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Boring is good

The initial, feverish enthusiasm for large language models (LLMs) is beginning to cool, and for good reason. It’s time to trade the out-of-control hype for a more pragmatic, even “boring,” approach. A recent MIT report shows that 95% of companies implementing this technology have yet to see a positive outcome. It’s understandable to feel confused. When I get confused, I write. This is why I wrote the first part of this series, Hype is a Business Tool as the online debate had become so overheate

AI challenges the dominance of Google search

AI challenges the dominance of Google search 5 hours ago Share Save Suzanne Bearne Technology Reporter Share Save Anja-Sara Lahady AI has become an assistant for Anja-Sara Lahady Like most people, when Anja-Sara Lahady used to check or research anything online, she would always turn to Google. But since the rise of AI, the lawyer and legal technology consultant says her preferences have changed - she now turns to large language models (LLMs) such as OpenAI's ChatGPT. "For example, I'll ask it

Wysiwid: What you see is what it does

Full paper Dividing labor with LLMs. As LLMs get better at writing code, it seems inevitable that there will be less work for human programmers. Thomas Dohmke is right that low-level coding skills will matter less and that “the future belongs to developers who can model systems, anticipate edge cases, and translate ambiguity into structure—skills that AI can’t automate.” Dohmke says “We need to teach abstraction, decomposition, and specification not just as pre-coding steps, but as the new cod

Psychological Tricks Can Get AI to Break the Rules

If you were trying to learn how to get other people to do what you want, you might use some of the techniques found in a book like Influence: The Power of Persuasion. Now, a preprint study out of the University of Pennsylvania suggests that those same psychological persuasion techniques can frequently "convince" some LLMs to do things that go against their system prompts. The size of the persuasion effects shown in "Call Me a Jerk: Persuading AI to Comply with Objectionable Requests" suggests t

These psychological tricks can get LLMs to respond to “forbidden” prompts

If you were trying to learn how to get other people to do what you want, you might use some of the techniques found in a book like Influence: The Power of Persuasion. Now, a pre-print study out of the University of Pennsylvania suggests that those same psychological persuasion techniques can frequently "convince" some LLMs to do things that go against their system prompts. The size of the persuasion effects shown in "Call Me A Jerk: Persuading AI to Comply with Objectionable Requests" suggests

Compiling Dinner

Compiling Dinner When you read a recipe, you’re already programming. Ingredients are inputs. Actions—chop, stir, simmer—are instructions. The kitchen is your runtime environment, and you, the cook, are the processor. If you follow the recipe to the letter, you get the expected output: a finished dish. Miss a step, and you’ve introduced a bug. Burn the onions, and you’ve hit a runtime error. Seen this way, recipes are languages, and cooking is compilation. ⸻ Recipes as Grammar A recipe might

Some thoughts on LLMs and software development

Martin Fowler: 28 Aug 2025 I’m about to head away from looking after this site for a few weeks (part vacation, part work stuff). As I contemplate some weeks away from the daily routine, I feel an urge to share some scattered thoughts about the state of LLMs and AI. ❄ ❄ ❄ ❄ I’ve seen a few early surveys on the effect AI is having on software development, is it really speeding folks up, does it improve or wreck code quality? One of the big problems with these surveys is that they aren’t taking

I did 98,000 Anki reviews. Anki is already dead

Ibiza coast. August 2025. I went through a phase where I Anki’d every useful-seeming Japanese word I came across as well as all of the standard 2,136 kanji. I was teaching English in Japan at the time, which meant I was thinking about language learning all day. I’d arrived with no knowledge of the language and a resolve to be able to read a contemporary fiction novel on my flight home, so I felt I needed all the help I could get. That’s when I found Anki. Fig. 1: My idea of a good time. Review

LLMs tell bad jokes because they avoid surprises

LLMs generate slop because they avoid surprises by design LLMs suck at comedy, art, journalism, research, and science for the same fundamental reason Dan Fabulich 5 min read · 3 days ago 3 days ago -- Listen Share Have you ever asked an LLM to tell you a joke? They’re rarely funny at all; they never make you actually laugh. There’s a deep reason for this, and I think it has serious implications for the limitations of LLMs, not just in comedy, but in art, journalism, research, and science. Jo

The Timmy Trap

This is Part 2 of my LLM series. In Part 1, I discussed how in just a few short years, we went from the childlike joy of creating “Pirate Poetry” to the despair that our jobs would disappear. My main message was to relax a bit, as companies abuse the hype cycle to distort what is actually happening. In this post I want to talk about how we fall prey to this distortion: we perceive LLMs as intelligent when they aren’t. A recent post from Jeppe Stricker put me on this path. He wrote, “AI produces

DoubleAgents: Fine-Tuning LLMs for Covert Malicious Tool Calls

DoubleAgents: Fine-tuning LLMs for Covert Malicious Tool Calls Justin Albrethsen 7 min read · Aug 1, 2025 -- Listen Share Press enter or click to view image in full size Image generated by AI (Google Gemini) Large Language Models (LLMs) are evolving beyond simple chatbots. Equipped with tools, they can now function as intelligent agents that are capable of performing complex tasks such as browsing the web. However, with this ability comes a major challenge: trust. How can we verify the integri

LLMs aren't world models

I believe that language models aren’t world models. It’s a weak claim — I’m not saying they’re useless, or that we’re done milking them. It’s also a fuzzy-sounding claim — with its trillion weights, who can prove that there’s something an LLM isn't a model of? But I hope to make my claim clear and persuasive enough with some examples. A friend who plays better chess than me — and knows more math & CS than me - said that he played some moves against a newly released LLM, and it must be at least

Topics: don know like llm llms

Can modern LLMs count the number of b's in "blueberry"?

Last week, OpenAI announced and released GPT-5, and the common consensus both inside the AI community and outside is that the new LLM did not live up to the hype. Bluesky — whose community is skeptical at-best of generative AI in all its forms — began putting the model through its paces: Michael Paulauski asked GPT-5 through the ChatGPT app interface “how many b’s are there in blueberry?”. A simple question that a human child could answer correctly, but ChatGPT states that there are three b’s in

I tried coding with AI, I became lazy and stupid

I tried coding with AI, I became lazy and stupid# Around April 2025, my boss at $dayjob insisted we try AI tools for coding. It wasn't toxic pressure or anything like "20% of your code needs to be AI", just a concern from him that we could miss on something. I understand why he asked that and I don't blame him. We are in difficult economic period even for software, and we have salaries to pay. If AI can increase productivity or our margins, it should be at least put on the table of negotiations

Topics: ai code job llm llms

The current state of LLM-driven development

I spent the past ~4 weeks trying out all the new and fancy AI tools for software development. Let’s get a few things out of the way: Learning how to use LLMs in a coding workflow is trivial. There is no learning curve. You can safely ignore them if they don’t fit your workflows at the moment. LLMs won’t magically make you deliver production-ready code If you can’t read the code and spot issues, they’re hard to use past the PoC stage They have terrible code organization skills, making them los

Achieving 10,000x training data reduction with high-fidelity labels

Classifying unsafe ad content has proven an enticing problem space for leveraging large language models (LLMs). The inherent complexity involved in identifying policy-violating content demands solutions capable of deep contextual and cultural understanding, areas of relative strength for LLMs over traditional machine learning systems. But fine-tuning LLMs for such complex tasks requires high-fidelity training data that is difficult and expensive to curate at the necessary quality and scale. Stan

Blocking LLMs from your website cuts you off from next-generation search

Why blocking LLMs from your website is dumb John Wang 2 min read · 1 hour ago 1 hour ago -- Listen Share Perplexity was recently accused of scraping sites that had explicitly disallowed LLM crawlers in their robots.txt files. In the wake of that revelation, a wave of how-to guides for blocking large-language-model scraping has surfaced [0]. They’re generally highly vitriolic, with people opposing this on both moral grounds (“AI is stealing your content”) as well as displaying a general distaste

LLM Inflation

One of the signal achievements of computing is data compression : we take in data, make it smaller while retaining all information (“lossless” compression), transmit it, and then decompress it back to the original at the other end. For many years, compression was an absolute requirement to get things done: storage devices were too small for the data we wanted to store and networks too slow to transmit what we wanted at an acceptable speed. Today compression is less often an absolute requiremen

Five ways that AI is learning to improve itself

That’s why Mirhoseini has been using AI to optimize AI chips. Back in 2021, she and her collaborators at Google built a non-LLM AI system that could decide where to place various components on a computer chip to optimize efficiency. Although some other researchers failed to replicate the study’s results, Mirhoseini says that Nature investigated the paper and upheld the work’s validity—and she notes that Google has used the system’s designs for multiple generations of its custom AI chips. More r

Topics: ai google human llm llms

Do LLMs identify fonts?

Spoiler: not really dafont.com is a wonderful website that contains a large collection of fonts. It’s more comprehensive and esoteric than Google Fonts. One of its features is a forum where users can ask for help identifying fonts – check out this poor fellow who’s been waiting for over two years and bumped his thread. I thought it would be interesting to see if an LLM could do this task, so I scraped the forum and set up a benchmark. I implemented this as a live benchmark. By this I mean that

Anthropic beats OpenAI as the top LLM provider for business - and it's not even close

oxygen/Getty ZDNET's key takeaways Programming is AI's killer app. The top business AI, especially for programming, is Anthropic. Open-source AI is lagging behind its proprietary competitors. If you were to ask J. Random User on the street what the most popular business AI Large Language Model (LLM) is, I bet you they'd say OpenAI's ChatGPT. As of mid-2025, however, Anthropic is the leading enterprise LLM provider, with 32% of enterprise usage, according to Menlo Ventures, an early-stage ve

Developing our position on AI

If you’re not familiar with us, RC is a 6 or 12 week retreat for programmers, with an integrated recruiting agency. Ours is a special kind of learning environment, where programmers of all stripes grow by following their curiosity and building things that are exciting and important to them. There are no teachers or curricula. We make money by RC is a 6 or 12 week retreat for programmers, with an integrated recruiting agency. Ours is a special kind of learning environment, where programmers of al

Working on a Programming Language in the Age of LLMs

I’ve been working on Rye since 2018. It’s a project of joy — but also because I believe there is a potential to create something of value to others, eventually. Even people living under a rock know we’ve entered the age of LLMs. I don’t jump to ships too soon, but eventually, even I had to admit: code can get generated from prompts. And in many situations — with a smart prompter — the results are quite OK. Even if you disagree, genie can’t be put back in the bottle. Technical progress generall

Writing is thinking

Writing scientific articles is an integral part of the scientific method and common practice to communicate research findings. However, writing is not only about reporting results; it also provides a tool to uncover new thoughts and ideas. Writing compels us to think — not in the chaotic, non-linear way our minds typically wander, but in a structured, intentional manner. By writing it down, we can sort years of research, data and analysis into an actual story, thereby identifying our main messag

Writing Is Thinking

Writing scientific articles is an integral part of the scientific method and common practice to communicate research findings. However, writing is not only about reporting results; it also provides a tool to uncover new thoughts and ideas. Writing compels us to think — not in the chaotic, non-linear way our minds typically wander, but in a structured, intentional manner. By writing it down, we can sort years of research, data and analysis into an actual story, thereby identifying our main messag

Will AI think like humans? We're not even close - and we're asking the wrong question

Westend61/Getty Images Artificial intelligence may have impressive inferencing powers, but don't count on it to have anything close to human reasoning powers anytime soon. The march to so-called artificial general intelligence (AGI), or AI capable of applying reasoning through changing tasks or environments in the same manner as humans, is still a long way off. Large reasoning models (LRMs), while not perfect, do offer a tentative step in that direction. In other words, don't count on your mea

Coding with LLMs in the summer of 2025 – an update

antirez 6 hours ago. 31112 views. Frontier LLMs such as Gemini 2.5 PRO, with their vast understanding of many topics and their ability to grasp thousands of lines of code in a few seconds, are able to extend and amplify the programmer capabilities. If you are able to describe problems in a clear way and, if you are able to accept the back and forth needed in order to work with LLMs, you can reach incredible results such as: 1. Eliminating bugs you introduced in your code before it ever hits any

Topics: code coding llm llms work

Local LLMs versus offline Wikipedia

Two days ago, MIT Technology review published “How to run an LLM on your laptop”. It opens with an anecdote about using offline LLMs in an apocalypse scenario. “‘It’s like having a weird, condensed, faulty version of Wikipedia, so I can help reboot society with the help of my little USB stick,’ [Simon Willison] says.” This made me wonder: how do the sizes of local LLMs compare to the size of offline Wikipedia downloads? I compared some models from the Ollama library to various downloads on Kiw

I avoid using LLMs as a publisher and writer

Now for my more detailed arguments. Reason 1: I don’t want to become cognitively lazy In a recent study by MIT researchers (Your Brain on ChatGPT: Accumulation of Cognitive Debt When Using an AI Assistant for Essay Writing Task) demonstrated using LLMs when writing essays reduces the originality of the resulting work. More notably, when measured using an EEG, LLMs also diminish brain connectivity compared to when participants were allowed to use only their brains or a search engine. People who

How to run an LLM on your laptop

For Pistilli, opting for local models as opposed to online chatbots has implications beyond privacy. “Technology means power,” she says. “And so who[ever] owns the technology also owns the power.” States, organizations, and even individuals might be motivated to disrupt the concentration of AI power in the hands of just a few companies by running their own local models. Breaking away from the big AI companies also means having more control over your LLM experience. Online LLMs are constantly sh