There are several payments processing companies that are already largely using AI for customer support queries. They still have an escape hatch to a human but at least one of those companies (on the smaller side) is reporting a ~99% success rate, they are down to a handful of human customer service employees now for cases where the customer can't find/produce the transaction ID.

> There’s no skill file that contains the tacit knowledge of a person who has reconciled a thousand payrolls. That person has zero skill in actually making tight automation that doesn't just fall over. And I have yet to see an AI agent that tells them "look, your requirements are contradictory, given this and that, these two cannot coexist". Those little sycophants will just go and try to please the domain expert and placate him in all ways possible. Bend backwards rather then forcing them to reassess their assumptions.

For the life of me I will never understand the thought process that leads you to say "we don't really know who developed this LLM but I'm going to feed all of my business's data to it"

I've replaced all of these with Go + SQLite: 1. Intercom 2. Zendesk 3. Email marketing 4. Kanban 5. Todo 6. Our billing stack 7. Our issue tracker 8. Our forum 9. Uptime monitor 10. PagerDuty (clone) I have dozens of products I sell, so I thought: why not build everything ourselves? All of these run on the same server and use very little memory. I replaced all the SaaS tools we used with these. I also moved to dedicated servers and dropped costs to about 1/10th of what we were paying for managed cloud solutions, while maintaining the same HA and even achieving lower latency (partly because noisy neighbors on VPSes were increasing tail latency). We used to spend a ton on this stuff. These have now been in production for four months and have only needed minor updates. Deployment is dirt simple. No Docker, no Kubernetes—just a systemd service and a binary built on the dev machine and deployed. We also used to pay for services like MaxMind and IPData. I ended up hand-rolling my own IP geolocation service, which, in my tests, outperforms most existing solutions. It all started with replacing Uptime Robot. Then I got more confident and replaced PagerDuty. After that, I replaced Intercom. Finally, I had always heard people say, "Don't build your own billing stack." But I said YOLO, let me make that mistake myself. So I studied our existing billing solution, developed my own, and rolled it out. So far, we've had zero issues with it. Caddy in front. I found that we only use maybe 1–5% of the features most SaaS products offer, while the features we actually need keep getting buried deeper and deeper inside these "enterprise-grade" platforms, making our workflows more difficult. I won't show my commercial products because our partners and clients probably wouldn't appreciate knowing how cheap I am—but I call it being resourceful. I can show my free app, though, which has 20,000+ users and was launched recently: https://macrocodex.app/ It only uses the Zendesk clone. Email is handled through Cloudflare routing, so we pay almost nothing to run the app.

For human in the loop to be effective, the human needs to actually be performing some substantive action, giving real guidance and critique and pushback. If the human only ever accepts the default plans then not only is there no understanding but the agent should learn to stop asking. It is not learning anything from the human, after all. One thing that I look at is pushback rate: what percentage of the agent's proposals are rejected or critiqued? If it's below 5% I have found I have gotten too credulous and I am no longer closely following. Danger! If it's above 50%, I have clearly not given the agents sufficient context to perform the task and need to update my harness and instructions. Who watches the watchers? I can imagine a guard dog process that halts the session to yell at the human if it detects complacency: if the human is providing too few tokens per minute of new context relevant to the task.

How in the world MCP is going to be more secure? It introduce a big surface layers for injection attacks and supply chain attacks..

I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle). What on earth do you do with that many devs on a project like Messenger? I mean, really? I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out? I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot. I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it should be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.

India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily. This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing. Comments from someone who knows more about this than I do would help here. The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them. Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy. [1] https://economictimes.indiatimes.com/news/economy/indicators... [2] https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...

I started setting up my workflows using Temporal. It deploys as relatively light weight local app. For an isolated local installation it uses SQLite. It makes the process of dealing with API retries and organizing workflows and tasks really simple. I recommend giving it a try. It is, philosophically, exactly what this article is suggesting, but it adds an incredibly rich and flexible interface for agents to work with. Additionally, the web UI makes it very easy to inspect workflows, review agent execution, etc. Temporal also encodes much higher reliability into your system, almost for free. Distributed and reliable systems are hard, don't reinvent the wheel IMO. If you find yourself wanting things like an easy way to then introspect your SQLite database, figure out what is happening in the workflow, compose individual tasks, make workflows trivially callable, etc, give Temporal a look. Alongside this, I have mostly moved away from files for agents. Markdown and JSON are great, but also feel like traps when building out smaller local apps. LLMs are great at SQLite and you can render anything you want out of it (Markdown, JSON, etc). It saves a lot of tokens when an agent can just query a specific row instead of having to fire up jq or grep through markdown. You get a nice portable self contained data management system that encourages agents to be more disciplined about how they structure their data than a bunch of files. It also continues to scale into MySQL/Postgres if your little local projects start to outgrow or become more formal, you already have schema and discipline around data.

I just tested this on a bug fixing benchmark I'm working on. It did not perform as well as I expected. Qwen2.5-Coder-3B (2 years old) outperformed it by a wide range -> fixing ~50% of bugs whereas this model only fixed ~12%. Granted, it's not a coder specific model, but given its benchmark performance to Gemma models, and that it's two years newer, and that it's an MoE with 8B total params, I expected it to be more competitive.

This article is wrong. LLM's encode all the domain knowledge you could possibly want. As a software dev I can query an LLM, become a domain expert in a short amount of time, and then code up a solution. If people think their niche is safe from automation, think again. Even the people who think theyre the masterminds at the top. Edit: Yes "expert" was too strong a word. Proficient would be better. A lot of the barrier to entry in a field is just not understanding the domain.

They are going to do what movie industry is already doing: create shell company for release of each game. Then they will shut down the company when they want, and there will be nobody to come for.

It took me quite a while to come round to OpenRouter. Originally I didn't understand why anyone would put a proxy between them and an LLM, but it actually adds some quite significant value: 1. By far the lowest friction way to support and try out all the models. 2. They offer billing caps! Most model providers still don't do this [EDIT: maybe they do, see reply comment], but if you're going to run anything in public it's very useful to have hard limits so it doesn't cost you $1m overnight because someone started abusing it. 3. Their rankings are one of the more interesting signals for which models are popular, despite their flaws (most OpenAI and Anthropic users don't go via OpenRouter, it's currently not possible to tell the difference between many users switching v.s. one "whale" changing their preferred model) Given how API costs are becoming meaningful for a lot of companies now, having a provider like OpenRouter to help measure your spend and easily experiment with and switch providers feels like a valuable service.

The article doesn't seem to take his train of thought quite far enough. If AI suddenly makes it possible for a law firm to be run with a skeleton crew, then what's stopping all those people you fired from starting new law companies, where AI also does most of the work, and competing with you for the same market? And ultimately, if AI gets to be so good that it can competently do a lawyer's job, what reason do big law firms even have to exist? Who is going to hire them if they can just hire AI? The companies that are rushing so hard to replace their workers don't realise that AI is eventually going to replace them too. I foresee a wave of entrepreneurship coming. AI will empower more people to provide useful services directly to other people, with less middlemen and menial work, and more direct problem solving.

> BNP Paribas runs Mistral models on-prem for KYC in Belgium, with sensitive data staying within the bank's walls. Abanca is using agent orchestration to handle sensitive customer information at a huge scale (2 million customers in their app). For European companies in regulated industries, this is a good alternative to relying on US hyperscalers. Mistral leaning into on-prem and European-hosted models is very smart.

I have led AI integration in a university faculty. From this experience I can conclude that good work is only produced when humans are in the loop. It's not a technical barrier, but a categorical one. "Good" work is defined by humans and our judgment is irrational but rooted in our evolutionary survival needs. In other words, AI don't have human motivation by definition. Without human in the loop, the top most motivation is never fully aligned with us, today, as humans. This removes the premise at the basis of this post.

A good MCP server makes the difference between an agent using 20k tokens and 2 million. It may not matter yet with sponsored Codex and Claude subscriptions, but it will kill many use cases once providers switch to token-based billing. That may sound like an exaggeration, but it’s exactly what I see in our product. Humans developing something already have context that agents don’t have yet. Most agents start a task with virtually no prior knowledge. And they start from zero every single time. That may improve in the future, but we’re not there yet. Can agents get the job done? Yes. But without a thoughtfully implemented MCP server, they are awkwardly inefficient.

I really want Europe to be part of the AI development and research. And I strongly cheered for Mistral. But they are accumulating too much technological delay. This needs to be fixed, otherwise it will turn into yet another proof we are not able to run large tech with good results. Basically any Chinese lab is doing much better. It's not Mistral that created I don't want to say DeepSeek, but MiMo 2.5, Minimax 2.7, and so forth. There are only weaker and/or larger and slower (no MoE) models. Not good.

Why is this time different? Won't super power AI tools allow companies to do more with the same number of people? Don't you think a smarter way to run a business is to capture more of the market if you have the resources to do so? If company A decides they just want the same slice of the market they have now and can fire half of their employees and pocket $$$, can't company B hire the same workers and compete harder with these new extra productive workers they hired? Won't the company B tend to capture more of the market and thus survive longer? In nature we say there are no unfilled niches, meaning that if there were space for something to come compete for resources, it would quickly be 'solved' by the motivating factors involved. Not a precise thing, but a good heuristic. US knowledge-worker compensation is around $10T / year. Anthropic and OpenAI have raised (not spent yet, just raised) $317B. That's ~3% of knowledge worker spending in one year alone. What business wouldn't pay 3, 5 or 10% more a year to make their worker productivity increase by larger factors?

"Agent Readiness" will likely age as well as "Web 4.0 Blockchain Integration" has. (To be entirely clear, not because agents won't be a relevant thing, although certainly I have my doubts, but because I believe even if they are a relevant thing, requiring special allowances from sites undermines the whole point, and such things will only end up used by bad actors to mismatch what agents see to what humans see, and so will be intentionally ignored.)

> This is especially attractive for AI agents and AI-generated workflows. Those systems are often bursty, experimental, and easier to reason about when each agent or tenant has a small self-contained unit of state. I am finding that the most important thing is one big, consistent data warehouse that is updated with the state of the business as close to real time as we can get. SQLite is not really great at this particular problem. Something like Postgres or SQL Server would be much more suitable for an OLAP data warehouse that can serve clients (AI agents) while simultaneously merging massive record sets from upstream business systems. These products also offer intricate permissions control. You can prove to an auditor that your AI solution will never see tables or rows it's not supposed to. SQLite doesn't even have a concept of a user, role or login. > The compute can stay cheap and disposable. Again, hosted sql is better aligned. The alternative is DIY hosted sql (SQLite + some other magic) which immediately violates this rule.

I've thought that skills and small scripts > MCP for quite a while now, tried out MCP in the early days (official ones, ones i made for scripts i already had), but they always end up using more tool calls/tokens than if i had just written a script + skill for claude.

I'm banned from using the free options. At some point they flagged my account as having engaged in model training against their ToS. This despite my account using around £15 worth of tokens over several months, nearly entirely through BYOK providers. The handful of times I did try a free model is when I used their chat interface to quickly compare a few open weight models with a single prompt. That's the only usage I can think which could have triggered the block on my account. Even still, what's the point in have the simultaneous chat feature if using it veers so quickly into a ToS violation. Their support is beyond useless in helping understand the situation. I don't think I managed to speak to anyone other than Tony Bot (or whatever it was named). Edit: Total usage over 1 year: Claude Sonnet 4.6 $8.80 Gemini 3.1 Pro Preview $6.71 Claude Opus 4 $6.19 Claude Opus 4.1 $7.49 Gemini 2.5 Pro $10.06 Claude Sonnet 4.5 $12.74 GPT-5 Codex $2.56 Grok 4 $4.39 Gemini 2.5 Flash Image Preview (Nano Banana) $1.88 GPT-5 $7.30 Others $7.99

How much pontificating needs to be done before people acknowledge nobody has any idea what to do with AI on an individual level? First being good developer and learning how to use AI was sufficient, next it was being able to design architecture, then it was “taste” that made all the difference and now being an expert in the domain is the only thing that matters really. Until AI is basically in a stable, predictable, state of improvement or stagnation, these takes will continue to be pointless and most likely completely wrong.

>“We now observe preparation gaps so severe that instructors must reteach middle-school mathematics while simultaneously teaching the material students need for sciences, engineering, economics, and other quantitatively demanding fields,” they warned. i dont understand why the teachers would go out of their way to reteach middle-school math. i teach. my courses have prerequisites. if a student somehow makes it into my class without a passing-grade grasp of the prerequisites, i will point them in the right direction to get caught up, but i am not spending any class time on it. its not fair to the other students.

This doesn't surprise me at all. From what I can tell, California's education system has moved from "equality" (which I would define as providing similar opportunities to all the kids) to focusing on "equity" (which I think they define as dictating the same outcome for all kids). To get an idea of how off the rails this has gotten, go read up on their statements trying to justify banning high school calculus. They explicitly (in the abstract / introduction of their plan) reject the idea that some kids are more talented at some things than other kids, so if you can compute a derivative by 12th grade, it's due to racial discrimination benefiting you or something. On a related note, instead of writing some Rust code, today, I think I'll go paint a Banksy or something after I finish my coffee. That plan caused a lot of uproar and was blocked before being implemented. Anecdotally, when I asked our local public school for a copy of the curriculum, the teacher said they just teach common core. If you go to the common core website, somewhere towards the top it makes it clear that it is not a curriculum, and just meant to be a lower bar that gets supplemented. Personally, I think all funding in California education (other than terminal levels like 4 year bachelors and up) should be a function of the percentage of students that succeed at the next step. If a local district starts losing funding, then it would have to close / shrink schools, and people from outside the educational system would be allowed to establish independent (secular) charter schools within the district. Those schools would also not be paid unless the students do well in the next phase of their education. This solves the problem of trying to use this as a curriculum back door for climate denial and Islamophobia (or whatever the red states are pushing).

While I agree that domain expertise has always been a moat, I believe the author is missing something critical: there is a big difference between being able to verify the output of a system is correct, and being able to tell a system how to generate the correct output to begin with. Personal example: I had a software engineering colleague who was the best coder of financial management systems I've ever encountered. He gained these skills through years of in-the-trenches development. One of the things he told me, and that I also observed, was that the vast majority of financial experts (basically, the people in the accounting department of companies) had an extremely difficult time just telling him what the rules of any particular transaction should be. But what they could do was tell him whether the handling of any particular transaction was right or wrong. So often times he would sit down with these accounting folks and go through lots of example transactions he came up with, and from there he essentially built up the requirements spec. In my experience, that is the primary difference between people I've known who are good software engineers and those who aren't: people who can specify the detailed rules of any system, vs. folks who take a "well, I know it when I see it" approach. I have a strong suspicion that folks who have a high degree of domain expertise in a particular area will fail as software builders even in an agentic world because they will struggle to elucidate clearly the rules in their head that they've learned over years. As an analogy, it's kind of like asking a native speaker for the grammar rules of their language. Often times they can't, but they'll just say "well, that sounds wrong." They may be "domain experts" in their language, but they'd have a hell of a time prompting an AI system on how to grade a test for grammar correctness.

OK, I'm 100% rooting for both Mistral and task focused small models. But Mistral has fall really far behind since 2025Q3. It seems they can't get good reasoning models working at even medium context sizes, which is necessary to be at the table right now. Gemma4 and Qwen3.6 are currently best in the small size; Mistral's "small" model has ~4x the parameter count at 120B and isn't even competing with models a quarter its size. Back one year ago with Mistral Small 3.1 they were keeping up, but they've fallen into irrelevancy right now. If Mistral seriously wants to play the on-prem and small task-specific model game, a decent proxy would be to build models that get the r/localLlama crowd excited

I'm sure I'm not alone in feeling the "deep expertise" OP laments was actually deeply inconvenient to many people. I understand that there's a good living to be made from knowing browser quirks, hand-rolling accessible components, mastering CSS specificity, but this is largely accidental complexity. More people building things is straightforwardly good, and if some of those things are slower or less accessible, that's a tradeoff people are entitled to make. You can argue that abstractions hide consequences that fall on users who didn't choose them, but I'd argue back that LLMs likely have a better understanding of a11y conventions than I do as well.

I recently reviewed an app built mostly with vibe coding. The owner said it was almost ready to launch and just needed a quick check. After looking through it, the database design was a mess. Some features worked, some didn’t. I explained the missing pieces and why things were breaking. Like OP said, he’s the domain expert. I used billions of tokens last month alone. The tools are getting better fast. But giving AI to a domain expert doesn’t mean you no longer need software engineers. A domain expert can use AI to build software. And a software engineer can use AI to learn about the domain. Both bring different expertise to the table.

I don't understand this obsession with SQLite for real, production apps. SQLite is an embedded database, completely unsuitable for managing concurrency. This is what database _servers_ are for, e.g., Postgres, MySQL, etc. Their entire job is to allow you to modify data from multiple processes, on different machines, at the same time. This is a foundational principle of computer science. It seems to me that the "SQLite for everything" crowd is a little bit inexperienced.

this whole blog post is basically "people need jobs to be happy, so we should design our society such that they need jobs" not only is the premise wrong, but forcing people to work is not a good or ethical way to address this problem most people like the social aspect of work, but not being beholden to their boss we can give people meaning, community, culture, growth, without relying on employment and money we can do better than this

I used to teach high school math. There was a big push for doing everything digitally. And admittedly, for some topics the use of technology in the classroom or at home can really be a benefit, for instance visualizations or interactive exercises. But having a digital device in class was the number one cause of distraction every time. For a lot of things, good old blackboards are just fine as are pen + paper exercises. Maybe even for most high school math. That was frowned upon though by the higher ranks. If I was evaluated as a teacher and didn't include some iPad shenanigans in the class that I was getting audited for, I would have been in trouble. How behind the times! I got along really well with most of my teenage students, it was a lot of fun interacting with them. But the politics behind it all got too annoying. Also, you're under very tight control on what you teach and how, that was super annoying. So I stopped teaching a few years ago and never looked back.

I have AkademikerPension as my pension fund through work and this move suits me quite well. They've already excluded Tesla as well as a variety of companies that profit of weapon production, fossil fuel production or are suspected for human rights violations. https://akademikerpension.dk/ansvarlighed/ekskluderede-selsk...

Can anyone comment on why "big video game" dev pay has lagged "big tech" pay so badly? Ostensibly they are doing remarkably similar engineering problem solving, so why is there such a disparity?

I've always found the idea of letting strangers clean my home strange. Maybe I grew up in the wrong tax bracket. I see cleaning your own home, as well as other chores (dishes, laundry) as an act of self-hygiene. If you want a robot to do your chores, that gives me the same feeling as desiring a robot to bathe you, wipe your bottom and genitals after the toilet, brush your teeth for you etc. Of course these are not apples to oranges, but I can't shake the feeling that you lose something about being a living, breathing being when you give up these mundane chores.

> The bill applies to digitally sold games. However, it excludes games provided via subscription services, free-to-play games, and games that are inherently playable offline indefinitely. It also prohibits the continued sale or distribution of games that have become unusable due to service termination. I believe this is the key paragraph. I wonder if this will be an incentive towards making more games qualify for those exceptions. I think the previous cases where this act would apply are few but good thing they wouldn't increase under this act.

CAPTCHAs are great. Exploiters get around them with proprietary anti-detect browsers and unethical residential proxies, while privacy browsers and affordable privacy VPNs get blocked and shadowbanned to death. Fingerprint.com, while not a CAPTCHA, gives you +3 suspicious score just for using privacy settings like adblock on your browser. This makes it harder to sign up for any sites that use fingerprint.com. https://github.com/CloakHQ/CloakBrowser is a good anti-detect browser as well as CAPTCHA bypass which is honestly fun to use coming from privacy browsers because every site just works and captchas get solved.

The problem we're seeing across many professions is AI output is not getting vetted by knowledgeable people, whether it's an experienced analyst, senior engineer, expert attorney, or the resident physician. At best they skim, at worst they don't even see it at all before it's published, pushed to production, distributed to clients, or submitted to the court. In many cases the skills are available in house to do the necessary vetting, but these people are already overwhelmed with their existing day to day. Anyone remember that item a few months back about Amazon now having senior engineers vet generative AI output (https://news.ycombinator.com/item?id=47323017)? I had to LOL when I read that. These folks are already slammed. And the idea that Amazon would allow human bottlenecks to multiply across projects and underlying infrastructure development is ridiculous.

This sort of thing is a complete embarrassment to a firm like EY, where people are paying them a lot of money for advice. They’ve basically demonstrated that their market leading research is just someone asking questions to ChatGPT. If you ever needed evidence to not buy “advice” from such outfits, this is exhibit one.

> more likely to get planning permission if their new skyscraper included a free public roof terrace If that's the deal, it's crazy that some of those places are getting away with then discouraging the public from actually going there. Book your visit in advance! Present ID! Photography forbidden! This grumpy security guard will be hovering nearby <3 It's like Nathan For You S03E01 where a store advertises a $1 TV, then tells the drawn in would-be customers to please respect the black tie dress code, crawl through a tiny door, and squeeze past the alligator.

The gold standard in hiring qualification is work-sample testing. It works fine. You do not need to "make hiring a profit center" or "provisionally hire" or do internships. Work samples done correctly demand less time from candidates than interviews and scale better than interviews. They are standardizable and iterable. What I feel like I'm reading here is someone who has been poisoned by FAANG hiring practices --- and they are terrible --- and has missed most of the work that's been done (outside of Google's admirable work in debunking their own processes). I appreciate the "kitchen confidential" here, but with respect to Yegge, I think he's been working at the Olive Garden this whole time. Go stage at Gramercy Tavern! They're working at a different scale, yes, but you'll at least get a different perspective on the "gold standard".

I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public. Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend. I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.

This article, like Citrini research's scenario before it, misses much of the economics. AI is unlikely to be as revolutionary as is presumed. It's definitely going to lead to increased productivity, and will probably render some jobs redundant, but it's unlikely to have a significant effect on wages/employment [1], and as of now there isn't one [2]. When it does effect workers (which is still uncommon), AI mostly leads to task reallocation. Right now, AI's massive valuations seem more like a reflection of the typical speculation that accompanies major technological innovations (thinking IoT, railroads, automobiles) than of its real economic value [3]. The "dead economy" scenario would only be possible in the event of extraordinary, and extraordinarily-unlikely levels of AI-driven unemployment. [1] https://economics.mit.edu/sites/default/files/2024-04/The%20... [2] https://www.nber.org/papers/w33509 [3] https://www.foreignaffairs.com/reviews/capsule-review/2003-0...

that's nuts, unless I'm missing something, it doesn't seem like those products are that mind blowingly complex... wow. Makes we want to try building my own for the hell of it. Downdetector in fact just seems to be a website catalog with essentially a guestbook and hit counter...

"The surge in math deficiencies after dropping the SAT highlights a systemic issue: grade inflation. Without a standardized baseline like the SAT/ACT, a 4.0 GPA from a high school with relaxed standards looks identical to a 4.0 from a highly rigorous one. Paradoxically, removing test requirements harms underprivileged students the most. Preparing for the SAT requires a book and an internet connection. In contrast, building a competitive profile based entirely on expensive extracurriculars, sports, and elite summer camps is far more wealth-dependent. Standardized testing isn't perfect, but it's often the only objective equalizer we have."

>Critics call the SAT inequitable and say high school grades are a good predictor of college success. I mean, it seems pretty clear from the last 6 years of experience by professors and others that grades (or at least grades in isolation) aren't a good predictor at all for this. The problem is removing the use of standardized tests here was done for ideological reasons. You can already tell by the use of the word "inequitable" here, because a certain insane subset of policymakers and the public believe that we should push for equal outcomes ("equity") over equal opportunity (usually referred to as simply "equality").

...in the age of AI, does anyone have an actual solution for keeping out bots while preserving the privacy of humans? Obviously this is terrible, but I think there's a possibility it's the least terrible option? Another option is IP reputation, which I think is worse. Or scanning a code with a non-rooted phone, which I think is even worse than that!

This is great news, unions not only improve working conditions, but also improve the final product by not having underpaid stressed staff with high turn-over. It's a good sign for the future product quality of any company to see workers unionise.

I was seduced by Apple Silicon after experiencing the exceptional battery life and performance. Those things are great, as are the screens and the speakers. But I'm still excited about the Framework 12 because I don't love macOS. I don't need an alternative to beat Apple on every line of the spec sheet. I just need them to align with my values, support Linux well, and cross a certain "good enough" threshold. The latest laptops from Framework meet all of those requirements, and I'm excited to buy one after I've saved up enough money. I've missed Plasma for a long time. At the same time, I wouldn't even consider a MacBook Neo.

As nice as Apple's hardware is it's all undermined by who they are as a company, intentionally limiting their devices more and more while they relentlessly argue in courts and to regulators that we owe them more and more for using our devices. Rosetta 2's retirement announcement was when I realized I won't buy another Mac, I'm not interested in a computer that is preoccupied with stopping me from running software. Work can buy them for me but I won't spend my money on a platform like that anymore. Depending on how their Supreme Court argument goes in a few weeks I will stop buying an iPhone too, if they establish the precedent that any method of paying for Netflix deserves a $5/month fee then they will leverage that to extract the same fee everywhere else.

This is the new way and we need to stop it now. Forget the 'is it legal or not' arguments, their lawyers will win. Just get mad and tell them this is wrong. Stop buying their #$@#$ software. Block them. This is what is wrong with cars too. Don't want to give them real time data on you and your passengers and instead try to disconnect the modem? Well, no car functionality for you even if it doesn't need it. -get mad- Stop taking it. Microsoft is the enemy and needs to be treated that way. Same with any tech company that does the bait and switch TOS world. I buy so little software now and it is hard, but unless we stop this now it will only get worse.

The point about the UI affordances strikes me as very relevant. I find that the way I want to use LLMs in coding is not available. We have chatbots in a sidebar that will just generate code for you or, more helpfully, answer your questions. We also have inline LLM code completion, which I've turned off completely because they're incredibly noisy. What I want is something between those. My ideal use of LLMs while coding would be, i start writing a function and need to act on some data. I don't know what method to use, maybe I'm in an unfamiliar language/framework and don't know what my options are. I want the AI to explain what methods I can call to do X in this specific place, no more, no less. It would need to know what outcome I want, which would be hard to do without jumping out of the code and typing into the chat, but I basically want it to function like Intellisense on steroids. Something that doesn't break my focus. Current LLMs are anti-flow. For me, that's poison.

I never want to hear from developers again that they are not susceptible to marketing. I see meet ups specifically about Claude often. Modern tupperware party. A colleague was convinced Claude is better so we played a game. We used the claude code and codex harness and I implemented some prs they needed with gpt5.5 and opus4.7 and asked them to identify which came from which only from the code. Couldn’t tell. Edit: i bet 99% of people here, if presented with a test where i gave 5 models but all of the results came from one, would not be able to discern this. Just vibes all the way down.

Captchas are primarily to punish users for not allowing tracking, or using the “right” services, they may prevent some bots as a side effect (or a pretence from the provider) but it’s mostly for google and cloudflare to abuse their monopolies.

>The US horse population grew from nine million in 1840 to twenty-one million by 1900, seemingly immune to technological change. Within sixty years of the internal combustion engine, the population collapsed by eighty-eight percent. I think this is a very interesting and chilling point, especially if you draw the parallel literally. For quite some time, I was pondering the question:"Who is buying though?". I.e if you automate workers out of labor, who are we selling these AI services to? I guess if global population drops by 80-90℅ you suddenly get a "sustainable" economy, as everything is repriced the economy of scale needs a much smaller scale. (Not speculating this is a plan, just a thought that occurred to me when reading about horses example)

I’ve been using Claude Opus 4.7 with Chrome MCP, and it has worked successfully about 95% of the time. However, I’ve failed various hCaptcha challenges.

Adversaries do not have to wait for LLM models to evolve to mimic human process, they can simply evade the detection JavaScript that evaluates similarity. JavaScript is visible, can easily be reverse-engineered.

> Together, we are organising around the things we want to change. Starting with: Pay transparency Flexible working An end to crunch That’s a lot of demands, what next? Competitive salary?! /sarcasm I hope more people will start fighting together for better work conditions. Company owners have money and lawyers so workers must unite to fight them back. I’m saying this as employer.

I worked mostly on frontend in 2012-16, in plain HTML+CSS, and then quit, because React was required everywhere, and I tried and hated it. But before React, I don't recall frontend as very inspiring and joyful. It was fun to see your work immediately on the screen. I did apply skills and had to solve some weird situations. I could optimize our CSS with OOCSS approach (later used in Bootstrap) -- only to complaints -- semantics! too many classes! (my trump card was that their commits contained +200 lines of CSS, while mine mostly had 0 -- and our CSS was already bloated into several megabytes). But this was a dead end. I tried making tools to find out unused styles, to automate some patterns -- like click a button and load some content over Ajax. But the guys, who copy-pasted code with dumb solution to this, got 2-3x more tickets closed. I proposed a tool to make screenshots of pages and diff them to search for regressions, but the response was it's heavy RnD, we're not a research institute, we got to ship the next popup tomorrow, etc. Nobody gave a shit much earlier.

https://folklore.org/The_Father_of_The_Macintosh.html: “There's no doubt that Jef was the creator of the Macintosh project at Apple, and that his articulate vision of an exceptionally easy to use, low cost, high volume appliance computer got the ball rolling, and remained near the heart of the project long after Jef left the company. He also deserves ample credit for putting together the extraordinary initial team that created the computer, recruiting former student Bill Atkinson to Apple and then hiring amazing individuals like Burrell Smith, Bud Tribble, Joanna Hoffman and Brian Howard for the Macintosh team. But there is also no escaping the fact that the Macintosh that we know and love is very different than the computer that Jef wanted to build, so much so that he is much more like an eccentric great uncle than the Macintosh's father. Jef did not want to incorporate what became the two most definitive aspects of Macintosh technology - the Motorola 68000 microprocessor and the mouse pointing device. Jef preferred the 6809, a cheaper but weaker processor which only had 16 bits of address space and would have been obsolete in just a year or two, since it couldn't address more than 64Kbytes. He was dead set against the mouse as well, preferring dedicated meta-keys to do the pointing. He became increasingly alienated from the team, eventually leaving entirely in the summer of 1981, when we were still just getting started, and the final product utilitized very few of the ideas in the Book of Macintosh. In fact, if the name of the project had changed after Steve took over in January 1981, and it almost did (see Bicycle), there wouldn't be much reason to correlate it with his ideas at all.”

I truly don't get it You have a rock solid piece of software used by an infinite amount of people and other services. It works fine, does it's job and just have some time to time updates due to minor bug fixes. Why do we need AI here? And more over, why people is saying "fork it and use the previous version". It should be actually all the way around, create a parallel fork younamethetool-ai and keep the OG untouched. What I have to do now, keep a fork of my entire system's toolkit?

There are several good points there, but there are also several points where I must disagree. First, Acemoglu may have a Noble Prize (occasionally dubious data selection aside[0]), but even he does not pretend to have the information of a central planner nor does he think that central planning is good idea. If actual businesses, which have local information, believe AI helps them, I'll bet the actual businesses are much more likely to be right, no matter what calculation Acemoglu did or how many Nobels he has. Second, it is likely that AI will eventually be better than (nearly all) humans in most economically useful things. We can debate the timeframe but it will happen and likely not that far away. That Federal Job Guarantee would generate bullshit jobs, and he won't be able to hide that from people. Ultimately, we'll reach an economy which objectively does not need humans and everyone will know it. He needs to face that reality and overcome it, and not hide behind temporary and dubious estimates. Third (admittedly a minor point), while the criticism against EA etc. is very justified, it's not quite fair to blame them (overwhelmingly STEM people) for not reading where the humanities did many of the same errors earlier (the author points out some of these) and discredited themselves. The people who could have taught them to not do it failed to teach themselves. And fourth: I'm pretty sure a lot of company would be able to charge AI agents themselves. The new economy will not be dead, it just won't involve (many?) humans. [0] https://xcancel.com/joefrancis505/status/2059340591490552054...

> Every investor presentation of an AI agent “doing the work of ten analysts” is telling you the same thing: the product is labor replacement. I have a solution for that. Let's use AI to replace all these corporations who just lost their big moats. Conveniently, they just laid off a bunch of people with all the critical know-how and I bet they are very willing to just give it up out of spite.

The assumption is that if you send people checks, they’ll find meaning in hobbies and community. They’ll paint. They’ll garden. They’ll finally write that novel. The author suggests it will fail because we'll all use drugs and booze and commit suicide. But it works for retired people. They love it. Is this why we all have to work 9 to 5 drudge jobs? Because we can't handle the freedom?

After having used Zig for a couple of months now I am convinced it is a fantastic tool language. You just pick it up to hack some idea together freely. Every time I hit a wall, I find the creators have thought of it already and offers comfort. But nothing gets in your face how to use the programming language "correctly". For me it is now the go-to "tinker in my garage" language.

I am not sure why this old news is surfacing here today but I can give my 2 cents, since I sold speedchecker.com last year and were directly competing with Ookla. The main business is selling the data. You use Speedtest.net to troubleshoot your connection but metrics captured with the test alongside location data give telcos invaluable insights on where they should improve their networks. Telcos pay 6 figures annually for this data and we have a few hundreds of of those big MNOs globally. This market is pretty big. Accenture is in trouble with their main consulting business due to AI so acquiring data business is one of the smart strategies they can implement to stay relevant. To all commenters who think they can code it over the weekend, yes you are right. I coded my first speed checker over the weekend in 2008 but it took me 18 years to grow the user base , figure out entreprise sales strategy and exit. Its not easy as it seems.

The abrupt swing in many non-technology company IT departments from "hey developer, you aren't using enough tokens" to this is just too funny. And I'm seeing almost no self-awareness from leaders. They are making decisions about things that they just don't understand. And are completely unworried about it. Just blindly following whatever the news cycle is about AI.

Apologies for the naivety, but, why is SpaceX valued so high? Starlink? Are rockets really a lucrative business? Don’t get me wrong, being able to send objects up into orbit is cool, but is it $1.8T cool?

My friend is an electrical engineer and just passed a FIDE chess rating of 2000. Has played for 30 years, started the chess club in high school. Knows a little programming from the stuff he had to do with microcontrollers in college. I'm an infra/admin jack of all trades with a comp sci degree and have been a hobby programmer for 30 years. I have a Lichess rating of 1000 on a good day. We tried doing a chess bot competition (open book, use AI to program it, pull in opening books, end game tables, whatever, free for all) and I absolutely stomped him, but I've only beat him in real life over the board twice in 20 years. He will beat 99% of random players in real life, and I will beat maybe 20%. I'm not sure what I'm trying to say, but it seems to me that maybe domain knowledge isn't everything anymore? Or the domain itself has shifted?

There's a lot of people agreeing and disagreeing with the article, but on what grounds? How do you know "domain expertise" is a "moat"? Vibes? Has there been ongoing, persistent attacks by AI on domain expertise where we can say the moat holds, economically speaking? So far it seems quite the opposite. So far the evidence seems to be pointing to a different adage, Sutton's Bitter Lesson, which (generalized) says to not bring human expertise to a problem that can be "solved" with unfathomable volumes of data. Because the latter has historically slaughtered the former for decades. But somehow people believe this time it's different? I will counter there is one thing that is a persistent moat, and it's not domain expertise; it's sales. Convincing other humans to part with their money. Humans have shown they will trust a person/human touch to part with their money more than an AI. But I'm not convinced today's AI or tomorrow's won't be able to replicate domain expertise in domain X for any X.

The "frontend skills" whose growing irrelevance are bemoaned in this article consist largely of navigating a minefield of unintuitive edge cases, browser incompatibilities, historic baggage, exceptions to exceptions to exceptions. Modern frontend, or the "tower of leaky abstractions", is finally a common-sense mental model for web development. Supplanted by force on top of an exploding bag of eccentricities that is web standards and conventions. The fact that it works at all and is merely a little leaky is an accomplishment in itself.

> Yes, the EU “cloud providers” are lagging behind but they’re catching up. Scaleway, Herzner, and others are there, and you should check them out if you’re starting a business in the EU. I would argue that these aren't even "cloud providers", they are just VPS providers. Which is fine, but it's not the same thing. There really isn't any European "cloud" service at all, which is a huge part of the problem. And I doubt there ever will be because who would even build it? It would cost billions and billions of euros just to be "not AWS" (but worse in every way except location). Who is investing in that?

> Problem 1: It Devours the Context Window Like would running `linearcli --help` then `notioncli --help` then `slackcli --help` etc, or am I missing something? At least with MCP your harness could add in the context only the title of each tool and add full documentation on demand, MCP server by MCP server and tool by tool. The equivalent would be for all CLI to feature a "--short-descr" command. > Problem 2: Low Operational Reliability If the tool is also using a REST API I see no reason why MCP should be slower, given the protocols are so close. When that happen, it's probably because MCP was added on top of an API, maybe hosted in a far away datacenter by a subcontractor? I won't argue that most MCP servers are probably awful, but that's an argument against the industry not the protocol. > Problem 3: Overlaps with Existing CLI/API Yes, when a CLI tool already exist. A SQL MCP server sounds stupid to me, and a waste of token. Why not a curl MCP? But in the vast majority of shops, a cli tool does not exist. At best they have an API, which is designed to be used by programs not LLMs (you know what I mean). > Provide CLI -> API -> docs, in that order Sure, and instead of slow and wasteful websites companies should first provide a native client for desktop, then a native client for phone.

This shouldn't be legal. The software was clearly marketed as a classic fixed-in-time release, like the old CD releases, that would not be updated but would work indefinitely. Now they're going to boldly revoke the licenses???

This change would go against multiple consumer guarantees in Australia where it's 1) a right to have undisturbed possession of a product 2) products must be fit for the advertised purpose https://www.accc.gov.au/consumers/buying-products-and-servic... Microsoft would be breaking consumer law if the change goes ahead for the perpetual licenses they sold in Australia

I'm getting a little fatigued by all the harnesses that are made by other coding agents. Like, when I checked out opencode, it looked and felt incredibly impressive, until I looked at how frequently it completely invalidated the KV-cache. After looking at the source code, it's basically unsalvageable and I ran far far away. (It's mostly imperative garbage which is typical of undisciplined agent output. It doesn't even use React, it uses some other reactive library in a non-declarative way, I think SolidJS) DeepSeek Reasonix is better in terms of cache stability because that is a core tenet, which should honestly be table stakes for agentic tooling, but the TUI is kind of ugly and the tools also kind of suck (they pretend the sandboxed working directory is at /, which makes the model almost unable to use MCP servers that expect to be passed filesystem paths). On top of that, it doesn't expose the structuredContent of MCP server tool responses, which is like... the entire point of it? Now all my tools that return huge swaths of JSON data into structuredContent, which Claude Code can process perfectly fine, need an additional separate path to generate readable versions of it into content because Reasonix ignores structuredContent for some reason. That's supposed to be the model-side output, while content is the user-side output, but whatever. I don't know how much more of this I can take. I'm in the process of working on my own harness essentially from scratch, manually, because I'm so fed up with all this vibecoded tooling that misses incredibly basic and obvious design. I feel like Claude Code used to be from scratch like this and that was why it was so good, until they started vibecoding large swaths of it and stripping away all the power-user features and good taste that made it so wonderful before. Now it even has random, inexplicable problems like "API Error: 400 messages.1.content.15: `thinking` or `redacted_thinking` blocks in the latest assistant message cannot be modified. These blocks must remain as they were in the original response." which shouldn't even be able to happen!! And like, I get the distillation angle of why thinking output was completely removed from Claude, but I work in bypass-permissions mode and I want to correct misunderstandings as I see them. This is different than wanting to review each edit. Speaking of reviewing each edit, I hate that Reasonix doesn't print diffs, and just says "use git diff". Like, no? I want to see each change the agent made and when. I don't want to only see one diff at the end; that nearly ruins the point of conversation history.

The reasonable compromise should be to force devs to release server binaries if they are not willing to run the servers themselves.

This is such a terrible solution to a literal non-problem. You should be able to make software that has a limited lifespan if you want. I just think that's fine. Games should not be special.

This article's premise is entirely built on the idea that CEOs who layoff people citing AI aren't just lying. And, well, of course they are. If AI was really making these companies meaningfully more productive, they could use that to out-innovate competitors. Instead, they're doing cost-cutting. That only makes sense if you're entirely out of ideas! It's a terribly embarrassing thing to say for a CEO! Really what's going on is that companies do layoffs for all the usual reasons companies do layoffs. And as usual, they never say the real reason because it's embarrassing (we hired too many morons; I founded this place but now I dread waking up every morning because I hate all the middle managers; we just want more money now and not later; etc etc). Instead they say whatever silly excuse is in vogue to say. Right now that silly excuse is AI productivity. A few years ago it was "ZIRP is over oops y'all cost too much now", and before that it was "financial crisis!", which you could get away with for scary many years after Lehman went belly-up. I feel like it's pretty ridiculous to take these remarks at face value and then build an entire what-if theory on top of it. Don't underestimate the possibility that layoffs happen because there happens to be a good excuse around. The occasional layoff can be good for a company. Cut out the dead meat etc. But if it makes you look bad, stock go down etc then you won't do it will you? But when ideas from lesswrong became mainstream enough that you can blame AI for your layoff, then what's stopping you?

Absolutely slamming that upvote arrow. Someone finally put into an in-depth, well-read essay what I've been trying to argue on my blog, in HN comments, in-person for several years now. What they call the "Dead Economy Theory" I've taken to calling the "Anti-Human Economy", but it's basically the same thing: half-assed, milquetoast automations displacing human labor such that capital can continue to accrue upwards and with no consideration for the actual impacts of these changes on humans, society, community, or civilization itself. I'm far from the first to highlight it either. The Animatrix highlighted it beautifully what one can expect in a civilization where machines replace human labor in a general sense, and where systems haven't been built to preserve human interests prior to their rollout - tax schemes, job programs, collaboration rather than competition. Ghost in the Shell has had multiple story arcs about the consequences of displacing human labor without care for the consequences of said displacement, because the displacing party gets all the money and power while remaining unaccountable (or so they believe until the very end) for their actions. Cyberpunk dystopias have been intensely focused on it in video games for decades: System Shock, Deus Ex, Horizon, you name it. All of them take those next steps of "what happens when automation displaces a plurality of labor" and reached the same conclusions on strife, despair, poverty, and the general collapse of social order. These effects have been known for centuries. They are not new concepts. The folks trotting out "people say this about every technological revolution" are those willfully naive to the past historical harms and ignorant of the plight of others in the present. A flimsy excuse to avoid having to stare into the heart of the system and understand its machinations for yourself, to avoid having to accept that yes, you are a part of it too, and therefore bear some degree of blame for how things function. This isn't the loom, or the radio, or the computer coming onto the scene, but generalized intelligence partnered with generalized robotics to replace the entire sum of human labor. This is what the AI firms openly and repeatedly advertise. This is what CEBros continue to do layoffs for, never considering for a single moment what comes after. Excuses of "people need to find meaning outside of work" or "new jobs will be created anyway" are similarly ignorant in narrative, hollow excuses to avoid the most basic of rational thoughts about the system they're defending beyond whatever nugget of faux-intellectualism they can spout out to sound like they have a clue. General intelligence, with general robotics, to replace general labor. There is exactly one way that story ends, and it's not for the benefit of humanity, not under the current systems of governance and systemic incentives we've built for ourselves. It doesn't end with infinite leisure or transhumanism or grandiose visions of utopia, but with the wholesale destruction of human civilization in the name of personal power and wealth.

Until they learn to do that. So cat and mouse. So nothing new.

Apparently CloudFlare’s turnstile can’t, as evidenced by several public-facing CRUD and mail routines we maintain that no longer are warding off the spam.

Software engineering is a domain on its own, just a technical, not a business one. Good luck with looking for a once in a million data race or deadlock bugs. Good luck with synchronizing system distributed over a whole globe. And good luck with keeping your domain knowledge up-to-date while developing and maintaining your vibecoded system. Assuming you can even provide enough details and deterministic specification to AI agent, because understanding business and having knowledge is not equal to being able to write down specific and concise rules to make a system out of it. And if you think LLM are (or will be) good enough to not care about software part, what makes you think that your domain will not be completely resolved by AI?

Too bad api use is like 100x more expensive than subscriptions for the big 3.

A race condition: Two processes intend to add two to a number. They each read the current value. Then they each write back the value which is two bigger then the original. If you instead use private fields and public getters/setters, or use actors to form a protective bubble around the mutable state, you get... The exact same thing but with more boilerplate.

llms.txt is supported by 0 of the relevant ai providers and must be seen as harmful .. as the webmaster implemented something that they might thought has an impact (false sense of impact), but has zero so net gain negative i consider such lists harmful - a good website is one that supports the goal of the website providers and its desired users (some of these users might be bots) a bad website is a website that does everything for everyone just because

> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market. If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request? It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?

I really want a QQQ/VOO replacement that excludes these new rushed IPOs that are just exit liquidity. There are ETFs that exclude harmful industries like gambling, weapons and tobacco. How about an ETF that doesn't include IPOs for six months or until insider lock ups periods are over.

I had to do a Captcha the other day, and the letters looked awful, so I clicked the speaker for an audible Captcha instead. I was even more horrified. The sound was almost painful. Sharp noise blasting as a high pitched tinny voice bellowed numbers at me. I honestly don't know how blind people use the internet these days with such blockers in place, and that's kind of sad. The cookie banners, the captchas and the bots and laws that made both appear have kinda en$hittified humanity's greatest communication tool.

So now I have to fail the capcha to prove I'm human, but in the right way? We don't hate these people enough.

The criticism seems politically motivated. Considering what happened to Blue Origin, SpaceX's success is commendable. Although I agree $1.8T seems crazy.

What's next, in 2027 will they release laptops with 4GB RAM? Are we going backwards?

I’m curious how much AV2 will actually help older hardware in practice. I’m on a 2019 Intel MacBook Pro: 2.6 GHz 6-core i7, 64 GB RAM. The machine is still more than powerful enough for normal desktop work and software dev, but YouTube in Chrome has become borderline unusable for me. My internet is fine, Safari plays the same videos smoothly, and YouTube “Stats for nerds” shows plenty of buffer but the decoding makes youtube unusable in chrome for me.

What's the endgame here? Like the group of psychopath capitalists own everything, automate everything, and devise ways to separate themselves from or un-alives the remainder of the population and live, trade, and war amongst themselves with their armies of robots? Edit: Also this article has so many AI-generated images. I hate that I can't tell if the words themselves are AI-generated or not as well.

> We now observe preparation gaps so severe that instructors must reteach middle-school mathematics while simultaneously teaching the material students need for sciences, engineering, economics, and other quantitatively demanding fields I was annoyed to not find specifics. I would be surprised if the K12 school board and university STEM professors are in agreement about what middle school mathematics is. Trig comes to mind as a common stumbling block. I could be forgetting, but I don't recall much of it on the SAT. If I had to pick one area of math where the gap between learning something initially and actually being shown its broader applicability is the longest, it would be that. Like a decade between SOHCAHTOA and diffeq / fourier probably.

I've recently been thinking about pulling my money from all of the US funds that I currently have. I really don't want my investments to be in SpaceX, OpenAI or Anthropic.

If you do not like Elon, you can simply move your assets to a direct indexing fund, there are plenty of them at reasonable cost, including from the large brokerages. If you believe SpaceX is overvalued or do not like the way it is being handled by the big index funds, again, use direct indexing. akademikerpension is pretty decent fund, it is about 50/50 asset allocation, losing out by only .9% per year compare to a US equity/bond portfolio. Better than many active funds: https://www.finanshus.dk/wp-content/uploads/2023/02/Pensions... https://testfol.io/?s=h8azNZvMICk You do not like the valuation ? What should a company that launches 98% of the world's non government tonnage to space (80% if you include the Chinese government) be valued at ? The only company that has figured out how to very reliably launch at a sustained and rapid pace ? Pioneered and is perfecting rocket reuseability ? The only thing we can can say with a degree of certainty is that $2T is either very overvalued or very undervalued. If you believe that space will become a huge part of our economy in the future, and believe that SpaceX will play a significant role, $2T is cheap. Dirt cheap. The only way to prosper is to be bold. For all those who come here to say that they do not like Elon or that the valuation is ridiculous, or that SpaceX will not succeed, that is perfectly fine - you are just a few clicks away from making it happen. Sell your assets and buy a direct indexing product, simply buy the stocks you want, buy ex-US, or any other number of options you can do on your phone with a few clicks. Less clicks than it takes to virtue signal on this forum.

For thousands of years, people have seen the benefits of living in cities.What is really a city? Simply a place where people have a mutual interest in living close to each other. Urban sprawl and car centric society seems to be a really bad idea. Build better cities rather than self driving cars.

What I don't like in Frameworks: Tiny screens. Imagine running a browser on a 13" screen, where part of screen space is used by taskbar, tab headers, address bar, sticky site header, cookie bar and you get less than 50% left for content. And of course site designer will use the largest font available so that you can fit only one paragraph of text into remaining space. Obviously you cannot fit VS Code or KDEnlive (it has so many panels!) into this small screen as well. I would prefer to buy 17" but sadly such laptops are considered "professional" and therefore overpriced so I had to settle with smaller screen size and cope with it. Small screens are only good for browsing social networks with post character limits and not for work. You could buy a monitor, but monitors aren't free and you cannot take it with you when travel (to the couch). They tend to use the most expensive CPUs which do not have the best cost/performance ratio. Mid-range, mid-low CPUs are better. Standard US-style keyboard. Doesn't have layout switch keys and extra keys for languages which have more than 26 letters which is like half of the world? To be fair, Macs or PCs don't have them either. PC manufacturers would rather add useless numpad than keys for foreign languages. Also, it doesn't have large arrow keys, and page up/page down and how do you scroll the code without them. I also do not like an idea with expansion cards for ports. Just add 6-8 USB ports, video and audio and you do not need any expansion modules which could save lot of money for the customers. Having 8 USB ports for free is better than having to buy 4 expansion modules. Also there is no need to customize color, it is waste of money Obviously it has lot of good features but currently it is more reasonable to buy a standard laptops for ⅓ price of 1 framework and install Linux. By the way, Macs seem to have no replaceable parts, like RAM or SSD. I wonder what Mac owners do when keys start falling out from keyboard, do they buy a new Mac, or keys on Macs never fall out? On PCs, I replace the keyboard every 2-3 years.

Estrogen (specifically Estradiol, E2) is one of the most important systemic hormones in both men and women I've spent a significant amount of my free time for the last 15 years studying androgen physiology and self-experimentation. Here are a few facts about estradiol that others might find surprising: 1. E2 acts as a master metabolic/energy regulator in humans. ER-alpha and pan-ER agonists are being developed for obesity and metabolic disorders. Example: SLU-PP-332 2. Libido in males is regulated by E2. Androgens like testosterone/DHT seem to be required to support the biology of erectile function, but for mental libido estrogen is the primary component. 3. Estradiol is synergistically anabolic with androgens. This is why cattle hormone implants contain a blend of Trenbolone and E2 Estrogen has so many supporting functions in brain, muscle, adipose tissue, and bone health... Apologies for no citations and rough formatting but currently on a phone. Happy to provide citations when home

I read a little about BitLocker. It seems to store the encryption key in TPM and acquire it automatically after boot. I wonder, can encryption key be extracted by inserting a rogue PCIe card and reading it from memory, or by inserting a rogue DDR memory card with a backdoor to read the key from it, or by sniffing CPU - TPM bus?

I would encourage affected customers to go to small claims court. You’ll probably get a default judgment. Small claims court was created for just this type of issue.

Meta comment: This is a domain under my countries TLD (Slovakia) and it is one of the handful of words that are a word with the TLD in my language (and coincidentally) also in English. Every now and then, I will check on the domains with a retrograde dictionary for domains that have this property and root of this particular domain had a roundcube email server on it (can be checked on archive.org). After further checking, the local company actually named themselves Obeli s.r.o. (s.r.o. is Ltd), presumably so that they could use a domain that is a real word when said together with the TLD. (EDIT:) Forgot to write the thing I wanted to mention in the first place: it appears the domain must have lapsed and/or the author bought it from the company that was using it. Another fascinating fact: our countries TLD has been stolen Ocean's 11 style (I am not kidding). After Czechoslovakia split into Czech Republic and Slovak Republic, the newly created Slovak .sk TLD has been under the care of people from the local university. The university also had some offices that they were leasing out. Someone had leased this office space (EDIT: this is important as this means they had the same physical address), created a company that had the same name as the NGO that was taking care of the domain, so e.g. the NGO was named "My Company o.z." and the perpetrator created a "My Company s.r.o." (our countries version of the american Ltd). This person then wrote to ICANN to change the address to the "My Company s.r.o." presumably under the pretense that this was just an administrative error and from this point, they have functionally taken custody of the TLD. I was not able to find how they did it technically, but I presume they persuaded ICANN to then point to their servers instead of the real ones. After this happened, it seems that no one noticed for some time. When they noticed, they tried taking it back, but they weren't able to. For some inexplicable reason, the government during that time (Šuster era, early 2000s) gave the new company a contract that was functionally uncancellable from the government side. Later governments made this even more uncancellable and in 2017, then Minister of IT (and as of this day president!) Pellegrini made the contract literally uncancellable. As a result of this, we have one of the most expensive domains around (18e/year, rising each year for no good reason). (EDIT:) The company running our countries TLD is now a foreign entity that the whole thing has been sold to (multiple owners over time) and we as a country have no control over if I understand it correctly. I might have gotten some details wrong as I am writing this from my memory of researching it a couple of years back, but you get the idea, crazy stuff. Here is an article in Czech [0] that tells the story a bit better, but you have to translate it. [0] https://www.root.cz/clanky/pribeh-domeny-sk-aneb-kradez-za-b... // EDIT: I have found that the article actually links the movement to return the TLD back [1]. It also has a story tab [2], so they have something much more precise than the paraphrasing I wrote. [1] https://www.nasadomena.sk/ [2] https://www.nasadomena.sk/historia/

Signals I've got from this post: - Steve's company got acquihired by Amazon, granting him a free ticket in without all the torment of the multi-stage interview pipeline. - It's a well known fact that it's easier to jump from one FAANG to another, so while interviewing at Google he had significant advantage, plus the blog gaining popularity. - All of this has caused a deep down imposter syndrome, which resulted in an attempt to "improve" an interview process from the inside - but the wings were clipped pretty quickly by the corporate politics. It turns out that lawyers are not planning to reinvent anything there and hence are somewhat more important than engineers. - The post itself is an self-applause over essentially a failed effort. "I've tried"

First model I've tried that gave me back HTML with a "Change Pelican Color" button: https://static.simonwillison.net/static/2026/hy3-preview-pel... (Transcript: https://gist.github.com/simonw/c2a0d8ecd3056a2681319eae8fc3f...)

I am so used to thinking that Zig, Rust, and the likes are only viable in niches where C is viable, but no. not anymore at least - once this linker and incremental compilation on other targets land, Zig will become THE C replacement and that will let me iterate at the speed of JS or Python with performance of C or Rust. even Andrew's initial dream - to create a DAW with uncompromising UX - will become much easier to create. once someone creates a Zig-native immediate-mode or reactive UI framework, that is. I am still a little salty about `@cImport` removal, though! without it, I can't confidently call it "Kotlin of C" anymore.

Bun is moving towards rust but does this also help bun's compilation times? https://ziggit.dev/t/bun-s-zig-fork-got-4x-faster-compilatio...

I think it's just a game of cat and mouse. It might be easier to catch naive AI agents that are not fine-tuned for specific CAPTCHA tasks with human behavior, can't recognize new challenges, don't know when to stop and ask a human, and just want to brute force their way with limited or no specialized harness and tools available.

This feels like the kind of thing where, "you must be at least this human to pass" and that it just otherwise mostly wastes your time if you're a robot would cover most of what Captchas are useful for. Like, if it takes you 3-5 seconds to get through a captcha as a human, as long as every single event has that effort added, the impact to something trying to use/reuse the end-page is way worse if you're a robot than if you're a human. I can see a few usecases where it would still be valuable to continue the game of cat-and-mouse, but I feel like solving for consistency of human experience of your website, may actually be more punishing to anything trying to bypass it.

- LLMs can't learn, therefore, LLMs are only good for things on which they are trained. - Captchas are not friendly with trial and error, so agentic solutions also don't help. - It's impractical to train LLMs on everything. - We humans are capable of creating infinite ways of captchas. While each of these sentences is true, captchas will always win against LLMs.

What happened to adversarial attacks? I.e. noise that makes an image look like something else to a classifier than to humans. I guess frontier LLMs are no longer vulnerable to those?

Appreciate this article...shows some interesting insights on how humans "behave" vs agents.

But.. the task was never "detect this" but always "detect this within acceptable constraints". Sure, once you collect enough bits, you can tell that its me. And if you know from other sources that I am human, that solves your immediate problem. But if you do that, you have still failed at the task of detecting certain kind of abusive behavior without harming my anonymity.

Just ask, "I need to wash my car. If a carwash is 50 ft away should I walk or drive?"

I wonder if AI could be detected via copyright. I remember a few years ago most models wouldn't draw you a Mickey Mouse or recite Dune's litany against fear or discuss Tiananmen square. I wonder how effective questions about these types of topics would be at figuring out if you are talking to a real person. As a crude joke that is only tangentially related, I saw a skit video a while ago with two guys saying goodbye and one says "send me a dick pic when you get home" and then explains that an AI won't simulate it so this is a sure way to know that it's his friend confirming his safe arrival.

I wanted to see how well Akademikerpension has done wrt. returns. This graph shows average yearly return from the financial crisis 2009 until 2021 and they are actually the best performing among other Danish pension funds [1]. [1] https://www.finanshus.dk/wp-content/uploads/2023/02/Pensions...

This seems like an interesting case to test AI agents on. Like we had weird examples like C compilers and Bun. This is a much more interesting example because its highly nontrivial. AV1 exists, Dav1d exists. Lets see AI take the AV2 spec and Dav1d code and try to make a working high performance AV2 decoder.

The standard take, including my own from last year, is that these tools amplify senior developers because senior developers have judgment. My take is much less charitable. I think a lot of senior devs are lonely and enjoy talking to chatbots all day. Saying it amplifies their productivity is a justification.

In my own experience this is 180 degrees from reality. As a generalist, feeling out the depths of a single domain (something I've been forced to do at least 50 times in my career, to the point that I'm probably a global expert in at least 2-3 things I don't actually care about, but are poorly documented and not especially lucrative on their own) is something that's basically a bunch of Google searches, reading source code, and writing/running tests manually, none of which I really care about short of getting to "the right solution." Meanwhile, as a generalist who has a basic understanding of general things, everything from how to design efficient network protocols, to how cache lines affect the performance of sorting algorithms, without being a real expert in any of those things, I act as a constant course correction for AI agents doing work on my behalf, in a way that LLM context windows simply cannot replicate. To give a concrete example, I recently used agents to build a specialized sync protocol that broadly resembles Dropbox. It's nowhere near as efficient in terms of how blocks are synced (because it entirely happens on a LAN and the cost difference is minimal), but I constantly had to make objectively more valuable course corrections on how the sync actually traversed the participating nodes. If I'd just let the LLM drive, it would have come up with a reasonably efficient algorithm (better than I probably would have done on my first try in the same timeframe) that would have had an obvious (to me) single bottleneck.

This looks like slop from a slop factory. "SEO", "Agent-readiness". That's precisely what a good website doesn't do (to paraphrase the homepage). Oh yes, it's produced by a Wordpress "SEO" expert and private investor using Claude LLM. What a surprise. A man who built a fortune destroying the internet we loved with advertisement slop now working on destroying whatever's left with LLM slop.