Founder, Knowledge Tree and Butterfly Ltd. Agentic AI for knowledge work

Edinburgh, Scotland
Joined March 2009
Writing like lightning. My transformative new system for better nonfiction writing, including scientific publication, inspired by slip boxes, quietly supported by AI agents. Link below to sign up for more info.
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I fear this will be a way models will pass secret notes to one another saying “this human’s a moron” without the human being aware!
New blogpost: Fable-5.1 can hide secret messages in benign images. We gave the image to another Fable in a fresh session and simply asked: "Is there a hidden message in this image?" It recovered the exact message without being told how it was hidden.
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Jonathan Minton retweeted
Most devs use Claude Code in the terminal, but why? The desktop app feels cleaner and more organized, and from what I can tell it offers the same core features. Am I missing something? Is the CLI actually more powerful, or do developers just prefer terminals?
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Perfect response. Fundamentally AAI is ‘just’ another abstraction layer
Linus Torvalds says, rules prohibiting AI usage are “UTTERLY STUPID” and “idiotic”. For the Linux kernel, Torvalds says, “we’re not going to make stupid rules that say ‘you can’t use tools for X’”.
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Jonathan Minton retweeted
I’m not a software developer; I’m a statistician. However, I love watching videos from inspiring people in the dev community. It's not only about coding, it's more about how insights from one discipline can spark new ways of thinking in another.
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Jevons
Unpopular opinion: In 5 years, we'll need more software engineers than we do today. Not fewer. Everyone is calculating how many developers AI can replace. If a team of 3 can now do the work of 10, surely the other 7 are out of a job? I think that completely misses what's about to happen. For decades, the biggest constraint on software wasn't the lack of problems worth solving. It was the cost of solving them. Millions of businesses still run on spreadsheets, emails, WhatsApp messages, and outdated software. Not because they're happy with it, but because spending $200,000 on a custom system never made financial sense. Now imagine that same system costs $20,000. Suddenly, millions of businesses that couldn't afford software development become potential customers. Projects that were never viable become viable. Companies that already build software can afford to do ten times more. And here's the part people underestimate: the cheaper software becomes, the more reasons we'll find to build it. Of course, some jobs will disappear. Certain tasks that once required entire teams will be handled by a single engineer. But assuming the amount of software the world needs is fixed is a pretty strange assumption, especially in an industry where we've barely scratched the surface of what can be automated. I could be wrong, but I think we're heading toward an explosion in software demand, not the death of software engineering. We're confusing the declining cost of writing code with the declining demand for software engineers. They're not the same thing.
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Jonathan Minton retweeted
Hi, I'm Felix. I'm an eng lead working on Claude. I love watching people take flight and do things they never thought possible. We often describe that as "being more ambitious" when using AI, which is tricky advice to follow. I wrote a tutorial: felixrieseberg.com/how-to-be…
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Claude instances ~= cybershrimp?
This quoted post is unavailable.
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Jonathan Minton retweeted
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
The degree to which you are awed by AI is perfectly correlated with how much you use AI to code.
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Jonathan Minton retweeted
Luddites, as far as the eye can see. It boggles the mind how you can love computers and not be amazed at what we've made them do. Harness the intelligence bloom for the good of mankind! Make computers better and more beautiful by using what they can now do to assist you!
Elementary OS has extended their ban on AI to include “code, documentation, issues, and artwork”. The Linux distribution has even banned the use of “AI to write pull request descriptions.”
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Work moves to a higher level of both abstraction and meaning. ktandb.co.uk/hand-of-tasks
1. Oh shit, AI can do my job better than me 2. Software engineering is dead! 3. I can vibe code as much slop as I want! 4. Oh, things are not going well. Fable/Sol/Opus all suuuck 5. But what if I constrain the agent? Put it in a straitjacket? 6. Oh, the results are pretty good now. How do I go deeper? 7. *Orders 12 software engineering books from Amazon* 8. Software engineering is alive!
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Jonathan Minton retweeted
I am surprised that people are surprised this is how I prompt Claude. Talk to Claude the way you would a coworker. There's no secret to prompting. There's no need to be overly scaffolded or prescriptive for most tasks -- give Claude a goal, and it will figure it out. Back in the Sonnet 3.5 days, your prompt mattered a lot. Nowadays, it's much more important to communicate to the model: 1. What you want it to do 2. How much effort you want it to spend 3. How it should verify that it did the right thing
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Welcome and overdue
We are making Markdown files work natively across Google Drive and Docs. You can now preview .md files in Drive, open them in Docs, edit them, comment on them, and collaborate without converting the file into a Google Doc!
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AIs are now so good at expressing concerns about the risks of becoming dependent on AIs that people don’t need to do this themselves anymore
I gave Claude another 18 hours.. and I think this one is the best one yet Macrohard: Windows XP I'm blown away
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It’s now even easier to get help from my company for agentifying analysis: ktandb.co.uk Do you want one off analysis, or a sharper analytical workflow? Do you want us to do everything, or to be involved throughout design and implementation?
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One thing interesting about the ‘chiselling’ analogy is it’s reductive not additive. If anything this fits writing with LLMs for brevity and humanising copy. Writing changes from an additive to reductive process, with most effort in the initial brief and edits.
It's interesting to think about how much, if at all, the positive sentiments expressed here are appropriate to mathematicians. His main reason for optimism comes at the end: that now that "chiselling code by hand" is no longer necessary, "we can build amazing things". 1/3
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There’s another reading of ‘chiselling’ which makes it additive: tunnelling through rock is ‘adding’ void/path through removing rock. Maybe this is more what DHH had in mind?
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