Language moves fast in tech, and mastery of new terms is usually the gateway to mastery of a given technology (or at least of being able to convince others you are a master of the tech), since grokking and competence are equivalent these days. Here are two terms I came across in the past month; I’m fascinated by them because they are cultural markers of where our tech is at a given moment in time.
The new slang term I learned for the AR/VR headset space is “Rectangle-pilling”. Can you guess what it means to be rectangle pilled?

The new slang term in AI / Vibe coding is “slopsquatting”. “Slopsquatting”, besides just being fun to say out loud, describes an exploit for a phenomenon in vibe coding where the LLM writes a code library for you that depends on another library you can download from github — except, said github repo does not actually exist. It is a hallucinatory repo. “Slopsqatting” is the practice of identifying these dream-repos (apparently the same ones come up a lot?) and creating an actual library to squat at the dream repo’s address. Then additional code, possibly malicious code, can be placed in the library. Or maybe just an unusual license. Or an IP pinger. At some point, an unsuspecting dev who has been told by his company to learn to vibe code will download the slopsquat code and push it out in an internal product. And then the trap snaps shut, whatever it is.

Efficiency means doing the same thing with fewer resources. In software, efficient code is faster, because that uses less compute. If some other software is waiting on yours to return, then your speed is saving upstream compute. Efficient data uses less space, which means less network bandwidth to move it around.

All this is very good, but getting that speed or compactness took effort. Someone got that process to work, and then someone wrote telemetry or tests to measure it, and then someone optimized code to get it there. Efficiency is expensive.

Therefore, efficient software is not the same as an efficient company–unless the software efficiency is important to the company’s business model.

Cat Swetel clarified this in her talk at Agile 2025: understand why your company cares about efficiency.

• Is it part of the business model?
• Trying to ride out hard times?
• or something else?

“Efficiency can be about hoarding or efficiency can be about access.” – Cat Swetel

Cat works at Nubank. Nubank serves millions of people who aren’t profitable for older banks, so older banks won’t (can’t) serve them. These are people with high transaction volumes and low balances. Nubank can only do this with super efficient transaction processing. It’s part of their business model.

Nubank is entirely on AWS, so they’re really good at optimizing cloud costs. For instance, they use a lot of Spot instances: cheaper than regular instances, but that computer can be taken away with 2 minutes’ notice.

With Spot, you pay less, but your infrastructure is less stable. The software has to compensate: services are quick to start up and shut down, and every part of the system handles ephemerality. Optimize for fault tolerance, not the happy path.

For Spot instances, Nubank does the upfront and ongoing work to cope with the instability and saved money on infrastructure. In another case, paying more for infrastructure saved money.

Their database, Datomic, has a local cache and an external cache. When transaction volumes shot up, the local cache ran out of space. Fetches from the external cache increased latency, slowing down all the services depending on this. Some of their spot instances happened to have an SSD, and they noticed that using that SSD to expand the local cache saved time (and therefore money) across the entire transaction flow. Numbers like: Spending $1 for SSD saved $3500 across the whole flow!

If each team minimized cost, then the database nodes wouldn’t add that SSD. Efficiency in the system is bigger than efficiency in the components. Nubank measures the cost of a flow, not a service. (They use honeycomb.io for this!)

Nubank learned: the Cost <-> Stability tradeoff isn’t. Instability is expensive! When fluctuations lead to scale-up, scale-down thrashing, efficiency is defeated. Building stable software on unstable infrastructure is expensive in development work, but the benefits of stability scale with their expanding demand.

Investing in software efficiency lets Nubank profit from customers that cost other banks money. They continually drive down cost per customer served, so they can serve more people. This is efficiency as business model.

If compute efficiency is not part of your business model, then it’s likely the investment in stability that it takes to work with spot instances won’t pay off. Instead, it could be a distraction from your core business. Does your product excel in user experience? In the complex legal knowledge built in? In traceability? in charm? Focus on these, until cost becomes a limiting factor. When you focus on efficiency, know why.

Last week the Guardian reported on "thousands of AI workers contracted for Google through Japanese conglomerate Hitachi's GlobalLogic to rate and moderate the output of Google's AI products, including its flagship chatbot Gemini... and its summaries of search results, AI Overviews." "AI isn't magic; it's a pyramid scheme of human labor," said Adio Dinika, a researcher at the Distributed AI Research Institute based in Bremen, Germany. "These raters are the middle rung: invisible, essential and expendable...." Ten of Google's AI trainers the Guardian spoke to said they have grown disillusioned with their jobs because they work in siloes, face tighter and tighter deadlines, and feel they are putting out a product that's not safe for users... In May 2023, a contract worker for Appen submitted a letter to the US Congress that the pace imposed on him and others would make Google Bard, Gemini's predecessor, a "faulty" and "dangerous" product This week Google laid off 200 of those moderating contractors, reports Wired. "These workers, who often are hired because of their specialist knowledge, had to have either a master's or a PhD to join the super rater program, and typically include writers, teachers, and people from creative fields." Workers still at the company claim they are increasingly concerned that they are being set up to replace themselves. According to internal documents viewed by WIRED, GlobalLogic seems to be using these human raters to train the Google AI system that could automatically rate the responses, with the aim of replacing them with AI. At the same time, the company is also finding ways to get rid of current employees as it continues to hire new workers. In July, GlobalLogic made it mandatory for its workers in Austin, Texas, to return to office, according to a notice seen by WIRED... Some contractors attempted to unionize earlier this year but claim those efforts were quashed. Now they allege that the company has retaliated against them. Two workers have filed a complaint with the National Labor Relations Board, alleging they were unfairly fired, one due to bringing up wage transparency issues, and the other for advocating for himself and his coworkers. "These individuals are employees of GlobalLogic or their subcontractors, not Alphabet," Courtenay Mencini, a Google spokesperson, said in a statement... "Globally, other AI contract workers are fighting back and organizing for better treatment and pay," the article points out, noting that content moderators from around the world facing similar issues formed the Global Trade Union Alliance of Content Moderators which includes workers from Kenya, Turkey, and Colombia. Thanks to long-time Slashdot reader mspohr for sharing the news.

Read more of this story at Slashdot.

1 The High Stakes of Email Delivery Email remains the backbone of digital communication for critical workflows: password resets, payment confirmations, fraud alerts, onboarding sequences, and service notifications. When you click "Forgot Password," you don’t think about queues, retries, or SMTP relays—you expect an email in seconds. But for the engineers behind the curtain, ensuring that message reliably reaches the inbox is anything but trivial. In this section, we’ll zoom out from code and APIs to understand why building resilient email delivery systems is not just a technical exercise but a business-critical mandate. Then, we’ll frame the architectural blueprint that guides every design choice in the sections that follow. 1.1 Introduction: Beyond "Fire and Forget" Too many teams still treat email as a “fire and forget” action: make an API call to SendGrid or Azure Communication Services (ACS), and assume the job is done. This mindset works for hobby projects and proof-of...

Donald Trump has never made his distaste for immigrants a secret. It's been a cornerstone of his political movement since he descended that escalator on June 16th, 2015 and started hurling racist vitriol in the general direction of Mexico and Mexican Americans. On the surface, his assault on the H-1B visa program seems like part of the White House's ongoing campaign to reduce the number of immigrants in the country. It might have that effect, but the biggest goal for Trump may not be forcing companies to hire more Americans or cutting down on the number of workers from India moving to the US. It's giving the government more leverage over his …

Read the full story at The Verge.

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