schools, connecting his personal pain to a broader cultural narrative. While Julian acknowledges that this "coyote" lens might also offer his father "a way out" of accountability, he believes it "deepens the truth of the whole thing," recognizing the ancestral patterns that manifest in human lives.

An Apology and the Hope for a New Generation

It wasn't until after Julian's book was published, and his father finally read an advanced copy, that the long-awaited apology came. Ed expressed understanding for the pain he had caused and apologized for it, also sharing his immense pride in Julian's artistic achievement. Julian sees his own art-making, though different from carving, as an echo of his father's legacy, fulfilling a desire for sons to become "little versions of them out in the world."

Now, Julian BraveNoiseCat is about to become a father himself, welcoming a son at the very same age his own father was when Julian was born: 33. This serendipitous timing adds another layer of significance to his journey. He admits to a deep-seated fear of repeating his father's mistakes, of "messing things up" and not being present. Yet, he holds onto the hope of "getting it right," of making "fewer mistakes than the last generation," and ultimately, of "bring[ing] our people back from the genocide."

Julian dreams of a "magical relationship" with his son, filled with cultural activities—hockey, dancing, and, most poignantly, bringing his son into the studio to sit with "his Ed" and learn to carve, hoping the artistic legacy will "skip a generation." When asked how he counters his fears, Julian humorously admits, "I usually take out a pre-roll." But he also looks at the "fullness of the story with my own father," a narrative that has transformed from one of "brokenness and pain" to one of "love and repair." Their relationship, despite the messiness and past transgressions, has become one where they are "best friends," making "little coyote trickster adventures of our own, in a beautiful way."

Julian believes his father will be an "amazing grandparent," a "rock" who will "nail it" in his "pa era." Indeed, in April of this year, Julian and his partner, Joan, welcomed their son, Copper Alexander Martin Noise Cat, a "little bear of a kid." Ed Archie NoiseCat was present in the delivery room, perhaps the most nervous person there, witnessing the continuation of a lineage now steeped in both historical pain and profound hope. Julian's story is a powerful testament to the enduring human capacity for healing, the complex interplay of personal and cultural identity, and the transformative power of love across generations, even when the path is unconventional and paved with smoke.

Based on "Are you anxious, avoidant, or secure? | The Gray Area" from Vox Watch the original video

The Hidden Power of Secure Attachment: Rewriting Your Relationship Story

Episode summary

Vox's "The Gray Area" features Amir Levine, author of Secure, who asserts that attachment styles (anxious, avoidant, secure, fearful-avoidant) are not fixed categories but a spectrum, changeable throughout life. He cites a 30-year longitudinal study showing parental behavior contributes only 3% to adult attachment style, while early friendships contribute 11%, challenging the notion that childhood dictates adult attachment.

Levine argues that feeling secure is about establishing a "social baseline" of safety, which is achievable through "secure priming therapy." This involves identifying and focusing on "secure kernels"—past or present positive relational experiences often overlooked—and rewriting self-defeating "scripts." He emphasizes that seemingly insignificant micro-interactions, like a non-response to a text, are crucial, as the brain, wired for tribal survival, interprets social exclusion (the "cyber ball effect") as a threat, regardless of conscious reasoning.

We are inherently social creatures, wired for connection. This fundamental need shapes our experiences of both profound suffering and deep healing. At the core of this human experience lies our attachment system – an intricate hierarchy in our brains that dictates how we seek comfort, navigate intimacy, and respond to perceived threats in our relationships. As Dr. Amir Levine, a psychiatrist and neuroscientist, explains, a single word or a hug from someone with whom we share a secure attachment has a power no medication can rival, instantly making us feel better. Conversely, insecure relationships are often the most potent instigators of emotional distress. Understanding and cultivating secure attachment, therefore, isn't just about better relationships; it's about the very basis of our well-being.

Decoding Your Attachment Style: Anxious, Avoidant, or Secure?

Initially identified in babies, attachment styles are now understood to persist throughout our lives, profoundly influencing our adult relationships. Dr. Levine, co-author of the influential book Attached, and now Secure, breaks down the primary styles based on two dimensions: our comfort with intimacy and our sensitivity to potential danger in a relationship.

Beyond Labels: Attachment as a Dynamic Spectrum

While these categories provide a useful framework, Dr. Levine emphasizes a crucial, hopeful insight: attachment is not a fixed trait. "It's not like a category that we fall into. It's a spectrum," he asserts. We can exhibit different attachment styles with different people, and importantly, we have the capacity for change. This understanding forms the bedrock of his new work, Secure, which posits that "we can all learn to live in secure mode."

Security, in this context, is less about the absence of anxiety and more about stability. It's our brain's quest for a social baseline, a "safe baseline," much like a biological system striving for homeostasis. Dr. Levine's new questionnaire helps individuals map their "attachment topography," providing a personalized understanding of their social world from which to build a "roadmap to greater security."

The journey to security involves understanding the "secure brain"—what it needs to feel safe and what makes it insecure. Many societal norms, Dr. Levine suggests, are actually misaligned with the fundamental needs of our social brains, contributing to widespread insecurity.

Challenging the Past: The Limited Influence of Childhood

One of the most surprising and liberating insights from Dr. Levine's work is the re-evaluation of childhood's causal role in adult attachment. While traditional therapeutic narratives often trace adult patterns directly to early experiences, Dr. Levine, who pivoted from psychotherapy to molecular neuroscience, questions this neat causality. "When I became a scientist, I discovered how hard it is to establish causality," he explains.

Recent longitudinal studies, some following individuals for 30 years, reveal a surprisingly small impact of parental behavior on adult attachment style. Maternal effect, for instance, contributed only about 3%. Early childhood friendships showed a slightly higher influence at 11%. This isn't to say childhood experiences are irrelevant, but rather that the "causal weight" often placed on them might be "too neat."

The danger of overemphasizing childhood causality, Dr. Levine argues, is that it can lead individuals to feel "damaged goods" and unable to change. Instead, he highlights that "a lot of the change that happens happens if we actually change the brain, change the environment for the brain in the here and now." This perspective shifts the focus from an unchangeable past to the empowering potential of the present.

Rewriting Your Story: The Power of Secure Kernels

Attachment styles, Dr. Levine explains, are essentially "scripts" we tell ourselves about ourselves and our relationships: "I can't trust anyone," or "I can't say anything because the relationship will break up." Our brains, sophisticated machinery that they are, then actively seek out evidence to reaffirm these scripts, often ignoring contradictory information.

Secure Priming Therapy aims to disrupt this cycle by helping individuals identify "secure kernels"—those past or present experiences where they felt truly safe and connected. Dr. Levine shares a personal anecdote of a vacation with his sister and her "very, very secure" friend's mother, Ruth, a memory he frequently returns to for its warmth and security. "Many of us have those experiences," he notes, "but our brain chooses to ignore them or they don't take center stage." The therapy encourages refocusing on these secure occurrences, "summoning out that potential that I believe resides in the vast majority of us."

We are, as the host observes, "narrative creatures," and while this allows us to make sense of the world, it can also become a curse when we cling to stories that make us miserable. The ability to rewrite these internal scripts is key to cultivating greater security.

The Sting of Exclusion: Our Deeply Social Brain

Why do seemingly minor social slights, like being ignored or ghosted, sting so much? Dr. Levine points to the powerful and often unconscious workings of our "social brain." He illustrates this with the "Cyberball effect," a series of experiments where participants playing a virtual game of catch are suddenly excluded by the other players. Even when offered money for exclusion or told the other players are members of a despicable group like the KKK, the brain's response is consistent: areas associated with painful distress and self-scrutiny light up. Psychologically, it leads to decreased self-esteem, a reduced sense of control, and a feeling that life is less meaningful.

This profound reaction, Dr. Levine explains, has deep evolutionary roots. His experience on an African safari provided a vivid analogy: walking single file, guides constantly urged the group to "close the gap" between them. A gap meant vulnerability, an opening for predators. Similarly, for our emotional brain, formed in a time when tribal belonging meant survival, being ostracized was literally a matter of life or death. Our brain, therefore, interprets social exclusion, even minor slights, as a significant threat, activating ancient survival mechanisms. "The brain's not making any distinctions here," between a life-or-death threat and a friend not calling back for three days, he notes.

Building a Secure Life: The CARP Framework

If exclusion is so potent, what nurtures security? Dr. Levine introduces the CARP acronym, representing the five pillars of a secure life: Consistent, Available, Responsive, Reliable, and Predictable.

He discovered the power of these elements through "reverse Cyberball" experiments, where individuals are "hyper-included" (e.g., always receiving the ball). This experience leads to increased self-esteem, a greater sense of control and meaningfulness, reduced inflammation, and even greater longevity. The CARP framework aims to replicate this hyper-inclusion in real-life relationships.

Predictability, in particular, is often misunderstood. It's not about being boring, but about being a steady presence. Just as a baby occasionally checks for a parent's presence to feel safe enough to play, adults need "momentary check-ins" to ensure the "thread that connects us" is still intact. When this thread feels secure, the relationship fades into the background, providing a stable foundation for life. Unpredictability, conversely, triggers the brain's radar, leading to self-scrutiny and anxiety.

These "seemingly insignificant minor interactions of everyday life" are incredibly important for the brain to register and build a secure mode.

Navigating Relationships: Rules for Secure Engagement

For those seeking to cultivate more secure relationships, Dr. Levine offers two key "rules of secure engagement," rooted in understanding attachment logic:

  1. Only one person is allowed to be upset at a time: This rule acknowledges that secure relationships are fundamentally about helping each other feel calmer. When one person is distressed, the other's role is to provide comfort and support, not to become upset themselves. This mutual commitment to emotional well-being is the hallmark of a secure bond.
  2. The Mia Kulpa Rule (Fallback Rule): If both individuals become upset, both must apologize. This isn't about who is "right" or "wrong," but about acknowledging that the "covenant of a secure bond" – the shared responsibility for each other's emotional well-being – has been momentarily broken. Prioritizing emotional resolution and reconnection over winning an argument allows the attachment system to settle down. "If you apologize and you can connect, then tomorrow you can discuss who's right and who's wrong," Dr. Levine advises.

Practical Tools for Managing Insecurity

For individuals with anxious attachment, Dr. Levine identifies a common pattern: the Protest-Regret Cycle. This involves lashing out when feeling insecure, leading to defensiveness from the partner, creating distance. The anxious individual then regrets the outburst and apologizes, but the apology focuses on the lashing out, not the underlying "non-CARP behavior" that triggered the initial distress. This perpetuates a loop where genuine attachment needs are never addressed.

To break such cycles and "rightsize" relationships, Dr. Levine offers a tool called Wall Tennis with Love. When dealing with a friend or partner who is often inconsistent or unresponsive, the anxious individual becomes "the wall." They respond immediately and lovingly when the other person initiates contact, maintaining the attachment thread without initiating too much themselves. "Whatever you dish the wall, the wall will return with maybe a tiny less velocity in the same direction. It never initiates," he explains. This strategy prevents the anxious individual from experiencing the "Cyberball effect" of unreturned texts or calls, allowing their attachment system to stay quiet, achieving the desired "homeostasis."

The Promise of Change: Agency Over Fate

The message is clear: we are not trapped by our past or by labels like "anxious" or "avoidant." While the host reflects on wishing he had this information earlier in life, Dr. Levine affirms that change is always possible. "Didn't you just say that change in your 30s and you were able to do more?" he playfully challenges.

The journey to greater security begins with acceptance. "Accepting okay, this is my biology, this is the animal that I am. Now how do I work with it to actually find a place that's more convenient and that feels good to me?" This self-knowledge, combined with a willingness to reorganize our social environment and practice new behaviors, empowers us to cultivate security. It's about agency, not fate. By understanding the deep-seated needs of our social brain and applying practical strategies, we can genuinely rewrite our relationship stories, fostering deeper connections and a more secure, fulfilling life.