This is Behind the Blog, where we share our behind-the-scenes thoughts about how a few of our top stories of the week came together. This week, we discuss the Madonna-whore algorithm, reader tips, and jazz.
SAM: Yesterday morning I published a story I started working on weeks ago and only in the last week or so felt enough distance from the topic to be able to articulate it clearly: My year in the wedding planning social media abyss. The piece is a long, more sourced BTB, and I don’t have a ton to add to what’s said in it, but I do want to highlight some of the comments I’ve gotten so far that touch on things the story doesn’t elaborate on.
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The remnants of a bizarre long-lost world that fell apart before our planet was fully formed are falling to Earth in the form of meteorites, according to a new study in Earth and Planetary Science Letters.
For decades, scientists have puzzled over the origin of angrites, a rare class of about 70 meteorites with unique volcanic compositions that suggest they were forged in a large ancient object with differentiated layers, including a metallic core and a magma ocean.
Scientists have long assumed that this object, the so-called angrite parent body (APB), was roughly a few hundred miles across, similar in size to the asteroid 4 Vesta. But researchers recently raised the tantalizing possibility that the APB might have been much larger, perhaps on the scale of Earth’s moon.
Now, a team led by Aaron Bell, an experimental petrologist and an assistant research professor at the University of Colorado, Boulder, has discovered “the first unequivocal evidence supporting the large angrite parent body hypothesis, which posits that the angrites are samples derived from a protoplanet that was catastrophically disrupted during the earliest evolutionary stages of the inner solar system,” according to the new study.
“It probably got destroyed in the early solar system, so [angrites] are remnants of a lost protoplanet,” Bell said in a call with 404 Media. “A few pieces broke off and are now in the asteroid belt, and a few of them have come to Earth, and we’ve picked them up.”
Angrites date back about 4.56 billion years, making them among the oldest known volcanic rocks. They belong to a class of stony “achondritic” meteorites that contain the crystalized signatures of melted rock, such as basalts, hinting that they originate in larger bodies that underwent some degree of planetary processing and layered differentiation, even if those early planetary embryos never accreted into full planets.
“Angrites are interesting in that they don’t have a known parent body,” Bell said. “It’s never been definitively identified, and that’s one of the mysteries.”
“There are a bunch of arguments about why angrites are so geochemically unusual,” he added. “They’re kind of this oddity.”
Most models of early planetary accretion predict that relatively small objects formed within the first few million years of the solar system, which is why the APB was assumed to be an asteroid-sized object, rather than a much larger nascent planet.
While working on a previous study, Bell became interested in an aluminum-rich angrite from Northwest Africa, known as NWA 12,774, which was classified in 2019. The meteorite is one of a handful of unusual primitive angrites that appear to have been crystallized at high pressure within the APB, indicating that it formed deep under the surface and therefore might shed light on the size of this bygone world.
“Even among angrites, there’s only four or five that have these primitive compositions,” Bell said, adding that the meteorite had “off-the-charts aluminum content, which is really very unusual.”
Bell and his colleagues developed a geobarometer—a tool that calculates the pressures at which rocks and minerals formed—-that estimated it would take at least 1.7 gigapascals to account for the rock’s special properties. This pressure corresponds to an object with a minimum radius of 620 miles (1,000 kilometers), which is just under the size of Pluto. The APB may even have been as large as the Moon, which has a roughly 1000-mile radius.
“Clearly, within the first few million years of solar system evolution, you could grow planetary embryos that were 1,000-plus kilometers” in radius, Bell said. “We’re talking within three million years of the condensation of the first solids in the solar system, so it’s right at the beginning.”
The discovery suggests that the APB may have been a first-generation protoplanet that coalesced and shattered millions of years before the familiar worlds of our solar system took full shape. Judging by the strange properties of angrites, the APB was also on track to be a very different kind of world than Earth and its neighbors, had it survived the chaotic environment of its infancy.
Angrites are “geochemically fundamentally different, and that’s why people were interested in the first place—because they were odd,” Bell said. “They don’t look like garden-variety
basalts you get from Mars or the Moon or Earth.”
“It’s sort of this path not taken—or maybe it was, but we just have a couple pieces of it that tell us something we didn’t know,” he concluded. “There were once large bodies that, maybe, didn’t look like the terrestrial planets.”
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On Wednesday the Federal Aviation Administration rescinded a temporary flight restriction (TFR) that created a no-fly zone within 3,000 feet of “Department of Homeland Security facilities and mobile assets.” The new restriction softened the language of the original and abandoned the threat of civil or criminal penalties but added the Department of Justice to the list of protected agencies.
A 2025 TFR restricted the presence of drones around Department of Energy and Pentagon assets. The FAA added ICE and CBP to the list of restricted agencies in January as ICE began operations in Minneapolis. The no-fly zone covered 3,000 feet around any ICE vehicle. Anyone who was caught violating it could be fined or jailed. Because ICE agents often drive through the city in unmarked vehicles it was impossible for drone operators to know if they were violating the order and local journalists who use drones to take pictures and monitor law enforcement activities were grounded.
Earlier this month, Minnesota journalist Rob Levine sued the FAA over the TFR. In a motion filed earlier this week, Levine’s lawyers argued that the FAA had violated his rights and should rescind the restrictions. Core to their argument was the unmarked vehicles which they said created a “flotilla of invisible, moving bubbles,” according to court documents. “Under any standard, the TFR’s chilling sweep violates the First Amendment as applied to the Petitioner’s use of drones in photojournalism.”
The FAA replaced the TFR this week after Levine’s lawyers filed the motion. The new advisory lessened restrictions, including dropping the language around 3,000 feet and criminal penalties, but expanded the amount of protected assets.
“UAS operators are advised to avoid flying in proximity to: Department of War, Department of Energy, Department of Justice, and Department of Homeland Security covered mobile assets,” the new TFR said. “UAS operators who fly within this airspace are warned that…DOW, DOE, DOJ, or DHS may take action that results in the interference, disruption, seizure, damaging, or destruction of unamended [aircraft] deemed to pose a credible safety or security threat to covered mobile assets.”
Despite the threat to shoot journalist’s drones out of the sky, Levine and his lawyers see the new TFR as a victory. “This is a big win. It was heartbreaking to have my drones grounded at a time of such importance to my community, but I’m looking forward to getting back up there and getting back to my journalism as soon as possible,” Levine said in a statement provided to 404 Media.
Grayson Clary, a lawyer with Reporters Committee for Freedom of the Press who took on Levine’s case, said there is still work to do. “We’re glad to see the FAA rescind its original order, which was an egregious overreach that had serious consequences for reporters nationwide. But this kind of arbitrary back-and-forth from the FAA is exactly the problem, and we intend to make clear to the D.C. Circuit that this restriction never should have been implemented in the first place,” he said.
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Welcome back to the Abstract! These are the studies this week that peacefully passed the crown, predicted trouble on the horizon, gave life after death, and coastally shelved an idea.
First, scientists watch a succession story play out for years in a naked mole rat colony. Then: prediction markets as a public health threat, the thorny questions of posthumous reproduction, and a walk on the shores of an ancient alien seas.
Murderous queens. Bloody power struggles. Strictly enforced hierarchies. I’m speaking, of course, of naked mole rats, a bizarre species of rodent that becomes embroiled in violent conflicts over the succession of one breeding queen to the next.
Though aggression in succession is the norm for these animals, scientists now report a rare peaceful transition of power from one queen to her daughter in a captive colony.
The discovery suggests that “the less common peaceful trajectory to queen succession…is possible under some conditions” especially when “aggression-based enforcement may be insufficient or unnecessary and when the cost of a ‘war’ may be too high,” according to the new study.
As we’ve covered before on the Abstract, mole rats (both the naked kind and the non-naked kind) are the only mammals to live in eusocial colonies similar to bees or ants, meaning they are reigned over by one breeding queen and her subordinate workers. In addition to this unique social structure, mole rats display a number of fascinating behavioral and genetic adaptations, including long lifespans and low rates of cancer, which has made them a popular species for research.
Naked mole rats may not look all that intimidating, but when it’s time to anoint a new queen, the fur starts to fly (or it would, if these animals had any fur). If a queen dies or is deposed by rivals, subordinate females in the colony battle to take the throne.
But scientists co-led by Shanes Abeywardena and Alexandria M. Schraibman of the Salk Institute for Biological Studies observed a different succession story that unfolded over many years in the Amigos captive colony housed in San Diego.
Starting in 2019, a queen named Teré reigned over the colony and produced many healthy pups. Once the colony became crowded, with nearly 40 members, Queen Teré began delivering litters with no surviving pups. When the researchers removed half of the members, she began to produce surviving pups again, though not many. The team then deliberately introduced another stressor by moving the colony to a new facility in 2022, which ceased Queen Teré’s fertility.
In response, Alexandria, one of Teré’s daughters, became pregnant in 2023 and 2024, but her litters also produced no survivors, and she had to be euthanized in 2024 due to a uterine torsion. Finally, the long reproductive hiatus was ended after three years by the ascension of Alexandria’s sister, Arwen, who became Queen Arwen upon her delivery of healthy pups in October 2025.
“Aside from a single incident on 6 February 2025 in which one animal was found with a superficial bite wound and dried blood around the face, an injury that resolved without recurrence, no aggression or dominance related conflict was observed,” the researchers said. “Instead, Queen Teré was reported to exhibit ‘guarding’ behavior of Arwen and her litter. No other signs of social instability, behavioral escalation, or colony-wide distress were documented.”
“Together, these observations indicate that following the decline of Queen Teré’s reproductive capacity and the loss of the intermediary breeder Alexandria, Arwen successfully assumed the reproductive role without eliciting aggression from the reigning queen or from other colony members,” the team concluded.
The study is an antidote to the story we covered last week about a lethal chimp “civil war,” demonstrating that animals with strict dominance structures choose peace over violence in some cases. My only note is that Teré’ be given the honorific Queen Mother for her service.
Prediction markets (PMs) are exploding in popularity, but researchers warn that the “addictive design, vulnerable users, and permissive regulatory environments” that characterize these markets “are a well-established formula for population-level harm,” according to the Policy Forum section of the journal Science.
PMs operated by companies like Kalshi or Polymarket “pose underappreciated threats to democratic integrity” and are linked to “addictive behaviors,” according to authors Nizan Geslevich Packin of Baruch College Zicklin School of Business and Sharon Rabinovitz of the University of Haifa. For instance, PMs can enable insider trading about classified government information and expose millions of users to the risk of addiction and major financial losses.
“A public health approach reframes PM risks as predictable outcomes of environmental design, analogous to tobacco control’s success in treating smoking as population-level exposure rather than individual vice,” the team argued in the article.
“The window for precautionary action is closing,” the researchers emphasized. “Each week of billion-dollar PM activity…prolongs a large uncontrolled experiment on users.”
It remains to be seen whether this warning about the dangers of a wild new industry will materialize into meaningful regulatory action. Want to make a bet?
Posthumous children—children born after the death of one or both parents—are popular in myth and fiction, from the Greek Dionysus to more modern characters like John Connor or Daenerys Targaryen.
But this is also a real demographic of people that may evolve in interesting ways as reproductive technologies enable larger numbers of posthumous conceptions—in which the sperm and egg donors for an embryo may be deceased, such as the case of a boy born in 2018 whose mother and father had both died years earlier in a car crash.
In this way, “frozen sperm, eggs (or embryos) are, at one and the same time, both alive and dead,” said Sandra Bamford of the University of Toronto in a new anthropological study of the topic. “Through their frozen gametes and the potential of new kin connections in the future, the dead remain as active participants influencing the lives of the living.”
The study, which is part of a broader journal issue exploring kinship, pulls together many intriguing case studies, including the “Nuer ghost marriage” practices of Sudan, in which a deceased man can be considered the father of a kinsman’s children, or the case of William Kane, who bequeathed frozen sperm to his girlfriend, sparking a legal battle with his adult children after his death by suicide.
In other words, the legal, ethical, and practical implications of posthumous conception are still very much in flux, raising thorny questions about when, and how, the dead can produce new life. For instance: the ambiguities over judging the consent of a deceased person over the use of their posthumous gametes; the rights of posthumously conceived children to be named heirs of estates; and the possible emotional and psychological toll on posthumously conceived children, along with their family members.
We’ll close, as all things should, with waves lapping on long-lost alien shores. The surface of Mars is etched with the memory of rivers, lakes, and perhaps even an expansive ocean that may have covered much of its northern hemisphere between three and four billion years ago.
Scientists have already mapped out the rough contours of what may be an ancient Martian shoreline, but a new study throws the seas into sharper relief by identifying topographic signs of a possible coastal shelf. The team argued in their study that these shelf features may be a better indicator of a past ocean than shoreline features, based on similar observations on Earth.
An illustration taken from orbiter data identifying the coastal shelf region on Mars. Image: A. Zaki
“Our results indicate that long-lived ancient oceans on presently arid planets may be best identified not only through discrete shorelines but also through…a global coastal shelf,” said researchers led by Abdallah Zaki and Michael Lamb of Caltech University. The study supports “the presence of an ancient ocean on the northern plains of Mars that was bounded by a coastal shelf.”
While this ocean dried up long ago, its topographic remnants are a reminder of a time when Mars was warm, wet, and perhaps, wriggling with life.
It created order through modern warehouses and declarative modeling tools. Dashboards became trusted, lineage was visible, and metrics were version-controlled.
Over time, it gained traction through communities like dbt Labs, where it was established as a discipline focused on documentation, reproducibility, and testing best practices.
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For many, analytics engineering felt closer to software engineering than traditional reporting.
With the arrival of Artificial Intelligence, the focus shifted from describing the past to predicting the future.
Systems began generating new outputs and working with probabilities rather than fixed answers. Instead of deterministic SQL queries, teams began working with uncertainty. Compared to the clean, predictable nature of dashboards, AI systems feel fundamentally different.
This was the turning point.
Analytics engineering prepared me to build reliable reports. AI requires building intelligent systems. That shift demands a full-stack mindset.
Analytics engineering foundations: What we were trained to optimize
The data warehousing tradition was the foundation of analytics engineering.
We learned to prioritize clarity of structure and dimensional modelling, drawing from texts like The Data Warehouse Toolkit. The goal was consistency and trust, where the same SQL query would always produce the same result.
This determinism became the basis of stakeholder confidence. It worked because it created stability and shared understanding across teams.
However, it also introduced a set of assumptions:
Transformations are rigid
Answers are exact
The world is structured
AI challenges each of these assumptions.
The mindset gap: Deterministic pipelines vs probabilistic systems
Machine learning operates on probability, while analytics engineering is built on certainty.
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A dashboard might report revenue as $1.2m. A model, on the other hand, might predict a 72% probability that a customer will churn. One is definitive, the other is contextual.
Research from Harvard Business Review reinforces this shift. Thomas H. Davenport and Rajeev Ronanki explain that successful AI systems deliver value within constraints, with usefulness taking priority over perfection.
This reframes what “correct” means.
Instead of asking whether something is correct, teams focus on:
Performance improvement
Comparison to a baseline
Value delivered to users
As a result, fixed validation gives way to experimentation. Metrics become distributions rather than absolutes, and progress is measured iteratively. For engineers used to deterministic systems, this shift can feel unfamiliar, yet it becomes essential.
The data problem gets harder: Messy inputs, drift, and continuous quality
AI introduces a level of complexity that structured analytics rarely encounters.
Data extends beyond clean tables to include logs, images, and unstructured text, all of which require ongoing interpretation and engineering. This data also evolves over time.
In traditional analytics, issues like null values or broken schemas were visible and relatively easy to diagnose. In AI systems, challenges emerge more subtly. Models can degrade while systems appear to function as expected.
Distributions shift.
User behavior evolves.
Language changes.
Simple checks such as row counts provide limited coverage in this context.
Modern AI systems require continuous monitoring and active data management. As Bernard Marr highlights, value from AI comes from actively governed data.
Data quality becomes an ongoing responsibility.
New responsibilities: From transformation to models and MLOps
In analytics, pipelines end at insight. In AI, they extend to action.
This shift introduces a new set of responsibilities:
Model deployment and rollback
Training and evaluation
Monitoring predictions in production
Ensuring training consistency
The lifecycle becomes continuous rather than static.
Guidance from Google formalizes this approach under MLOps, where models are treated as production systems.
Frameworks like the ML Test Score, developed by Eric Breck, provide structured ways to assess readiness and manage risk.
The risks are well documented. D. Sculley shows how quickly complexity builds in machine learning systems when pipelines are fragile or loosely defined.
Over time, shortcuts accumulate and systems become unstable.
ML systems are engineering problems, as well as data challenges.
The full-stack reality: Infrastructure, product, and human trust
As soon as models are embedded into applications, the scope expands.
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Concerns such as latency, cost, and scalability become central. Real-time systems and APIs become part of the data workflow. At this point, work extends beyond reporting into product development.
Trust also becomes a defining factor.
Dashboards present verifiable numbers. Models make decisions that impact users. This introduces new expectations around transparency, bias, and accountability.
Trust becomes something that is designed, measured, and maintained alongside technical performance.
Conclusion
Analytics engineering provided strong foundations in lineage, reproducibility, testing, and discipline.
AI builds on these foundations while introducing uncertainty, continuous change, and new system-level challenges.
The boundaries between engineering, analytics, and product continue to converge. Data professionals increasingly think across the full stack, from data models to real-world impact.
The goal is to extend analytics engineering.
From clean dashboards to intelligent systems. From static pipelines to adaptive ones.
This is the shift AI demands, and it highlights the gap that analytics engineering alone did not fully address.
References
Eric Breck, Polyzotis, N., Roy, S., Whang, S., & Zinkevich, M. (2017). The ML Test Score: A Rubric for ML Production Readiness.
Thomas H. Davenport, & Rajeev Ronanki (2018). Artificial Intelligence for the Real World. Harvard Business Review.
Google (2020). MLOps: Continuous Delivery and Automation Pipelines in Machine Learning.
Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit. Wiley.
Martin Kleppmann (2017). Designing Data-Intensive Applications. O’Reilly Media.
Bernard Marr (2021). Data Strategy: How to Profit from a World of Big Data, Analytics and AI. Kogan Page.
D. Sculley et al. (2015). Hidden Technical Debt in Machine Learning Systems. In Neural Information Processing Systems Proceedings.
The difference between a developer who gets mediocre results and one who ships faster than ever comes down to one thing:
How well they have set Claude up to succeed.
Claude Code works best as a smarter collaborator. It’s closer to onboarding a new engineer, one who needs context, structure, and clear boundaries to do their best work.
