🌀🗞 The FLUX Review, Ep. 212

October 23rd, 2025

“FCP-212” // Photo: MK with Midjourney

Episode 212 — October 23rd, 2025 — Available at read.fluxcollective.org/p/212

Contributors to this issue: Ade Oshineye, Erika Rice Scherpelz, Neel Mehta, Boris Smus, MK

Additional insights from: Ben Mathes, Dart Lindsley, Jasen Robillard, Justin Quimby, Lisie Lillianfeld, Robinson Eaton, Spencer Pitman, Stefano Mazzocchi, Wesley Beary, and the rest of the FLUX Collective

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We’re a ragtag band of systems thinkers who have been dedicating our early mornings to finding new lenses to help you make sense of the complex world we live in. This newsletter is a collection of patterns we’ve noticed in recent weeks.

“If men use their liberty in such a way as to surrender their liberty, are they thereafter any the less slaves? If people by a plebiscite elect a man despot over them, do they remain free because the despotism was of their own making?”

— Herbert Spencer

📣💂Good definitions gatekeep

Back in February, Andrej Karpathy coined the term “vibe coding” for using LLMs to produce working code without caring about the code itself. The only requirement was that it should function, even if it was janky or mystifying under the hood. The term caught on, and soon it started getting used for any AI-assisted coding, from exploratory prototyping to meticulous software engineering.

It’s a classic case of conceptual drift. It’s natural… and often annoying to those who preferred the original scope. That’s because naming something isn’t just about communication. It’s about creating a boundary.

Good definitions gatekeep.

Not in the institutional sense — we’re not talking about standards committees. A good definition delimits. It draws a clear enough boundary around a concept so people understand what belongs and what doesn’t.

Sometimes a term is delineated by being clear. “Test-driven development” can mean many things, but much is clearly outside the boundary. Other times, it is delineated by being opaque, forcing you to verify the definition before you engage. Think of the phrase “the lethal trifecta” or “yak shaving.” You don’t know what it means until it’s explained to you.

Contrast either of these with something like “agile.” The term is immediately evocative and broadly appealing… which is also why it’s so vulnerable to drift. The word promises speed and responsiveness (and once upon a time, cachet). But ask ten teams what “agile” means and you’ll get ten different answers.

Given this, how do you choose the right kind of name for a new idea? It depends on what you’re optimizing for.

If your goal is to capture mindshare, broad and memorable can be assets. Terms like “agile,” “growth hacking,” or “AI-native” are compelling because they’re loose. People can project their own meanings onto them. Ambiguity invites participation.

If your goal is to communicate a specific mechanism, specificity wins. If you can find an unambiguous enough term, opt for clarity. “Test-driven development” is harder to misunderstand than “agile.” If not, go for narrowly scoped opacity. A term like “yak shaving” or “the lethal trifecta” may not be clear at first, but it points directly at the concept. Specificity creates tight mappings between terms and concepts.

That’s the tradeoff: drift versus adoption. The more legible and evocative your term, the more people will use it, but the less control you have over how. The more bounded your definition, the more consistent the interpretation, but the harder it is to spread.

Every definition draws a line between what the concept is and what it is not. That’s the gate. You can’t control language, but if you know your intent, you can try to point it in the right direction.

🛣️🚩 Signposts

Clues that point to where our changing world might lead us.

🚏🇮🇪 A deepfake video showed an Irish presidential dropping out of the race

An AI-generated video posted to Facebook and YouTube purported to be a clip from the popular Irish news channel RTÉ, showing a “clip” of Irish presidential candidate Catherine Connolly announcing her withdrawal from the race. The video also featured a studio scene in which a deepfaked anchor introduced the clip, and an outdoor scene in which an AI version of a well-known correspondent discussed the impact of her withdrawal, noting that the election would be “canceled” as a result. The fake clip racked up 30,000 views on Facebook before it was removed; it was also taken down on YouTube after the real RTÉ flagged it. (In the Republic of Ireland, the presidency is a primarily ceremonial office and holds little real power, but it’s still a nationally elected position.)

🚏🧺 AI startups are paying people to record themselves folding laundry

Robotics companies are keen to build AI-powered robots that can do humanlike tasks like making coffee or loading dishwashers, but they need a lot of training data to do so. So, some startups have started offering people money to record themselves doing mundane tasks like cooking dinner or folding laundry. They post ads on sites like Craigslist, saying they’ll pay $10–$25 an hour for videos of chores, but up to $150 an hour for more complex tasks like operating surgical equipment.

🚏🇨🇦 British Columbia will ban new crypto mining projects from the grid

Canada’s westernmost province has unveiled a plan to “permanently ban new cryptocurrency mining operations” from connecting to its electricity grid to “avoid overburdening” the system. (Off-grid mining setups would presumably still be allowed, though their high power demands would likely make that impractical.) BC will also limit the amount of electricity available to AI and data centers starting in January 2026.

🚏🚕 Uber will pay drivers up to $4,000 to switch to electric cars

In 2020, Uber pledged that all trips in Europe, the US, and Canada would be electric by 2030 as part of a push to go “completely carbon neutral” in those areas. But now that the US’s $7,500 federal EV tax credit—something that helped Uber drivers make the switch to electric—is expiring, Uber is stepping in to sweeten the pot. It’s offering a $4,000 grant to drivers in New York City, California, Colorado, and Massachusetts who get a new or used electric car. The choice of locations seems strategic, since some of these spots still offer state-level EV credits; Colorado and Massachusetts each offer $3,500–$6,000 rebates, and Massachusetts also offers an extra rebate for Uber, Lyft, and taxi drivers who go electric.

📖⏳ Worth your time

Some especially insightful pieces we’ve read, watched, and listened to recently.

• “Workslop” Was the Logical Outcome of Productivity Maxxing (Product Picnic) — Argues that many leaders’ simplistic desire to maximize outputs will incentivize employees to submit “workslop” (low-effort AI outputs passed off as human work). Instead of reducing the overall workload, this just pushes effort downstream to people who have to review the work. Their job is made harder by the “humanwashing” of the AI-generated slop; the reviewer can’t tell which parts of the output were generated by AI, so they have to review the whole thing painstakingly, hunting for hallucinations.

• A Post-Literate Society Is a Too-Literal Society (Paul Musgrave) — Argues that our modern society is (as many have observed) seeing a decline in literacy, but not in the “can’t physically read words” sense; rather, people are losing the ability to focus and engage deeply with a piece of media. In a world where every bit of content is designed to be consumed by audiences who are distracted or between other tasks, people expect media to be direct and repetitive; consider how many TV shows do mid-episode recaps or have actors literally explain what they’re doing out loud. In this world, subtlety, misdirection, and subtext are seen as hostile, confusing, and unnecessary.

• How AI and Wikipedia Have Sent Vulnerable Languages Into a Doom Spiral (MIT Technology Review) — Observes a vicious cycle that’s harming endangered and minority languages: AIs are trained on the limited, often error-filled online content in that language, and then AI is used to write new content in that language (such as Wikipedia articles), further poisoning the training data for that language. The only way out of the “garbage in, garbage out” trap is manual translation and a human community dedicated to preserving and growing the language.

• Silicon Valley’s Best Kept Secret: Founder Liquidity (Stefan Theard) — Examines the little-discussed practice where startup founders sell a portion of their shares during a new funding round. This enables founders to reduce the risk they take on, casting doubt on the attractive story that they are “all-in.” What this article doesn’t mention, though, are liquidity events for well-vested employees, which reduce risk for early employees as well.

🔍📆 Lens of the week

Introducing new ways to see the world and new tools to add to your mental arsenal.

This week’s lens: atomic tools.

A writer’s key tools often look like an incomprehensible mess to others. Perhaps it’s a folder with a mess of half-finished notes, interview templates, generic article outlines, and publishing checklists. No writing app could replicate it, but every piece they publish starts there.

The world is full of these sorts of highly personalized systems. Sometimes, they’re informal, like the folder of useful starting points. Sometimes they’re discrete tools, like a bash script you’ve extended over the years to handle a common workflow.

Following a term we discovered in Ep. 658 of the Changelog Interviews podcast, we call these tools atomic tools. Atom tools are tools we build for ourselves, for our own workflows. The quality standard of an atom tool is not polish or robustness. It’s fit. This tool exists to do precisely what you need, and nothing more. Atom tools tend to look rough from the outside, but they feel like extensions of mind.

By contrast, a world tool is built for others (perhaps including yourself). A world tool has to generalize. It may be used by millions or by specialists, but it is outward-facing. A world tool replaces fit with polish and generality. Our lives are saturated with world tools such as platforms, apps, and shared environments. Their prevalence teaches us to prioritize universality over personal resonance.

Atom tools remind us that we can reclaim the small, private layer of our systems. So take a look at something you have created in your life and consider how you can make it better. And look for opportunities where something general isn’t really fitting your needs and could use a little atomizing. Let yourself zoom in.

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