Hacker News, Distilled

Name Collisions and Project Naming

• Many comments focus on “Gemini overload”: Google’s AI, this protocol, and other uses make the word ambiguous.
• Several note this protocol predates Google’s LLM (started ~2019), so blame is split on who is “cluttering” search results.
• Broader gripe: tech naming in general is uncreative, collisions are inevitable, and big companies dominate name meaning (“Amazon” example).
• Tangent discussion on internal codenames, boring vs whimsical names, and the perennial difficulty of “naming things.”

What Gemini Is and How It Works

• Described as “modernized Gopher” or “a radically stripped down web stack.”
• Technically: a client sends a one-line textual request over TLS; the server returns a MIME-typed response or error, then closes the connection.
• Gemtext is a very simple, line‑based hypertext format, roughly like minimal Markdown; easy to implement and render nearly statelessly.
• Positioned between Gopher and the Web in complexity: heavier than Gopher, lighter than HTTP/HTML.

Philosophy and Appeal

• Core goals: simplicity, privacy, non‑extensibility, and defense against the modern web’s bloat, tracking, and JS-heavy pages.
• Fans enjoy “smallweb” vibes: cozy, low‑noise reading, often via desktop clients like Lagrange; some run gemlogs, social-style services, and even a Gemini “Wayback Machine.”
• The separate protocol acts as a gatekeeper: only people strongly motivated by minimalism and privacy tend to show up.

Discovery and Ecosystem

• Discovery works via search engines, directories, feed aggregators, and webring-like linking between “capsules.”
• There are multiple clients and servers, some HTTP proxies, and search/crawl projects indexing thousands of hosts and ~1M documents.

Design Choices and Controversies

• Strong restrictions: mandatory TLS, no inline images or embedded media, no inline links, no styling, no file size or range requests.
• Supporters say the value is in what you can’t do: no JS, no tracking pixels, trivially simple rendering, predictable UX across sites.
• Critics argue these constraints are “stupid by today’s needs,” make art and rich documents awkward, and limit adoption; several wish for HTML 2/4 + no JS instead.
• There is tension over clients that add optional features (favicons, auto-fetching images); some call this spec-violating, others see it as practical.
• Some complain about the per-request TLS handshake overhead and lack of connection reuse.

Critiques of Messaging and Broader Context

• Multiple readers say the front-page 100‑word intro is vague motivational fluff that doesn’t clearly convey “it’s a protocol + text format.”
• Broader lament about the modern web: browsers becoming “publishers’ agents,” DRM in HTML, erosion of user control, and speculation about attested, locked‑down future clients.
• For some, Gemini is a nostalgic, principled refuge; for others, it’s an unnecessary NIH reimplementation that Gopher or “simple HTML” already covered.

XSLT deprecation: usage, impact, and backward‑compatibility

• Many commenters see XSLT-in-browser as niche and “dead”; others show concrete uses: RSS/Atom and podcast feeds, sitemap and government/regulatory sites, XML-based hobby sites, IoT devices exposing XML+XSLT, document/report viewers, and simple templating for non‑programmers.
• A recurring argument: even if usage is small, the web’s “contract” was that standards-based content would keep working indefinitely. Removing a standard feature is viewed as a precedent that erodes trust.
• Others counter that backward compatibility itself has a cost; if a feature’s usage is tiny, removing it can be justified.

Security, maintenance, and cost–benefit

• Pro‑removal side: libxslt is old C code, a frequent source of security reports, and expensive to maintain; the maintainer quit under unpaid bugfix pressure. Keeping unused, complex code increases attack surface.
• Critics respond that “security” is overstated or misused: XSLT has memory‑safe implementations and could be sandboxed or shipped as a WebAssembly/JS polyfill bundled with the browser, largely eliminating native-risk without breaking sites.
• Disagreement over process: some feel Chrome pushed “intent to remove” and code changes before properly quantifying usage or understanding key cases (e.g., podcast feeds), contrary to Google’s own deprecation guidelines.

Comparisons with other web features

• Opponents note XSLT’s usage is reportedly higher than various newer hardware APIs (WebUSB, WebSerial, MIDI, WebTransport) that browsers are eager to add and keep; they see inconsistency in invoking “low usage” only for older XML tech.
• Defenders reply these APIs can’t be polyfilled and enable genuinely new capabilities (device setup, education, debugging), whereas XSLT transformations can be done on servers or in JS.
• FTP and Gopher removals are cited as precedent. Some argue they were more widely used than XSLT but still rightly removed; others say FTP never got a proper successor for directory‑style browsing.

Standards process and Google’s influence

• Several stress that removal was proposed within WHATWG with support from Mozilla and Apple; it’s not purely a unilateral Google move.
• Nonetheless, Google’s dominance and its speed in landing Chromium patches make people see this as symptomatic of a browser‑vendor‑driven web, where implementor convenience outweighs user and author needs.
• There is concern about Chrome moving to a partial Rust XML parser, seen by some as a signal that even standards‑compliant XML support may shrink.

Alternatives, polyfills, and RSS/Atom usability

• Multiple people suggest that RSS/Atom feeds could be made friendly with JS and CSS embedded in XHTML namespaces, or via JS XSLT polyfills.
• Critics argue that:
  • This breaks “truly static” sites and very constrained devices.
  • It forces authors to learn more complex JS instead of simple declarative templates.
  • It degrades the experience for non‑technical users who click feed links and see raw XML.
• Some propose that browsers should instead offer first‑class, built‑in RSS/Atom rendering, which would obviate XSLT here, but they doubt such support will materialize.

Broader “open web” and philosophy debate

• One camp: removing XSLT is a routine pruning of obsolete complexity and narrows the API surface, which can even help new engines like Ladybird.
• Another: it exemplifies a shift from the web as a durable document network toward a brittle, app‑delivery platform optimized for ads, telemetry, and proprietary ecosystems, with backward compatibility and user control treated as secondary.

Perceived Forecast Accuracy & Consumer Experience

• Several commenters say Google’s consumer forecasts (Search, Pixel, default Android weather) have become noticeably worse in the last 6–12 months, with temperature off by a few degrees or rain predictions clearly wrong.
• Others report consistently good results from national services (e.g., Norway, US NWS) or apps like Windy, yr.no, and some niche apps.
• A recurring theme: forecasts have objectively improved over decades (linked long‑term statistics), but users still experience jarring local failures, especially for precipitation and in complex microclimates.

Ensembles, Uncertainty, and Metrics (CRPS)

• Multiple comments explain that modern forecasting is fundamentally probabilistic: an ensemble of scenarios is run, and “chance of rain” reflects the fraction and spatial coverage of rainy members.
• Some users want a single “best” forecast; others strongly value explicit uncertainty/variance.
• WeatherNext 2’s emphasis on many scenarios and CRPS loss is discussed:
  • CRPS encourages sharp, well‑spread probabilistic forecasts, countering the blurring and loss of extremes seen with L2 losses.
  • Noise-driven ensembles (applied to inputs or parameters) plus CRPS help generate diverse but calibrated members without heavy post‑processing.
  • This is framed as a major technical advance versus earlier neural weather models and generative approaches.

Comparison with Traditional NWP Models

• Several commenters insist the key benchmark is accuracy vs major physics-based models (GFS, ECMWF, ICON), not speed. They note the article gives limited direct skill comparisons.
• There’s praise for Google’s recent hurricane track performance and criticism that US GFS has had a poor hurricane year.
• Some meteorology-savvy participants argue that, in this stack, WeatherNext still relies on ECMWF analyses, so it doesn’t yet close the loop with observation targeting or new data assimilation techniques.

High-Resolution & Specialized Use Cases

• Energy market participants need 5–15 minute forecasts for load and renewable generation; they describe using regional high‑resolution models like HRRR and custom NWP runs.
• Other specialized needs (e.g., structural engineering wind gust statistics, wildfire or severe thunderstorm behavior) often require reanalyses, regional models, or bespoke simulations; commenters doubt generic AI models yet excel here.

Data Sources, Integration, and Access

• Discussion of smartphone barometer data: historically proposed, but commenters note privacy, quality-control, and limited benefit; WeatherNext 2 does not use such data.
• WeatherNext 2 outputs are available via Earth Engine, BigQuery, Vertex AI, and are being integrated into Search, Gemini, Pixel Weather, and Maps/Maps Weather API; no dedicated consumer “WeatherNext” app exists.

History and pharmacology of stimulants

• Commenters note that substituted amphetamines and related phenethylamines (meth, MDMA, 2C-x, cathinones, etc.) have been around since the 1930s–50s and were researched for depression and what became ADHD.
• Stimulants were widely used in WWII by multiple militaries (“go pills”), and still see limited use (e.g., Dexedrine, modafinil) in modern forces.
• There’s debate over Adderall’s chemistry: some emphasize it’s just mixed amphetamine isomers and salts, not a “substituted amphetamine” like MDMA or meth.

Huxley, Soma, and fictional drugs

• Many initially confuse the article’s topic with Brave New World’s “soma,” then clarify that the linked Huxley lecture instead imagines a side-effect-free focus/attention drug.
• Discussion over what soma most resembles pharmacologically (weed, benzos, opiates, MDMA-lite) leads to broader debate on how cannabis and MDMA actually feel and function.

ADHD, Adderall, and stigma

• A large subthread pushes back hard on the framing “Adderall increases mental efficiency.”
• ADHD commenters stress that for them Adderall primarily reduces executive dysfunction (starting tasks, following through, managing daily life), not IQ or general “efficiency.”
• They highlight severe untreated-ADHD outcomes: shorter lifespan, high depression and suicide rates, rejection sensitivity, and emotional dysregulation.
• Several describe life-changing benefits from Adderall, atomoxetine, or modafinil, and object to framing these medications as shortcuts or productivity hacks. Misconceptions are seen as fueling stigma and diversion, making access harder for those who need them.

Therapy vs medication

• Disagreement over behavioral therapy: some say it “does nothing” for ADHD; others cite guidelines and CBT studies showing moderate benefits, especially combined with medication.
• Nuanced view: therapy doesn’t fix core neurobiology but can help with acceptance, coping strategies, and guilt; it’s complementary rather than an alternative to meds.

Cognitive enhancement, abuse, and safety

• Several argue Adderall does not make non-ADHD people smarter and may even reduce performance while increasing the feeling of productivity.
• Others point to historic and military use of stimulants for endurance and boring tasks, suggesting real (if narrow) performance gains.
• Debate over addiction and “wear and tear”: some call amphetamines safe and low-risk at prescribed doses; others note dependence potential, strong side effects, and misuse in academia.

Corporate structure and secrecy

• Commenters are surprised a company raising $6.2B can remain so opaque (unclear start date, location, staff).
• Several explain U.S. structures: corporations/LLCs must exist in state records, but private firms disclose minimal ownership or operational details; Delaware and some other states expose almost nothing publicly.
• Sole proprietorships and some partnerships can operate with almost no registration, but that’s seen as unlikely for a multi‑billion‑dollar vehicle.
• Speculation that this entity is buried under layers of holding companies and possibly using a code name, making it effectively untraceable to outsiders.

Scale and nature of the funding

• Some see $6.2B as potentially circular: money flowing from Amazon-related interests to the startup and back via AWS or chip purchases.
• Others suggest similar circular deals are widespread in the current AI boom, inflating apparent spend and valuations, though there’s disagreement about how extreme this is.
• A few wonder if this is partly an “experiment in AI financing” designed to multiply capital on paper without much real deployment.

AI productivity, jobs, and the bubble question

• One thread claims concrete evidence of reduced hiring in AI‑susceptible roles (content writing, front‑end dev), with an anecdote about replacing a front‑end developer using AI coding tools.
• Others push back: correlation with weaker hiring doesn’t prove AI causation; some roles might simply be easy to consolidate or were “non‑essential” already.
• There’s debate over whether AI tools really increase productivity for skilled workers, with one side citing studies and the other emphasizing lived experience.
• Several see the whole sector as a bubble or “musical chairs,” while others argue there is substantial real spend and consumer/business value underneath.

Co‑CEO role and billionaire behavior

• “Co‑Chief Executive” is widely read as a vanity or “seagull management” role: money brings final say without day‑to‑day work.
• Others counter that top‑level CEOs mainly set direction and hire; executing is delegated, especially when one is a celebrity billionaire.
• Some praise the founder’s historical track record and view his involvement as a net positive; others point to delays and underperformance at his space venture as evidence of distraction.

Relation to Amazon and the AI landscape

• Multiple comments argue Amazon has become bloated and ineffectual in AI, with tiny startups out‑innovating it; this could explain why a separate venture was chosen.
• People note Amazon’s existing multi‑billion stake in another frontier lab and hope this new effort is “something wildly different,” possibly focused on physics‑based or simulation‑driven scientific discovery.
• There’s cautious optimism that more well‑funded frontier labs increase competition and innovation, tempered by concern that this accelerates risky capabilities.

Ethics, science, and public trust

• Some see “AI to advance science and engineering (e.g., materials, manufacturing, spacecraft)” as one of the most socially positive AI directions.
• Others are skeptical, recalling earlier promises from high‑profile AI orgs that later pivoted to profit maximization; trust in billionaire‑led “for humanity” narratives is low.
• A recurring criticism is opportunity cost: instead of another AI moonshot, ultra‑wealthy individuals could address homelessness or other social problems, but commentators also argue that their personalities are intrinsically driven to chase more influence and wealth.

Miscellaneous reactions

• Several mock the name “Project Prometheus” as overused, and joke about mythological punishment and Amazon‑style liver subscriptions.
• Co‑CEO structures are called “a recipe for disaster” by some, though others note examples where dual leadership appears functional.
• Side threads discuss whether a 100‑person, multi‑billion‑dollar entity still counts as a “startup,” NYT’s “A.I.” styling, and celebrity‑gossip details of the founder’s social life.

Why geothermal hasn’t been a “holy grail”

• Usable high‑temperature resources are geographically patchy (Iceland, rift zones, volcanic regions). In most areas, hot rock is deep, heat flow is tiny (~40–60 mW/m²), and rock is a poor conductor, so you quickly “cool the rock” and must wait for it to reheat.
• Several commenters frame non‑volcanic geothermal as more like a finite hot‑rock “battery” than a continuously renewable source unless drilling is very cheap and very deep.
• Economics are “iffy”: very expensive wells for tens of MW, with high exploration risk and uncertain output. In many cases, solar and wind are already cheaper.

What’s changing

• Oil/gas drilling and fracking have driven costs down and enabled much deeper, more precise wells; some see this as the enabling tech for “deep geothermal” / enhanced geothermal systems.
• Ideas: plasma drilling, fracturing to increase rock contact, branching wells, and reusing orphaned oil wells for geothermal remediation projects. Opinions are mixed on how much this really fixes cost and water‑intrusion issues.

Heat vs power: ground‑source confusion

• Several comments emphasize the difference between:
  • Deep geothermal power (hot rock, steam turbines, MW‑scale electricity).
  • Ground/pond‑source heat pumps and district heating, which mainly exploit shallow ground as a seasonal heat store, often ultimately solar‑driven.
• Ground‑source heat pumps are praised as effective for buildings, but they don’t solve grid‑scale electricity needs.

Geothermal vs solar, wind, and nuclear

• Pro‑geothermal view: dispatchable, low‑carbon, good complement to intermittent renewables and for district heating (e.g., Munich, Iceland, flooded mines).
• Skeptical view: steam turbines and drilling are fundamentally expensive; with PV module prices plunging and batteries improving, geothermal will remain a niche except in very favorable geology.
• Large side debate: whether nuclear fission should be the core solution (cheap baseload if politics and regulation allowed) vs renewables+batteries outcompeting new nuclear on cost and build speed. No consensus.

Grid integration, storage, and “baseload”

• One camp argues “baseload generation is obsolete”: cheapest energy is now intermittent (solar/wind), and what’s needed is dispatchable capacity and storage (batteries, pumped hydro, demand shifting).
• Others counter that real grids still have large continuous loads and that countries relying heavily on intermittent renewables (e.g., Germany) struggle with costs and coal backup, whereas nuclear‑heavy grids (e.g., France) enjoy cheap, low‑carbon power—though maintaining aging fleets is getting very expensive.
• Several note promising work on large‑scale batteries, thermal storage in rock/soil, and grid‑forming inverters, but long‑duration/seasonal storage remains hard; many expect some continued fossil backup.

Risks and planetary impacts

• Induced earthquakes from enhanced geothermal projects have already shut down some trials, prompting calls for caution, especially in historically seismic regions.
• Concerns about “cooling the core” are dismissed as physically negligible relative to Earth’s internal heat budget, based on figures shared in the thread.

C++20 as GCC’s Default

• Some welcome GCC 16 moving to C++20 by default, wanting easier access to features like modules without extra flags.
• Others insist serious projects should always pass an explicit -std= flag, so defaults shouldn’t matter for well-maintained code.
• Concern is raised that unpinned legacy projects and deep dependency trees implicitly rely on a stable default and may break when it changes.

Modules Debate

• A strong faction argues C++20 modules are a failed feature: underspecified, implemented ad‑hoc across major compilers, and not robust enough for serious, non‑hobby code.
• It’s noted that the original high‑profile “modules are dead” critique predates standardization, but commenters claim the final standard still lacks a solid, independently implementable spec.
• Counterexamples like Microsoft Office are clarified as using non-standard “header units,” not full C++20 modules, so not evidence of mainstream module adoption.

Standards Support and Backward Compatibility

• People question why not default straight to C++23 or newer; the answer in the linked GCC docs and thread is that support is still incomplete.
• Compatibility concerns center on new keywords and stricter rules making previously valid code fail. There’s disagreement over whether this constitutes “breaking changes”:
  • One view: C++ rarely makes truly breaking changes and is strongly backwards compatible.
  • Another: changing defaults so old code fails to compile is practically a breaking change, even if technically minor.

Bootstrapping and Self‑Hosting

• Some confusion arises about whether changing the default impacts GCC’s own build; others clarify that GCC’s build uses explicit standard flags, so this is only about user defaults.
• There’s a side debate on bootstrapping and whether using the latest standard complicates self-hosting with older compilers; participants dispute what “requires bootstrapping” actually means.

Rust and Release Cadence Comparison

• A few praise C++’s slower, multi‑year default updates compared to Rust’s rapid evolution, arguing Rust’s culture of always targeting very new compilers complicates distro self‑hosting.
• Others counter that Rust projects can and do pin minimum versions, and that rapid improvements are beneficial rather than inherently problematic.

Anubis / Anime Gateway Tangent

• A large subthread focuses on the anime-style Anubis gateway in front of the GCC mailing list:
  • Some find it jarring, unprofessional, or creepy, especially in serious or corporate contexts.
  • Others like the playful aesthetic, argue open-source maintainers should prioritize fun over “corporate bland,” and note that the mascot doubles as a funding/branding mechanism (free version keeps the mascot; paid allows custom art).
  • Comparisons are made to Cloudflare-style blocks: Anubis is considered less harmful because it still shows page content, though some note performance issues on poor connections.
  • There’s a meta-argument about cultural bias toward anime art and whether negative reactions to “anime mascots” reflect broader prejudices.

Coroutines and ABI Concerns

• One commenter wonders whether differing coroutine implementations could break interoperability between GCC and Clang binaries; the question is raised but not substantially resolved in the thread.

Practices and Personal Choices

• Several commenters reiterate they always specify language standards and warning flags (both for C and C++) and consider relying on defaults a bad practice.
• Some developers state they’ll continue using older standards (e.g., C99 or C++03/11) regardless of GCC defaults, prioritizing stability and long-term compatibility over new language features.

Russia–EU War Scenarios & Drone Warfare

• Several comments envision a future Russia–EU conflict shaped by mass, decentralized drone attacks on logistics and civilian infrastructure, not classic tank thrusts.
• Others dispute this, arguing Russia’s battlefield losses, sanctions, and fuel shortages limit its capacity; if it could win big conventional wars, it would have taken Ukraine already.
• Some cite reports of Russia rebuilding and storing tanks, with fewer deployed to Ukraine, reading this either as preparation for larger future conflicts or simply adaptation to a drone-dominated battlefield.
• There is disagreement over whether Russia could quickly seize the Baltics or would instead lose air superiority and supply lines against NATO.

Putin’s Constraints & Domestic Politics

• One line of discussion suggests Putin personally has “no way out” of the war because dictators cannot appear weak, even if Russia as a state could withdraw.
• Internal power struggles among security elites are mentioned as a factor that may limit his options.

Nature of the Airport Drone Incursions

• Commenters ask what drones are actually being seen: cheap FPV hobby drones, civilian quadcopters, or military systems like Shaheds.
• Some say it’s mostly civilian-style drones operated by locals recruited online (e.g., via Telegram), potentially as part of low-cost Russian intelligence/sabotage operations.
• There is frustration over vague imagery and limited public evidence, with comparisons to earlier “mass delusion” drone/UFO episodes.

Countermeasures & Practical Constraints

• Ideas range from jamming, radar, counter-drones, and automated turrets to tracking drones back to operators.
• Others stress constraints: legal bans on shooting/jamming near civilian airports, response-time issues, risk to aircraft and bystanders, and difficulty detecting small, fast drones in time.
• Some governments are reportedly updating laws and exploring specialized anti-drone systems, but defense has largely been oriented toward hobbyist, not military, threats.

Attribution, Motives, and Skepticism

• Proposed culprits include: Russian sabre-rattling, NATO running secret drills, opportunistic “idiots,” and (less credibly argued) China.
• Some see the media narrative as fearmongering to justify expensive anti-drone “walls” and military spending.
• A minority frame the broader conflict as Western aggression against Russia and speculate the drone incidents are false-flag operations to prepare public opinion for a larger war.

Overall reception of the article

• Several commenters found the piece insightful and said it should be taught in professional development; others derided it as naïve, “AI slop”-like, or emotionally tone-deaf.
• Many agreed that “movie logic” (conflict sustained by not naming the obvious issue) is both pervasive in fiction and recognizably present in dysfunctional workplaces, friendships, and marriages.
• Others argued the advice is oversimplified: you can’t fix deep psychological patterns with three conversational tricks.

Debate over the Good Will Hunting example

• The article’s flagship example was widely called out as wrong: in that film, everyone does tell Will he’s wasting his talent; his problem is believing it and processing his trauma.
• Several noted the film is explicitly about how inner change requires experience and emotional readiness, not just someone finally saying the magic sentence.
• This was used to argue that real change rarely comes from a single frank conversation or “epiphany.”

Communication, conflict aversion, and feedback

• Many recognized themselves or their cultures (especially Midwestern U.S.) as kind but conflict‑averse, leading to unclear priorities and hidden tensions.
• Others emphasized how hard it is to receive feedback: sunk-cost thinking, emotional investment, and fear of vulnerability often override stated desires for honesty.
• One thread argued basic communication skills are rare and may worsen as people outsource writing/thinking to AI tools.

When bluntness fails or harms

• Multiple anecdotes described “clearing the air” making relationships colder, awkward, or unrecoverable, especially with conflict‑avoidant people or those with serious mental/behavioral issues.
• Commenters stressed that directness can feel like attack, leave “scars,” or destroy tolerable-but-imperfect dynamics; judgment is needed about when not to raise issues.

Movies, exposition, and “idiot plots”

• Several invoked “Idiot Plot” and discussed how poor communication and withheld info drive drama in films and TV.
• Others noted that in real life, people also avoid uncomfortable topics; movies often mirror, rather than distort, this avoidance.

Deeper psychological and cultural angles

• Some tied the issue to self-deception: people can’t communicate honestly because they’re not honest with themselves.
• Cultural differences (e.g., blunt vs. circumspect societies) were cited as crucial context for how “direct” talk lands.
• A few mentioned therapy and game theory: surfacing implicit knowledge changes the “game,” but usually requires outside help and long-term work, not one neat conversation.

C vs C++ vs “C with Superpowers”

• Many argue that if you want RAII, vectors, smart pointers, and sum types, you should just use C++ (possibly in a “C-like” style) instead of macro-heavy C.
• Counterpoints:
  • C++ is hard to parse and tool for; C stays “hackable” with simpler parsers and tiny compilers (TCC, slimcc, etc.).
  • Some embedded vendors still don’t ship usable C++ toolchains; C remains the lowest common denominator.
  • Migrating a large legacy C codebase wholesale to C++ is non-trivial.

Portability, Toolchains, and Extensions

• The header relies on GCC/Clang features like __attribute__((cleanup)) / [[gnu::cleanup]]; this excludes MSVC and strict C99/C11 environments.
• Clarifications that C23 only standardizes a small set of attributes; cleanup remains a vendor extension.
• Some suggest using C11 threads.h / atomics instead of POSIX mutexes for better portability.

Value and Limits of the “Safe C” Header

• Supporters: neat toy, shows how far you can push C toward safer patterns (RAII-like cleanup, vectors, Result types) without adopting full C++/Rust.
• Critics:
  • Expect many corner cases and UB; without a spec and battle-hardened implementation it’s risky for serious code.
  • Macros create a project-specific mini-language that newcomers must learn.
  • Shared-pointer and view/string_view style constructs still allow use-after-free; nothing enforces correct lifetimes or refcount discipline.
  • “Result” types don’t force checking like Rust; you can still ignore errors.

Safety vs. Language Choice

• Some say energy should go into incrementally rewriting C systems in memory-safe languages (Rust, Fil-C, etc.), not layering more macro magic.
• Others argue there are billions of lines of C that can’t be rewritten soon; incremental tools that reduce footguns are valuable.
• Debate over whether an “improved C” could achieve memory safety via ownership and lifetimes without GC; lifetimes + polymorphism seen as likely required.

GC, Fil-C, and Performance

• Fil-C (a GC-backed C runtime) is raised as a more thorough safety approach.
• Long subthread on garbage collection:
  • One side: GC overhead is negligible for most programs; safety payoff is huge.
  • Other side: GC can significantly hurt throughput, latency, and working set for systems/embedded workloads; manual or ownership-based schemes are still preferred there.

Coding Practices and Alternatives

• Some prefer classic patterns: goto out cleanup blocks, arenas, or simply not freeing process-lifetime data (like parsed CLI options).
• Concern that trying to make C “safe” hides its nature; better to use languages like Nim, Go, Rust, or specialized verified C dialects (Frama-C, Fil-C) when safety is paramount.

Legacy Devices & Alternative OSes

• Commenters note active work on dual-booting older devices like the N900, suggesting Maemo Leste as a strong option despite incomplete hardware support.
• 3G network shutdowns make such devices less usable as phones; someone wonders about a 4G/5G “bridge” that presents a local 2G/3G cell, with a joking reference to Stingray devices.

Linux Phone Experiments (postmarketOS, Sailfish, Waydroid)

• Several people are testing postmarketOS and Sailfish on modern hardware (Fairphone, Xperia, Redmi).
• Consensus: usable for tinkering and some daily tasks, but not yet full daily drivers. Common issues: audio, sensors, and especially banking/“app-only” services.
• Waydroid (Android-in-a-container) works “pretty good” and helps fill app gaps; questions remain about background GPS, sensors, and navigation reliability.
• Some users value having a standard Linux userland (Nix, Python, git, containers) more than perfect phone features.

AOSP Forks, GrapheneOS, and Security Models

• Debate over “why not just hard-fork AOSP”:
  • One side: Android’s permission model and sandboxing are far ahead of classic Unix security and should be preserved.
  • Others: if you can’t or don’t rebase on AOSP, Android apps break; truly hard forks are unrealistic.
  • Concern that if Google stopped updating AOSP, OEM/chip-vendor private channels or Chinese forks would dominate; unclear how non‑open SDK/NDK would affect viability.
• GrapheneOS is cited as an example of a privacy/security-focused AOSP fork:
  • Critics report poor battery life (especially with 5G and GPS tracking apps), an intrusive GPS indicator, and UX too complex for “normal users.”
  • Defenders say it feels like stock Android with better privacy controls and no noticeable battery issues.

postmarketOS vs Android Security

• One camp calls postmarketOS “antiquated” for phones: classic Unix permissions allow mic snooping, ransomware, and credential theft if apps are compromised.
• Others counter that:
  • Linux increasingly uses sandboxing (Flatpak, etc.) and distro trust; dangerous permissions can be constrained.
  • Not all use cases require Android’s tight model; many users value root/admin control and reject “Android‑bis.”
• Follow‑ups stress that all software should be treated as untrusted (citing the XZ backdoor) and that defaults, not optional hardening, matter for most users.

Terminology & Control: “Sideloading” vs Installing

• Long subthread on language:
  • Some argue “sideloading” is a PR term to stigmatize installing apps outside Play Store; they prefer just “installing,” or phrases like “installing from outside the store.”
  • Others say the distinction is useful: installing via the main, monitored channel vs arbitrary APKs from the web is a real risk difference for typical users.
• Comparisons to macOS, Linux package repos, and game consoles:
  • On desktop Linux, nobody calls manual .deb/AppImage installs “sideloading,” but the same conceptual distinction (official repo vs third-party) exists.
  • Some see Android and iOS converging on console-like walled gardens; others argue it’s “industry standard” and still more open than consoles/iOS.
• There’s disagreement over whether Play Store monitoring meaningfully reduces risk, with counterexamples pointing to Play malware and F-Droid’s better record.

Hardware Openness, Bootloaders & Firmware Layers

• Concern that unlockable bootloaders are getting rarer; advice is to buy devices officially supporting unlock (LineageOS device list, recent Pixels, some Motorolas).
• Xperia devices are praised for upstream kernel contributions, bootloader unlocks, headphone jacks, and microSD—even as some report physical quality issues.
• Technical discussion on why phones lack a PC-like “BIOS experience”:
  • Many modern phones (especially Qualcomm-based) do use UEFI under the hood, but there is no ACPI-like standard layer.
  • On x86, decades of legacy BIOS/UEFI interfaces (INT 10h, 13h, 16h) make minimal OS bring-up trivial and portable.
  • On ARM, each board relies on a specific devicetree and custom drivers; that fragmentation makes generic OS support and projects like postmarketOS much harder.

Alternative Uses & Networking Freedom

• Some run postmarketOS phones as pocket Linux PCs with external keyboards and power banks; ARM and small screens limit but don’t prevent real development work.
• A few envision phones as nodes in mesh networks and resilient P2P systems (Freifunk-style), independent of big tech clouds.
  • SDR + protocols like Reticulum/Yggdrasil could provide the fabric, but stock Android struggles as a general-purpose server/container host.
  • Commenters lament that phones, despite powerful open-source cores, are “tivoized” and locked down like consoles, undercutting the benefits of open source.

Big Tech, Competition, and Lock-In

• One commenter delivers a broad critique of big tech as building “alien” ecosystems, with heavy AI/PR layers detached from human needs.
• Others respond that in competitive markets, firms “fight for their lives” by erecting barriers to competition; app-store lock‑in and restricted installation are seen as examples.

Device Support & Resources

• The postmarketOS device compatibility matrix is highlighted, plus a scraped table of “testing” devices (considered relatively stable).
• LineageOS’s device list with a bootloader-unlock filter is suggested as a guide for future‑proof, hackable purchases.

Risk & Bricking Concerns

• Someone asks how hard it is to unbrick a phone when attempting dual-boot/flash experiments; the thread does not provide a clear or general answer.

Desire for openness and control

• Many see these hidden iPadOS features on iPhone as proof of how much Apple locks users out of their own hardware.
• Several commenters say they’d rather have “boring” but open devices (Linux laptops, Android/GrapheneOS phones) than powerful but constrained Apple hardware.
• Some argue that, as paying adults, they should be allowed to assume more risk (sideloading, root, custom OS) if they want.

What people say they’d do with a more open iPhone/iPad

• Run full browsers with extensions, true ad blocking, and alternate engines.
• Sideload apps (especially FOSS), install personal/internal apps permanently without paying Apple, and pin old versions to avoid “enshittified” updates.
• Script and automate via shells (termux/a-shell–style), run CLIs like ffmpeg/yt-dlp, packet sniff, fine-grained firewalls, and even Emacs, Python stacks, or Mathematica.
• Customize UI/UX (window managers, key remapping, disabling unwanted UI “glass” trends) and small quality-of-life fixes (flashlight behavior, Screen Time controls).
• Use phone/tablet as a dockable desktop: external display, keyboard/mouse, desktop-class multitasking, maybe even VMs.

Security, battery life, and complexity

• Opponents of openness stress that phones hold “entire lives” and that relaxed security, root, and sideloading would massively increase risk for typical users.
• Others counter that desktop OSes work despite weaker models, that power users could improve battery by killing unwanted background services, and that Android/Lineage/GrapheneOS show FOSS can be efficient.
• Some think iPad/iPhone multitasking UIs are already too complex for nontechnical users; others argue complexity should be optional, not forbidden.

Mac vs Linux and “locked down” debate

• Debate over whether Apple Silicon Macs are truly “locked down”: many say macOS lets them build/run anything and is a good dev machine; others dislike notarization, UX constraints, lack of Linux boot, and proprietary GPU/Vulkan stack.
• Asahi Linux is mentioned as partial relief but not yet a full mainstream replacement.

iOS vs iPadOS and feature gating

• Thread consensus: iOS and iPadOS are clearly the same codebase with features toggled via configuration, not separate OSes.
• Some see the separation as largely marketing and possibly regulatory strategy (keeping iPad out of EU “gatekeeper” rules).

Multitasking, small screens, and external displays

• Mixed views on split-screen and Stage Manager: some find them useless or cramped even on 11" iPads; others rely on split-screen even on small Android phones.
• Strong interest in a DeX-like or even macOS-on-iPhone/iPad mode when docked to a monitor, but skepticism Apple will ship anything that cannibalizes MacBooks or weakens App Store control.

Meta: article accessibility

• Multiple complaints that the linked site is overloaded with ads, trackers, and/or Cloudflare errors, making it nearly unusable without reader mode.

Role of LFP Patents

• Some argue core LFP patents were already a “non-issue”: royalty flows are tiny relative to the battery market, and real differentiation now comes from newer, still-patented advances (additives, coatings, manufacturing).
• Others counter that patents did suppress competition outside China, via blocking licenses, high fees, and “mutual assured destruction” patent thickets that deter new entrants and invite trolls.
• Suggestions include patent pools or “GPL-like” cross-licensing schemes to neutralize trolls, though concerns remain about fees and incentives for low‑quality patents.

Battery Chemistries: LFP, Solid-State, Sodium, Others

• LFP is seen as practical, cheap, and safe, with sufficient energy density for most cars but less ideal for large trucks/SUVs and cold climates.
• Cold charging is a recurring theme: heaters and thermal management are viewed by some as an adequate workaround; others call this a “hack” that adds complexity, energy cost, and edge‑case failure modes.
• Sodium-ion is widely discussed as a likely successor for many uses: better cold performance and charge rates but lower volumetric density and trickier power electronics; timelines to cost parity with LFP range from a few to 10–15 years.
• Solid-state batteries are compared to fusion: impressive lab results and one‑off demos (cars, bikes, drones), but still extremely expensive and not yet mass‑produced.
• Niche chemistries like lithium‑titanate are praised for ultra‑fast charging but criticized for low energy density.

IP History and China’s Lead

• Foundational LFP work came from a Canadian/Quebec lab, with patents licensed via Hydro‑Québec and a major US company allegedly infringing and triggering long legal battles.
• Commenters say this litigation chilled Western investment while China received favorable domestic licensing and built a huge LFP ecosystem.
• China is now seen as dominant in batteries and EVs, with recent moves to restrict export of advanced LFP tech and equipment.

Recycling and Regulation

• EU recycled‑lithium quotas are criticized as potentially constraining growth when total deployed capacity is still ramping; others see them as necessary to capture waste (e.g., vape cells).
• Concern that “recycled content” rules might incentivize scrapping still‑usable large packs rather than repurposing; practitioners note second‑life use of car packs is logistically and economically limited versus modular stationary batteries.

EV Markets, Tariffs, and Chinese Cars

• Forecasts discussed: EV adoption slowing in the US but accelerating in countries like Vietnam, driven by cheap Chinese models.
• Europe and the US are using tariffs to slow Chinese EV imports; some see this as delaying the inevitable, given China’s cost and tech advantages.
• Several participants want access to $20–30k Chinese EVs in the US but worry about both Chinese and domestic car software collecting data.

Energy Prices and Renewables

• One side claims an “ideological push” for renewables is driving up European electricity prices via storage, grid, and capex needs.
• Others counter that wind and solar are now the cheapest new generation, pointing to:
  • Very low off‑peak EV tariffs in the UK tied to renewables.
  • The South Australia experience, where high renewable penetration plus batteries is pushing prices down after an investment phase.
• There is debate over whether apparent inefficiencies (e.g., old wind turbines removed when subsidies end) reflect bad policy design or rational asset replacement.

Cars vs Public Transit

• Some see EV focus as perpetuating car dependency; they argue for dramatically expanded, cheap public transit and denser land use.
• Counterarguments:
  • Many regions are too low‑density or poorly planned for efficient mass transit; personal vehicles remain more practical.
  • Experiences with unreliable or inconvenient transit (especially in US cities) push people toward cars.
  • Others provide examples (Europe, parts of Australia, some US suburbs) where buses and trains work well even for families with small children, with “last mile” handled by walking, bikes, or small vehicles.
• Historical notes point out that US cities once had extensive transit networks and that auto industry lobbying contributed to their dismantling.

Article as Law-Firm Marketing

• Multiple comments note the linked piece is effectively an advertisement for legal services (freedom‑to‑operate analyses), likely to emphasize ongoing patent risks even after key expiries.
• Some think this doesn’t necessarily undermine factual accuracy; others stress the need to view its framing through the lens of attracting clients.

Profitability of Cures and Patent Dynamics

• Multiple comments argue curing patients can be extremely profitable, citing blockbuster examples (e.g., Hep C cure, major cancer drugs) generating tens of billions in revenue.
• “Unsustainable” is seen as a bad framing: all patented drugs (cures and chronic treatments) are inherently time-limited due to patent expiry and generics, so firms must continually find new products anyway.
• Some note pricing for certain cures was “scandalous” and triggered investigations, but others counter that high prices are what enabled those profits and further R&D.
• Analogy is made to oil/mining: one finite “deposit” can still be a fantastic investment even if it eventually runs out.

Market Incentives, Competition, and Cartels

• A recurring theme: if a market is full of chronic treatments, any firm that launches a cure gains huge competitive advantage; coordinated withholding of cures is described as an unstable equilibrium.
• Patents and time limits incentivize bringing cures to market rather than hiding them; sitting on a patented cure would forfeit revenue and eventually allow competitors free use.
• Some push back, raising concerns about cartels, regulatory capture, and buyouts where firms purchase cures to protect existing treatment franchises.
• Conspiracy-style ideas about systematically suppressing cures are generally rejected as implausible given the number of independent labs and the dynamics of competition.

Capitalism, Ethics, and Role of Government

• Several comments argue that for-profit medicine misaligns incentives: recurring treatment revenue can be more attractive than one-shot cures (“health as subscription”).
• Others emphasize higher-order societal benefits of cures (longer, healthier lives, more economic contribution) that aren’t fully captured by private firms—classic externality problem.
• This leads to advocacy for socialized healthcare or stronger government role in funding R&D, especially for antibiotics, rare diseases, and unprofitable cures.
• There is debate over whether “economic value” should be the justification at all; some insist healthcare should be provided on moral grounds, not just ROI.

Industry Structure and R&D Risk

• One detailed thread explains the biotech pipeline: university research → VC-backed biotech → pre‑revenue IPO → eventual acquisition by big pharma that handles late-stage trials, manufacturing, and global roll‑out.
• Scientific and clinical risk is largely borne by startups and public investors; big pharma competes to acquire successful assets, including cures.
• Because of this structure, as long as the market isn’t a tight oligopoly with captured regulators, there are strong incentives to develop and commercialize cures.

Alternative Business Models and Policy Ideas

• The Goldman report’s own “solutions” are noted: focus on large markets, high-incidence disorders, and continuous portfolio expansion; genetic and personalized medicine can generate a continuing stream of new cures.
• Suggestions include “post-scription” models (small lifelong payments after a cure), insurer structures where cures can be priced against lifetime treatment costs, and tax/market designs that reward social outcomes (e.g., reduced disease incidence).
• Some analogies to public transit highlight that activities can be socially valuable but privately unattractive, implying need for mixed public–private or redesigned incentive systems.

How to Interpret the Nvidia Sale

• Some view the move as a “signal” or part of a larger, opaque strategic game among billionaire “whales,” not just an economic act.
• Others argue Occam’s razor applies: he bought low, the position was up massively, so he’s locking in gains and reducing concentration risk.
• Several note this Nvidia stake (~$100M) is tiny relative to his reported net worth (tens of billions), likening it to a small retail investor selling a few thousand dollars of stock.
• Filing after market close raised eyebrows, but Nvidia traded up after hours, undercutting immediate “bad omen” narratives.

Bubble Fears, Macro Risk, and Timing

• Many commenters are convinced AI/Nvidia is a bubble; some say “at this point if you don’t think AI is a bubble, I don’t know what to tell you.”
• A minority warn of an extreme systemic crash (USD collapse, whole financial system at risk); others respond this doesn’t match past bubbles and that central banks exist to prevent total meltdowns.
• There’s concern that private credit and liquidity issues, combined with AI capex excess, could trigger broader sell-offs.
• Some push back: bubbles are hard to time, prior “insider” exits (e.g. big funds selling Nvidia in 2019) missed huge upside.

Rotation into Microsoft and Apple

• The disclosed move was largely from Nvidia into Microsoft and Apple.
• Some see this as a modest hedge: shifting from a pure AI hardware play into mega-cap tech with diversified cash flows that would likely survive any AI correction.
• Others say these are still AI-exposed, so this is a half-hearted bubble hedge at best; Apple is seen as somewhat less AI-dependent than hyperscalers.
• A few think the sale would have made more sense redirected into fabs/equipment (e.g., chip manufacturers), though others note those usually fall alongside chipmakers in downturns.

AI Fundamentals and Nvidia’s Moat

• Bears: Nvidia is priced as if it will permanently dominate AI; yet AMD, big-cloud in-house chips, and other accelerators are gaining. Efficiency improvements (e.g. GPU pooling, model advances) could drastically cut demand versus the most optimistic projections.
• Bulls: Even huge efficiency gains still leave enormous GPU demand; hyperscalers openly report AI infrastructure as a growth bottleneck with 20–40% revenue growth.
• There’s active debate over hardware depreciation and whether current spending is sustainable or a classic capex overshoot.

Is This a Reliable Signal?

• Some distrust his judgment due to highly controversial religious and political statements (e.g., “antichrist” rhetoric), arguing this undercuts his perceived rationality.
• Others insist political or theological beliefs don’t negate decades of strong investing performance and insider knowledge of the sector.
• Several note he’s not alone: large Nvidia sales by other major players (SoftBank, prominent fund managers, tech insiders) make this feel like a stronger sell signal—though still not conclusive.

Legal and Regulatory Issues

• Commenters discuss whether the described timeline violates SEC cyber-incident rules that require disclosure within four business days once an incident is deemed “material.”
• Speculated potential violations: late disclosure, misleading omissions to investors, inadequate internal controls, and broken disclosure processes—though nothing in the thread proves regulators’ view.
• On suing, several note the need to show concrete, quantifiable harm; user agreements and mandatory arbitration may further constrain options.

Did This Prove Coinbase “Knew”?

• Some readers think the January report plus Coinbase’s acknowledgment (“robust report, investigating”) indicates early awareness of a systemic breach.
• Others argue it only proves Coinbase knew of a sophisticated attack against one user, not that they had concluded a company-wide compromise.
• Skeptics emphasize that customers are frequently compromised via malware, OSINT, or prior breaches, so initial suspicion naturally falls on the user.
• A few other organizations/users report similar targeted scams in early 2025, suggesting a broader pattern but not conclusively tying it to Coinbase’s internal systems.

Email, DKIM, and Technical Confusion

• Multiple commenters are puzzled how a phishing email could have a valid DKIM signature for coinbase.com.
• Confusion centers on a claim that both amazonses.com and coinbase.com DKIM checks passed; several note SES should not be able to sign as a domain without control of its DNS, implying either misinterpretation or a more serious compromise.
• This part of the story is seen as unclear and under-documented in the blog post.

AI-Written Article and Style Backlash

• A large subthread criticizes the article’s style as stereotypical “LLM slop”: overlong, heavy on bullets, dramatic section titles, neutral-but-grandiose tone.
• The author confirms extensive AI assistance (transcription, structuring, drafting, editing) and defends it as a time-saver compared to not writing at all.
• Many readers object that AI makes it too easy to generate thousands of words of marginal value, wasting reader time; some ask for explicit AI disclaimers so they can auto-summarize instead.
• A minority defend the practice, arguing content should be judged on substance, not its production method.

Security, Outsourcing, and Crypto Context

• The breach being linked to bribed overseas contractors at an outsourcing firm prompts calls to ban offshoring of sensitive financial data, with doubts about enforceability.
• One commenter with Coinbase experience says the whiteboard-password anecdote refers to a building vendor, not Coinbase, and asserts Coinbase had a strong internal security culture.
• Others broaden this to fintech/crypto generally, describing unreliable APIs, operational chaos, and frequent hacks, while noting that “Bitcoin” the protocol is distinct from exchanges like Coinbase.

User Experiences and Mitigations

• Several users report Coinbase-themed scams (calls, emails, “security alerts”) in the same general period.
• One highlights using unique, per-service email aliases so any mail to the leaked alias can be treated as hostile post-breach.
• There is brief debate over self-custody vs custodial exchanges: “not your keys, not your coins” versus the high rate of lost wallets and keys.

Disclosure Practices and Trust

• Some users say they only learned of the breach via social media, not direct notice, and question whether Coinbase’s customer communication met legal or ethical expectations.
• Reports of failed account deletion, unresponsive privacy channels, and under-rewarded or buried vulnerability reports contribute to a perception that Coinbase’s handling of user data and security disclosures is opaque and self-protective.

AI authorship controversy

• The site prominently claims “zero AI” and “hand-written” content. Many readers find the prose and structure highly reminiscent of LLM output: repeated “not just X, but Y” constructions, breathless marketing tone, generic “transformation” language, and odd flowcharts and headings.
• Others argue style alone is not evidence; those rhetorical patterns predate LLMs and are also taught in writing classes. Overuse might indicate mediocre human writing rather than AI.

Trust, ethics, and AI detection

• Several commenters run the intro (or whole chapters) through Pangram, which flags it as AI-generated with high confidence. Some treat this as strong evidence; others cite Pangram’s reported false positives and consider it unreliable proof.
• The ethical concern is not AI use per se but the explicit “no AI” claim. Many say that, if LLMs were used (even for drafting or rewriting), the statement is misleading and undermines trust in the technical content.
• Repo signals heighten suspicion: anonymous author, entire book pushed at once, odd Git history, deleted issues, and even issue labels like “AI ALLEGATION.”

Perceived quality and pedagogy

• Some readers praise the breadth, detail, and apparent correctness of chapters they understand, and see it as the best Zig resource they’ve found.
• Others find the pacing and ordering chaotic: chapter 1 dives into symbol exporting and platform details before basic control flow; “how it works”/“key insights” sections feel like generic summaries; flowcharts and headings are seen as clutter with little conceptual payoff.

Technical accuracy and possible hallucinations

• Commenters point out concrete errors typical of LLMs: references to non-existent, renamed, or internal Zig std APIs, and misleading details about the compiler and build system.
• This reinforces concern that hallucinations may be scattered throughout, making the book risky as a primary learning source.

Zig’s value proposition and comparisons

• Side discussions debate whether Zig really “fundamentally changes how you think about software” versus being “modern C with a good stdlib.”
• Supporters highlight explicit memory management, allocator-passing, comptime, strong C interop, and cross-compilation; skeptics feel the intro overpromises compared to truly paradigm-shifting languages (Lisp, APL, Prolog, Erlang).

Site design and format

• Several usability complaints: tiny fonts, slow site, hard-to-find table of contents, distracting animated progress bar, no official PDF. One commenter shares a script/command to generate a PDF from the AsciiDoc sources.

Meta: AI accusations on HN

• Some want an HN guideline against casually accusing content of being AI-written, saying it derails discussion.
• Others argue public scrutiny of AI-authorship claims is a necessary defense against fraudulent “human-only” branding.

Favicon behavior and bugs across browsers

• Many commenters report long‑standing favicon glitches: wrong icons shown for specific sites, icons “stuck” for months or years, persisting across profiles, private mode, OS updates, and possibly iCloud sync.
• Bugs appear across Safari, Firefox, Chrome, iOS Safari, and other WebKit-based browsers, suggesting deep or shared caching issues.
• Safari’s favicon cache is described as extremely persistent; some mention only extreme measures (e.g., deleting cache files or changing system time) fully resetting it.

Live demo and whether the attack still works

• Several users can’t get the demo working (infinite 1–18 redirect loops, especially on iOS Safari and Firefox private mode). Others report seeing a unique ID after the first cycle.
• Some note the GitHub repo is old (Edge 87 mentioned) and conclude the specific exploit is largely patched; a linked issue states major browsers fixed this years ago.
• However, another link suggests Chrome briefly patched and then regressed, with a more recent note that favicon tracking should now reset on cache deletion and incognito entry.

Effectiveness, limitations, and mitigations

• Users observe different IDs between normal and private windows, and even between separate incognito sessions, implying at least some mitigation in Firefox and elsewhere.
• Deleting cookies and site data in Firefox is reported to remove the identifier.
• One commenter questions practicality: 32 redirects to construct an ID seems heavy; others reply that ad networks value any extra bits of identity, even if costly.
• Disabling favicons is discussed: some argue that being “favicon-less” could itself be a distinctive fingerprint; others say it would just look like a fully cached state, depending on implementation (details remain unclear).

Favicons vs usability and privacy

• Some users happily run favicon‑free browsers and question why they’re needed.
• Others defend favicons as essential for tab‑heavy workflows, where icons are easier to scan than truncated titles.

Ethics, regulation, and business models

• Strong criticism of hidden tracking: some want it criminalized, likening it to stalking or malware.
• Debate over GDPR: some say it already covers such tracking; others highlight weak enforcement or “legitimate interest” loopholes.
• One long subthread argues:
  • Tracking within a single site to improve services is acceptable; reselling data and third‑party brokers are the core problem.
  • GDPR and similar rules may inadvertently entrench large incumbents and hurt small, data‑driven businesses.
  • Opponents push back, emphasizing user consent, the difficulty of opting out when most sites require JS, and the need for regulation because users can’t realistically audit code.

Hardened browsing setups and practical issues

• Some describe extreme isolation: running browsers in disposable VMs with qemu and sandboxing, deleting state on exit.
• Others note that such setups can themselves become fingerprints (e.g., odd GPU/rendering behavior, missing fonts), triggering CAPTCHAs and suspicion.

Broader tracking landscape and related techniques

• Commenters expect similar attacks on other long‑lived browser artifacts and caches.
• A GPU-based fingerprinting technique (“DrawnApart”) using WebGL timing is mentioned as another example of increasingly sophisticated tracking.

Reception of the research

• Several find the favicon “supercookie” technically clever or “lovely” as an attack vector.
• Others are more interested in using it (or similar tools) for non-ad-tech purposes like detecting banned users who try to evade bans.

Scoring System and Taxonomy Concerns

• Many see the numerical ratings as “dubious”: games perceived as benign (e.g., traditional roguelikes, HyperRogue) score poorly because any checked pattern counts negatively.
• The implementation treats patterns like “competition,” “grind,” or “collecting items” as uniformly bad, despite the textual descriptions saying they are only dark in certain contexts.
• Several commenters say the site is more useful as a pattern database than as a comparative scoring tool.

What Is a Dark Pattern? Mechanics vs Monetization

• One camp argues: the overlap between “fun mechanics” and the site’s “psychological dark patterns” is huge; what matters is when those mechanics are tied to monetization (loot boxes, microtransactions, wait-to-play with paid skips).
• Others reply that some items (daily rewards, friend spam, social pyramid schemes) are intrinsically manipulative and not fun.
• There is debate over whether competition, grinding, reciprocity, power creep, and “wait to play” are inherently dark or only when used to drive spending, guilt, or habitual daily logins.
• Some define a true dark pattern as any design that serves the business at the expense of the player’s own goals (e.g., obscured subscriptions, tracking, loot boxes with paid keys).

Monetization Models and Live Service Debate

• Many praise pay-once, no-IAP games as healthiest; others defend trials, shareware-style unlocks, or modest F2P models.
• Debate over live-service / card games: controlled power creep can keep a meta fresh, but is criticized when tied to paid card acquisition and devaluing prior purchases.
• Examples discussed include PoE stash tabs, Fortnite’s cosmetics and battle pass, and War Thunder’s “pay to progress” grind.
• A proposal to fund games via background crypto-mining is widely viewed as parasitic or untrustworthy.

Addiction, Players, and Children

• Multiple commenters describe personal or observed harm: lost time, depression masked by grind loops, kids normalizing exploitative designs.
• Others note that “addictive” is not automatically bad if aligned with beneficial goals (e.g., language learning apps), though some argue gamified education still uses the same hooks.

Usefulness and Author’s Clarifications

• The site creator explains the project arose from their own game addiction; learning the patterns helped them quit.
• They emphasize the written pattern descriptions as the core value; the crowdsourced game ratings are outdated, likely noisy, and may be removed.
• Several people report the site (and similar “no BS games” lists) as valuable for finding healthier games and understanding manipulative design, even if the scoring is imperfect.

AI slop, spam, and the degraded web

• Many see AI as “industrializing” existing bad behaviors: spammy tutorials, phishing, scraped blogs, low‑effort PRs, SEO garbage.
• Others argue this era already existed pre‑LLM; AI just changes the flavor, not the underlying problem.
• YouTube and web search are described as increasingly overrun by AI‑generated content; some imagine “human‑only” or paid, curated services as an escape, but doubt this can scale or be reliably enforced.

Search engines, SEO, and AI summaries

• Some praise AI search summaries for bypassing clickbait and SEO slop for simple queries.
• Others say summaries are often subtly wrong, strip context, and make it harder to judge source quality; “slop vs condensed slop.”
• Strong disagreement over whether Google “nerfed” search intentionally for ads versus just losing the fight to SEO. Internal-ad-economics stories are cited as evidence of deliberate degradation.

Fate of small / micro open source libraries

• Many distinguish between genuinely useful small tools and trivial micro‑dependencies (e.g., “left-pad”–style utilities) that arguably never made sense.
• Several see LLMs as the final nail in the coffin for these micro-libs: developers can just generate a 10‑line helper instead of adding a dependency.
• Others counter that mature utilities (e.g., Apache‑style commons) encode years of bugfixes and edge cases; LLM‑generated code is “instant legacy” with unknown behavior.
• Vendoring tiny snippets or header‑only style libs is praised as a middle ground, though critics worry about updates, security, and licensing.

Open source maintenance, spam, and gatekeeping

• Maintainers report a surge of AI‑generated PRs/issues from contributors who don’t understand the project, treating maintainers as free QA.
• This is framed as a “care” problem amplified by AI: low‑effort code at much higher volume.
• Proposed responses: stricter vetting, filters (possibly AI‑based), closed or “cathedral” contribution models—at the cost of making FOSS more gatekept and less welcoming.

Motivations, licensing, and training data backlash

• Some creators now refuse to open source new work (or release binaries only) to avoid it being used as free AI training data, seeing current AI as one‑way extraction with privatized gains.
• Suggestions include copyleft/AGPL to deter corporate use, or “source‑available” licenses, though many doubt this will meaningfully stop scraping.
• Others argue that broad reuse—including via models—is aligned with the original spirit of free software and that obsession over attribution misses the larger benefits.

Education, documentation, and learning

• Concern: LLMs shift culture toward “instant answers” over deep understanding; small OSS and blog posts once served as educational material.
• Counterpoint: LLMs can be superb tutors—patient, interactive, and able to explain code or docs at arbitrary depth. Some projects now ship LLM‑friendly documentation (e.g., llms.txt‑style outputs).
• There’s skepticism about whether people will study LLM‑generated inlined code more than they ever read code buried in dependencies; careless developers may read neither.

Broader outlook

• Some think open source will remain central and even get stronger as motivated developers use AI to tackle more ambitious projects.
• Others foresee burnout: rising spam, corporate control of ecosystems (package hosts, search), and a sense that anything open will just be harvested into proprietary models.
• A shared theme: the real scarcity is care and high‑quality human attention; AI can either free that up for harder problems—or flood it with even more low‑value noise.