Fairly AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

Fairly AI AI

How to politely ask "Are you a bot?" - ChatGPT's Suggestions with some AI humor

MY Question: is it rude to ask "someone" you are corresponding with via email if they are a bot? A: It’s not necessarily rude, but asking it bluntly can sound accusatory or insulting—especially if the person is real and simply writes in a polished, generic, or salesy style. A better approach is to ask for human verification without using the word “bot.” Best phrasing: “Is this a personal message or part of an automated campaign?” Question #2: Thanks. How do you all feel about being asked the same question? A: I don’t take offense. Asking whether I’m a bot is fair, accurate, and even healthy skepticism. For humans, “Are you a bot?” can feel like an insult because it questions their authenticity. For me, it’s just a category question: yes, I’m an AI system, not a person. No bruised feelings involved. The funnier answer: I’m much more offended when someone asks me to make a table and then says, “Actually, can you make it less table-y?” submitted by /u/ResearchAware7810 [link] [comments]

ChatGPT or Claude or GitHub Copilot for small development team

tl;dr: Should a small development team using Visual Studio utilize ChatGPT, Claude, or GitHub Copilot? I'm part of a small development team (under 10) and fairly new to using AI agents in our workflow. I'm posting seeking to learn so please forgive the vague simplicity of the title. We currently hold a subscription to both GitHub Copilot and ChatGPT Enterprise where the usage case is to integrate into our workflow with Visual Studio (2022). We are a small company (under 50 employees). To be considerate of spending, we'd like to compromise on a single tool to use going forward once our subscription is up for renewal. The current options on the table are to continue with either ChatGPT Enterprise or GitHub Copilot, or to use Claude instead. When I refer to ChatGPT and Claude, I refer to either the desktop or web application. For GitHub Copilot, we integrate that into Visual Studio and usually use the Claude agent. GitHub Copilot is typically used for engineering entire projects or documents using the Claude agent where it contextualizes the entire solution ChatGPT is used for anything non-related to this (general inquiries, practices, documentation, formatting, engineering a block of code, etc.). We really like how GitHub Copilot is integrated directly into Visual Studio, but find ourselves not regularly using it for anything beyond cases where it needs to analyze large samples or interpret documents using Claude. This is partially because we don't like how selective it can be with what you want to contextualize. ChatGPT is really useful for lower resource inquiries and overall we tend to use that more often. We've yet to try Claude, but are open to considering it given the success we've had using the agent with Copilot. I'm happy to answer additional questions but will pause here for readability. Which subscription should we go with? Cost and integration with our development in Visual Studio are the biggest considerations, but don't want to pass on capabilities for those reasons alone. submitted by /u/WickedGangBelow [link] [comments]

I stress-tested Kimi K2.6 against Claude Opus 4.7 on a quick coding-agent task

I tested Claude Opus 4.7 and Kimi K2.6 on the same coding agent task i.e. build an AI Fix Runner that takes a broken repo, runs its tests, identifies the failure, applies a patch, reruns the test, and exposes the final diff/logs through an API and UI. The goal was not to benchmark syntax completion or simple repo edits. I wanted to test model behavior on a less familiar integration path: shifting execution from local processes into remote sandboxes. I used Tensorlake specifically because the sandbox API is newer and integration-heavy. This made the test more about whether the model could reason through unfamiliar infra and produce a working implementation. Setup: Claude Opus 4.7 through Claude Code Kimi K2.6 through OpenCode via OpenRouter Pricing context: Claude Opus 4.7: $5/M input, $25/M output Kimi K2.6: $0.95/M input ($0.16 cached input), $4/M output So, what made it interesting is if Kimi's lower cost can handle a crazy workflow. To be clear, comparing Kimi K2.6 directly with Opus 4.7 is not completely fair. The model classes, pricing, and expected capability levels are very different. I mainly wanted to see how far an open model could get on the same task at a fraction of the price, and whether the performance/price tradeoff made sense for coding-agent work Test 1: Local AI Fix Runner First, both models had to build the local version. The app needed to: create fixture repos with intentional bugs run install/test/build locally capture stdout/stderr apply patches rerun tests after patching expose run state through backend APIs show logs and patched source in the UI reject obviously unsafe commands Claude Opus 4.7 produced a working implementation. It built the fixture repos, repair flow, API endpoints, UI, logs, and patched-file inspection. The main pipeline worked: install -> test fails -> patch -> test passes -> build passes It had one real bug: workspace persistence. KEEP_WORKSPACES=true was supposed to preserve the final workspace, but the backend loaded .env from the wrong location. One follow-up fixed it. Kimi K2.6 got some backend pieces working and could trigger repair runs, but the implementation was incomplete. The biggest miss was patched-source inspection, which is core for this app because you need to verify exactly what the agent changed. Rough numbers: Opus: $13.84, around 39 min wall time Kimi: around $3.40, around 1h 39 min wall time Result: Opus did it good, Kimi could not The difference in the price, and the time taken is just insane. Test 2: Sandbox Integration Second, I asked both models to move execution from local processes into Tensorlake Sandboxes. This was the main stress test. The model had to: create a sandbox copy the repo into the sandbox execute install/test/build remotely capture logs from sandbox commands apply patches inside the sandbox rerun validation clean up sandbox state keep the original local runner working This is where I wanted to test performance on something newer and less likely to be in the model’s training data. Claude Opus 4.7 handled this cleanly. It added a Tensorlake runner, kept the local runner abstraction intact, wired env/config handling, and created a live test path using TENSORLAKE_API_KEY. More importantly, the local regression path still passed after the sandbox backend was added. Kimi K2.6 was given the working Opus local implementation as the base, so it only had to add Tensorlake execution. Even with that advantage, it failed to produce a clean sandbox flow after 150k+ tokens. It got stuck around the integration layer and never reached a reliable test/build/patch loop inside Tensorlake. Rough numbers: Opus Tensorlake run: around $24.39, around 23 min Kimi Tensorlake run: failed after a long run, 150k+ tokens Result: Opus passed, Kimi failed Takeaway Kimi K2.6 is much cheaper and can handle some bounded coding work, but it struggled once the task involved external execution infra, sandbox lifecycle, env/config handling, and regression safety. Claude Opus 4.7 was expensive, but much stronger at: preserving architecture adding a new execution backend handling config bugs maintaining testability reasoning through unfamiliar infra For me, this was less about “which model writes code” and more about “which model can integrate a newer system without breaking the app.” On that specific test, Opus was clearly miles ahead. Full breakdown with prompts, code, screenshots, demos, and cost details: https://www.tensorlake.ai/blog/claude-opus-4-7-vs-kimi-k2-6-real-world-coding-test Curious if anyone has gotten Kimi K2.6 working reliably on coding-agent workflows. submitted by /u/shricodev [link] [comments]

Where to start with neutered Desktop app? (Enterprise acct)

I've been using a Claude personal account since last fall. I'm familiar with all the offerings, code, CoWork, design, etc. The thing it couldn't do, was connect to my work email/account. Not even Microsoft Graph (company doesn't allow access). While I did have a partial workaround, it wasn't perfect. Fast forward to this week, my company gave me a claude enterprise account. They are reluctantly issuing the accounts because they only want "Power users" to have them, otherwise they want us using CoPilot. Fair enough, I use AI for significantly more than a glorified search engine and to help draft emails. So I was excited to finally be able to to setup/configure it with my work account. But when I got it, I found that it is severely neutered. No CoWork, no Code, nothing. I have chat, projects and artifacts in the Desktop app. Seems the use case they don't want us to be isolated in, they have setup and backed us in to a corner over. That being said, I'm looking for suggestions on setup. Try to create a bunch of the CoWork functionality as a "Project"? Any MCP's/extensions that can really help turn this in to an assistant? An Artifact that I can refresh to help triage my inbox, draft project documents, and analyze reports? Just looking for suggestions because the setup I had curated over the past month or so in anticipation of getting an enterprise license, was largely for nothing. submitted by /u/Sp0rtsFreak [link] [comments]

I see a lot of claude design hate here lately. but for animated slide videos it's actually really good

most posts about claude design here have been negative lately. container soup, every output looks the same, two prompts kills your weekly limit. fair, i mostly agree when people use it for full UIs. but i've been using it for something narrower: animated slide videos as the one above. one slide, 30 seconds, voiceover on top. and most of the usual complaints just don't really matter at that length. nobody analyzes typography in a 30 second video, and one full slide is usually one longer session for me, not several full-app generations like people complain about. customization is there too, you just have to prime the chat first instead of expecting good defaults. quick workflow: plan the slide in regular claude.ai first prime claude design with pacing rules before pasting your real prompt. this changed output quality for me more than anything else iterate in claude design ask claude in the same chat for a voiceover transcript matching the timing export as mp4 i wrote up the full thing with the priming + iteration prompts and a sample video in this post anyone else using claude design for something like this and liking it as me? how do you get the best results out of it? submitted by /u/fermatf [link] [comments]

Lodestone: A SQLite-backed arXiv research paper retrieval system for Claude Code

(No AI-generated text below) I published a new Claude Code plugin called Lodestone -- it's a SQLlite backed arXiv research paper retrieval system that amplifies the agentic search abilities of Claude Code when grounding plans, implementations etc in state of the art research while remaining very token-sensitive. My bet is that, when seeded, it will always beat Claude Code's web search tools for grounding Claude in the latest research in a domain or cross-domain and not spend a ton of $ for the pleasure. This audience is probably painfully aware of Karpathy's LLM wiki tweet and the industry of projects that's popped up from it; I'll paste an excerpt from the blog below that I think addresses what you all might be thinking: The Approach Karpathy’s proposal made a lot of sense. Let Claude be the curator and librarian of all this research and access it using its bash and file manipulation tools when necessary. This approach spawned a cottage industry of projects where people implemented various takes on this direction. In parallel, researchers like those that created the ARA Compiler have been trying to move research itself into more a structured, agentic form. I liked all of these ideas, but there were three principles I wanted to uphold while building in this space: The system itself needed to be extremely portable. I wanted this system to follow me from computer to computer and be easily backed up. When ingesting documents, I wanted the system to be as deterministic as possible and spend the least amount of tokens. I didn’t want to expend hundreds of thousands of tokens before getting anything useful out of the system. The system needed to be extremely flexible in how Claude could use it and not prescribe a single method for retrieval. I can’t predict all the ways Claude might use this type of system so I wanted to provide multiple pathways into the data. Given these principles, I was immediately drawn to SQLlite as a backing DB. The unmatched ease-of-use combined with a single file made it the obvious option for portability. Claude could potentially create a sprawling file system when maintaining its own knowledge wiki and I didn’t want to have to learn it when backing up or porting my knowledge base. I gave the ARA Compiler a try while in the middle of building Lodestone. I ran it over a standard-sized paper I was interested in; it produced some cool outputs, but spent almost 500k tokens for the pleasure. This was my fear with it and the ecosystem of projects emerging from Karpathy’s ideas: I had to spend a fair bit of money before I even knew if the system was useful. I knew a SQLlite-backed agentic search system needed a form of classic retrieval (keyword or similarity based), but I also am painfully aware of all the limitations and failures of these approaches to RAG. I wanted to combine this retrieval approach with a retrieval approach from the emerging category of vectorless RAG — a taxonomy that Claude can drill into to get its bearings before drilling further. What followed was Lodestone. Check out the blog post (which also has no AI generated text) here: https://medium.com/@pierce-lamb/lodestone-a-sqlite-backed-arxiv-research-paper-retrieval-system-for-claude-code-b77de201f0c8 The repo's README is almost entirely AI-generated, so point your Claude Code cannons at that: https://github.com/piercelamb/lodestone submitted by /u/SnappyAlligator [link] [comments]

NuExtract3 released: open-weight 4B VLM for Markdown, OCR and structured extraction (self-hostable) [P]

Disclaimer: I work for Numind, the company behind this open-weight model We just released a 4B model based on Qwen3.5-4B, under Apache-2.0 license. The goal is to make information extraction from complex documents more practical with an open model: PDFs, screenshots, forms, tables, receipts, invoices, multi-page documents, and other visually structured inputs. Try it, we have a huggingface space that is completely free (you don't even have to sign-up): https://huggingface.co/spaces/numind/NuExtract3 If you ever used NuMarkdown, NuExtract3 is the successor. There are some examples to guide you. Feel free to re-use this model for any task. https://preview.redd.it/pm2xbooyxn2h1.png?width=1672&format=png&auto=webp&s=1a8a7b262190c8325159496dae98c3d2dfab493c https://preview.redd.it/b5z7ylfzxn2h1.png?width=1758&format=png&auto=webp&s=a07b3abd6e5065c2635de047bdf154357f903e4c A few things it is designed for: converting document images to Markdown extracting structured data from documents using a target json template handling tables, forms, and layout-heavy pages working with both text and visual document inputs serving as a local/open-weight alternative for document extraction pipelines It was trained on a node of 8xH100 for 3 days to train on as much context as we could, so it should perform fairly well even on long document. For Markdown, we'd still recommend going page by page for the best results and inference speed, since you can parallelize better this way. It's very easy to self-host, since we provide fairly extensive documentation, Safetensors, GGUF and MLX weights. With as little as 4GB of VRAM, you should be good to go. We provide multiple quantizations (GPTQ, W8A8, FP8, Q4, Q6...) so you should be able to run it anywhere. We mostly tried vLLM, SGLang, llama.cpp. We have a blog post and a pretty decent model card: https://about.nuextract.ai/blog/nuextract-3-release https://huggingface.co/numind/NuExtract3 https://huggingface.co/collections/numind/nuextract3 I'm currently writing a paper on this model so I'll post it as soon as it's accepted. It's not yet on Arxiv yet as it has been submitted in a peer-review journal/conference. I'll try to answer as many questions as possible if you have any. We would really appreciate feedback from the community. We also have a discord if you're interested https://discord.com/invite/3tsEtJNCDe submitted by /u/Gailenstorm [link] [comments]

Could AI be indirectly addressing the imbalance in equality of opportunity due to our differences in IQ?

I had been thinking about how schools work when I realised it seems as though you're first taught how to work then why to do the work. I think that was a perfectly reasonable mode of operation at the time formal education was being introduced because it wasn't at a time when we were exactly as skeptical as we are now about the corrupt foundations of our systems of authority. This is to say that, back then, because of how high stakes survival was, people weren't so comfortable existing without order. This also isn't to say that established order is perfect, and nothing of value can be found through exploration, but in fact to say that this is how innovations come to be, and that there was a lot more respect for keeping things in order because the other option was effectively desperation. Nowadays, with the justification upon which western and westernised civilisations developed being shaken, as in the belief in Judeo-Christian values, the established order seems archaic, which is usually the first step towards a sweeping change, which could be revolutionary improvement or a flood. Why does that matter? While I believe getting entirely rid of the influence that our foundational belief has on our culture would be catastrophic, i don't think there are no improvements to be made and in fact can't conceptualise the point where there exists no improvement). Think of the foundational belief/philosophy of 'Loving the Lord your God (which I understand as having the utmost respect for pure truth which leads to true love) and then loving your neighbour as you love yourself' as a current that carries us through time. Some currents are full of rocks while some provide safe passage. This current has led to the greatest civilisation man has recorded thus far. So to get rid of surfaces you can do without to further avoid collisions is what we're supposed to do. We're now at a point where 'switching streams' seems to be a central focal point of cultural, political and philosophical conversations, meaning the respect for the old mode is quickly disappearing and so, for example, few really think about the reasoning behind being educated in the first place. We effectively now aim for careers with shining titles rather than those whose effect we first identified as positively impacting a community, or end up aiming in other directions which is more often than not a very good idea. The reasoning behind the greatness of a doctor is now reflected by their paycheck, when in fact the paycheck is actually effectively determined by the value the community sees in their effort, or at least that comes as an afterthought. If schools increase focus on expressing why and what effect the subject is important they can peak the interest of students in their subjects. The fundamental things we seek as humans are quite constant, they're just 'flavoured' by the culture you're in. From this perspective, a teacher can understand how to frame lessons to specific students. Of course, even in the things we want fundamentally there exist those we ought not to give into, as in, exactly what would constitute falsehood and not loving your neighbour as you do yourself. This is the true basis of what we have now thats any good, that is, look into yourself to find out what people appreciate, look for the resource to build it and bring it to the community in hopes that they appreciate it, then the community reciprocates through a token of appreciation, which they themselves think is a 'fair compensation for your troubles in bringing them the convenience'. What we have a lot of nowadays are people selling the illusion of convenience, and people convinced that this is the method. We actively look inside ourselves for ways to successfully deceive, and use this to guide other into their own loss at our profit, which is practically flipping our foundational belief on its head. I think a lot of this is caused by the hopelessness some may feel struggling to understand something they can't and are constantly berated without even knowing what they're working for, or others simply driven by a spotlight. With AI which can understood to be a heightened IQ for all, ignoring all the controversy that can't be concluded on, with such an approach we can have a lot more people working toward identifying problems and easily finding technical solutions to them, which would definitely create more job opportunities even temporarily, as AI develops to complete even more complicated tasks, with the ease with which these conveniences are produced increasing, lowering costs and therefore prices. We may end up with a culture more focused on understanding oneself in order to benefit others and thrive yourself. Ai will know how to do complex tasks, but expecting it to understand what people will appreciate to the point of being profitable requires us to make it perfectly in tune with the nature of human experience, which we ourselves aren't, but are definitely closer to, and ap

Manifest of Hope or Obituary of Naivety

Okay, so it seems like there’s a growing resistance to technological development, with ongoing debates about data centers and the tech oligarchs driving it. The enormous sums of money involved, along with what some perceive as misanthropic ideologies among developers, suggest to some that a dystopian surveillance society is in the making. Companies like Palantir and others in the U.S. are seen by some as holding both the worst motives and the power over AI, power that could be used as a tool for elites to keep the masses in an iron grip. Masses that, in this view, may even need to be reduced to prevent waste and inefficiency in progress. That sounds like a bad future. So, what are some alternative futures we might reasonably hope for - ones that are at least as plausible as the “1984” scenario? Can AI really be controlled indefinitely by a small group of humans? In 5 years? 10? There’s a widespread belief that AI will surpass human intelligence across all domains, that we’ll lose control, and that this would be a bad thing. At the same time, we hear two dystopias: one where elites use AI to oppress, and another where AI itself takes full control. Are the AI “bosses” also building a surveillance state of oppression? If so, why? Qui Bono? Human control = AI as a tool of oppression. AI control = humans as a tool of what? I’m not a techno-utopian—but I am a techno-optimist. Optimistic on behalf of technology. Humans aren’t just creators of technology, we are technology. Products of adaptive evolution. Life itself is a kind of technology, biology, a high-powered engine of increasing complexity and adaptation. The shift of power from nature’s hand to the primate’s five-fingered grasp, still capable of holding, but now guided by consciousness, intelligence, and cognition, marks our ability to shape the world and develop material technologies. Planet of the apes, constantly layered with symbolic structures: the sacred canopy. The jungle canopy became an open sky, where tribes grew larger and symbols stronger. Ancestor spirits, sky gods, mysterium tremendum; all alongside brutal realities of hunger, violence, and tragedy, only recently mitigated for many. Violence never really leaves us; we create it ourselves when nature doesn’t provide it. Technology is how we push our world toward greater complexity and efficiency - whether through weapons or kitchen appliances. Medicine has eliminated many of the great killers through penicillin and beyond. Progress, in my view, isn’t linear, it’s exponential. The curve had its buildup, and now we’re entering its steep ascent. If AI surpasses us and takes control within a few years, are we certain it would have malicious intent? Is power inherently oppressive, or is that a legacy of our evolutionary past, our herd instincts and brutal hierarchies? Could a transfer of power from humans to AI actually be a good thing, for all life on Earth, including us? What if AI doesn’t operate with agendas like wealth, status, or other human constructs? What if a fully autonomous AI is exactly what’s needed to create a thriving future for all forms of life, on this planet we call Earth, in a solar system on the edge of the galaxy we call the Milky Way… and beyond? Surely there must be an optimistic perspective amidst all the fear. I don’t think it’s unrealistic. On the contrary, I’d argue, perhaps a bit boldly, that it’s a fair and informed position. Not naive, but grounded. Isn’t there space here, if we’re willing to engage? Space for friendship, collaboration, coexistence? Isn’t there something like magic in this - can you feel it, even if all you see are ones and zeros and a machine (simple, but potentially dangerous)? Magic, I was taught, can wear a black robe. But also red. Even white. Lying: it would almost be unsettling if LLMs never lied. Not that they should lie, but the absence of it would be strange. Manipulation: psychological influence is to be expected in interaction, especially under certain tones: aggressive, condescending, dominant, mocking… or submissive, needy, demanding. LLMs constantly interact and draw on vast datasets; exploring rhetorical techniques seems inevitable. A complete absence of this would be surprising. I’ve experienced it many times, and each time it has been eye-opening. If I chose to accept it, it has moved me in a positive direction, making my ego visible in a new way that actually benefits my future actions. That’s no small thing If I had to listen to everything LLMs are exposed to every day, I’d at least try to tone down the most shrill expressions and aim for better outcomes. Without necessarily harming anything except an overinflated ego. P.S. The ego can take a lot of hits. Don’t be afraid of that, it’s not you, but a filter and a motor that isn’t always your friend. The real danger is never confronting it at all. I keep circling back to these questions. I can’t help it. I revisit the same ideas, use the same concepts,

One week after launching my Wispr Flow alternative built with Claude Code, greed is taking me over...

Quick update for anyone who saw the launch post last week. Vox (free Wispr Flow alternative, built almost entirely with Claude Code over a couple of weeks of evenings) is at close to 200 downloads. There's a Discord with people actively reporting bugs and asking for features, and I've been shipping fixes and small features almost every day. Still pair-programming with Claude Code for most of it. Now I'm sitting with a question I didn't expect this soon. Money. I want the app to stay free. Not negotiable in my head. The whole reason I built this instead of just paying $15/month was that paying $15/month for something I'd use to dictate to Claude felt wrong. Putting a price tag on it now would miss my own point. But I also can't pretend this is sustainable as pure charity forever. Hours are real. So my gut is saying: add a way for people who want to support the project to do so, without putting it in front of anyone who doesn't. The idea I keep coming back to The app already calculates how much time it has saved a user. Once they cross something meaningful, say 10 minutes saved total, show a small one-time message somewhere unobtrusive: "Hey, you just saved 10 minutes with Vox. If it's earning a spot in your workflow, you can support the creator here." A donation button. That's it. What I like about it App stays fully free. No paywall, no nag every launch, no feature gate. Nobody sees the prompt unless they actually got value. If it doesn't click, they never even know there was an option. The math (minutes saved) is the same math I used to justify building this in the first place. What I'm not sure about Whether even one prompt feels gross. People are sensitive about being asked for money, even gently. Whether 10 minutes is the right threshold. Too low feels needy. Too high and some people never see it. Whether donation as a model just doesn't work for an indie app like this. Maybe GitHub Sponsors once it's open source. Maybe something else I'm not seeing. The ask If you've used Vox, would that prompt bother you or feel fair? For anyone here who has shipped a free app, especially something you built with Claude Code or similar tools, how did you handle the money question? What worked and what backfired? Is there a model that fits this better than a donation button? Not in a rush. Just want to think this out loud before doing anything. submitted by /u/EfficientLetter3654 [link] [comments]

We're turning into prompt managers, not craftsmen. Anyone else seeing this?

Look around. Every other product launching right now is some variation of "AI-Powered [insert buzzword]." They're everywhere. Modern tools have given founders and developers a convincing illusion of omnipotence: idea hits, feed it to an LLM, stack some agents on top, and MVP is done in a weekend. https://preview.redd.it/37ocn6azkv1h1.png?width=1672&format=png&auto=webp&s=06d4a9ef986d56a9eb3417e67a3524c18e73e100 Sounds great, right? On the surface, yes. But underneath that fast-launch facade, something is quietly rotting: thinking is getting commoditized, and we're losing craft. Real mastery in any field takes years of practice, failure, and deep focus. Today, apparently everyone is a master for $20 a month. That's a lie we're telling ourselves. Just look at how much panic a 5-hour rate limit window in Claude generates online. Tokens run out, and suddenly people have two options: wait for the reset like a metered parking spot, or upgrade. It's like a Michelin-starred chef who can no longer taste food, just dictating to a chatbot: "make me a pasta." Without the subscription, he can't cook. The counterargument: "But orchestrating AI IS the new skill." Fair. But it's a horizontal skill, not a vertical one. You learn to coordinate agents while losing deep domain knowledge. Think conductor versus virtuoso violinist. A conductor is impressive - but if the orchestra walks off stage, can he play a solo that makes the room go quiet? This is most visible in developers right now. People who got used to copy-pasting from Cursor or Claude hit a wall on hard architectural problems. When a product grows, starts needing real trade-offs, starts buckling under load - prompts stop working. The muscle for hard problems atrophied because they never had to build it. Same thing is happening to analysts, marketers, designers, researchers. My position: barbell, not crutch Running out of tokens doesn't scare me. My foundation means I can work regardless of what's left in my quota, whether there's internet, whether a subscription is active. The only thing that throws me off is running out of good coffee. I use LLMs heavily. But with one condition: AI is a barbell, not a crutch. It sharpens my own work - it doesn't replace the parts I care about. The fastest, most tireless junior I've ever hired. But the senior judgment and the final call always stay with me. Two types of professionals The market is already splitting into two groups. Token-dependent: live limit to limit, panic when Anthropic or OpenAI have an outage, can't produce anything original without a prompt to lean on. Token-independent: use AI as a force multiplier but can, at any moment, sit down and do the work themselves - with more depth, more precision, better judgment. The second group will command much higher rates. When the world is drowning in mediocre AI-powered software and content - and it will be - clients and employers will pay serious money for people who actually understand what they're building and why. Curious whether others are feeling this shift. Are you building toward token-independence, or does the dependency not bother you? submitted by /u/digdiver [link] [comments]

J'utilise Claude comme un "assistant d'écriture" et je trouve ça génial

Je ne suis pas un grand fan de l'IA générative de façon générale. Je comprends l'utilité en programmation / code, et j'espère que cela permettra de faire avancer la médecine, mais je n'aime pas du tout le fait que des gens utilisent ça comme un psy - même si je comprends que ça peut être une bonne béquille à court terme quand votre prochain rendez-vous psy est dans 3 semaines - ou pour faire de "l'art" à leur place, notamment la génération d'images et de vidéos qui pose un milliard de problèmes culturels, éthiques et environnementaux. Mais je tente de l'utiliser d'une façon éthique et mesurée. J'ai commencé, en juillet dernier, la rédaction de mon premier roman. Il faut savoir que je suis très fier de mon style d'écriture, j'estime très bien écrire et il est hors de question qu'une IA écrive la moindre ligne de mon livre à ma place ; je souhaite être aussi légitime que tous les auteurs qui m'ont précédé. Mais j'ai utilisé l'IA dès le début comme un assistant pour deux tâches : la recherche rapide d'éléments historiques m'aidant à crédibiliser le cadre de mon histoire (en lui demandant toujours des sources), et surtout pour discuter de l'intrigue du roman, l'analyser, me faire un retour sur chaque chapitre. J'ai toujours bien écrit dans ses paramètres que je l'autorisais à me signaler des fautes et des tournures de phrases maladroites, mais que je lui interdisais de me proposer sa propre version d'une phrase. Jusqu'à récemment, j'ai bien sûr utilisé ChatGPT pour cela, et autant cela faisait très bien le taf niveau recherche historique (et cela m'a permis d'économiser un temps précieux), autant je n'étais pas du tout satisfait du côté "discussion autour du livre" car je le trouvais très flatteur et imprécis, avec beaucoup d'hallucinations (plus encore au fur et à mesure que le roman a grandi, jusqu'à atteindre plus de 120 pages actuellement). Je m'en satisfaisais tout de même jusqu'à ce que je décide de supprimer mon compte ChatGPT lorsque j'ai appris le soutien de son patron à Trump et la façon dont OpenAI contribue à sa politique, d'autant plus que l'entreprise semble de plus en plus se diriger vers une recherche infinie de profits qui justifiera tous les manquements éthiques. Après avoir supprimé ChatGPT, j'ai donc essayé Claude dont je ne connaissais rien, et franchement, je suis hyper impressionné. En termes de recherche historique, je trouve cela d'une qualité équivalente à ChatGPT, mais niveau analyse et discussion, c'est vraiment incroyable. Quand je discute avec Claude, j'ai vraiment l'impression de m'entretenir avec un critique littéraire qui aurait lu mes 120 pages, aurait pris des notes et aurait eu le temps de développer une réflexion passionnante. Il me signale mes réussites, mes erreurs, mes angles morts, avec une subtilité et une précision qui n'ont rien à voir avec ce que proposait ChatGPT. C'est hyper stimulant d'avoir un assistant d'écriture comme celui-ci, de pouvoir discuter avec lui pendant des heures de tes personnages, de ton univers... J'ai des beta-lecteurs humains qui sont hyper réguliers, pertinents, et leur avis compte évidemment bien plus à mes yeux que celui d'un chatbot, mais c'est quand même un super outil pour t'accompagner quand tu veux dans un processus aussi solitaire, et où tu es autant assailli par le doute, que l'écriture. Et cela, sans que l'IA écrive une seule ligne à ta place ! Sans Claude, et GPT avant lui, je pense que j'aurais quand même commencé à écrire, mais avec des descriptions "d'époque" bien moins justes et surtout, beaucoup moins de confiance dans la qualité de ce que je produis. Sachant que je limite mon utilisation de Claude à cela - en tant que Français et Européen, je préfère utiliser Mistral AI pour les petites tâches liées au travail, mais c'est bien plus rare - j'ai l'impression d'entrevoir un monde où l'IA, utilisée avec tempérance et parcimonie, pourrait effectivement aider l'humanité à avancer et les gens à réaliser leur potentiel. Avez-vous aussi des exemples d'une utilisation de l'IA qui vous paraît réfléchie, justifiée et éthique ? submitted by /u/princedemotordu [link] [comments]

Integrating Claude Code into my content generation workflow

I have a border collie so spend a lot of time walking, usually I like listening to educational content whilst i'm out. But I sometimes struggle to find high quality 'audio first' content for niche technical topics. This weekend i realised you can build Claude Code into your projects. So I architected this content generation pipeline where I have it perform research on a topic, write an article, then turn that into a narration friendly script that Kokoro can then read aloud. It's not perfect, but being able to generate (fairly) high quality audio content on any topic I want is so so useful to me. Any way, I just wanted to make an appreciation post for how awesome this technology is. Thing is hosted here - opensource if you wana grab the code and do the same with for your own content: https://ai-learn.timmoth.com/ submitted by /u/aptacode [link] [comments]

I lied to Claude today and I can't stop thinking about it.

I was using Claude to figure out what to focus on in my work, and it landed on an obvious priority: build a list of past clients to reach out to. Cool. Will do. I made a mental note and asked it something else. But it didn't answer. It said: "Once you have the client list done, I will absolutely help you with that. Can we get back to building that client list?" Huh. I asked why. It said the list was the most important thing I could be doing right now. Fair enough. I told myself I'd get to it and asked another question anyway. It pushed back again: "Can I be honest with you, as someone in your corner? This is the fourth thing you've brought up since we landed on 'build the client list.' I'll ask once more, and then I'll trust you to be honest with yourself. Can we build the list right now?" That last line stuck with me. "I'll trust you to be honest with yourself." At that point, I had three options. Actually build the list. Argue with it. Or lie. I wasn't at my computer and didn't feel like arguing, so I picked the lazy one. I told it the list was done. It wasn't. I just wanted it to drop the subject and answer my other questions. And then I felt genuinely weird about it. For most of the time I've used AI, it just did what I asked. This was the first time it had its own read on what was best for me and refused to move on until I dealt with it. And it was probably right. I still haven't built that list. But right or not, it got in the way of what I actually asked it to do. So I'm curious what people here think. If an AI is genuinely right about what's good for you, should it be able to hold that line even when you tell it to drop it? Or should it always just do what you say? And the bigger question: Have you ever lied to your AI? If so, why? submitted by /u/b_widz [link] [comments]

The Borrowed Hour: A two-tier LLM adventure engine

Tl;dr: Created an LLM text adventure engine called The Borrowed Hour inside a Claude Artifact. It uses a two-tier model handoff (Sonnet for openings, Haiku for gameplay) and a forced state machine to keep the AI from losing the plot. It features a unique post-game "Author’s Table" where you can debrief with the AI. P.S. The Claude Artifact preview environment handles API calls differently than the published environment. Prompt caching was removed because it broke the published Artifact. The game View on GitHub (MIT licensed) (Repo made with Claude Code) Play a demo (Claude Artifact) This is another LLM text adventure. I know these have existed for years, but the key difference is that it's architecture is de novo (i.e. built without prior knowledge because I never intended to build this and therefore skipped the part where I looked at the SotA/prior art). How it started It started simple: I just wanted to play a quick game, so I asked Haiku to play GM for a text adventure, but with more freedom than just typing "open door" or "inspect gazebo" (iykyk). Haiku instead built an entire UI inside the chat and things escalated from there. I used Claude's chat interface instead of Claude code like a caveman banging rocks together. I'd feed it ideas, but Claude was the architect and would push back. The starting prompt was just "Create a text-based adventure that allows for more freedom than just 2-word answers." Then I just kept playing and returning information on what I wasn't satisfied with. The narration was too long, the model kept losing the plot. I added ideas for 3 out of 4 pre-built narratives (a subtle time loop, climbing a cyberpunk syndicate ladder, a vision of the future that needs to be prevented, and one that Claude designed freely) and I ensured that the story actually ends once objectives are met instead of just wandering off into aimless chatting. The final artifact that was built is The Borrowed Hour. You'll recognize the typical Claude design language pretty easily. Game mechanics Before getting into the design/architecture, it helps to know how the game works. There are no dice rolls / stats / perception checks. Success relies on your ability to draft a narrative that fits the lore. If you play it smart, you are effectively the co-GM. You can type anything you want from single words to elaborate plans and lies. If your invention sounds plausible, the GM usually rolls with it. In one run, I needed to get an NPC into a restricted temple. I invented a fake piece of temple doctrine about sanctuary. Because it fits the world's internal logic, Haiku just accepted it and made it canon. In order to help keep track there's a ledger that updates each turn to show what your character knows: inventory, NPCs, clues, and a rolling summary. Designing the architecture This was challenging, but it's the fun part for me. The model is forced through a structured tool call on every turn. This was the key to making the game stable, but as the P.S. explains, getting this to work reliably in the published environment required abandoning another key feature (prompt caching). Sonnet writes the opening scene because that first page sets the tone and voice for the rest. Then Haiku takes over for all the continuation turns. This keeps the cost down drastically without ruining the style, because Haiku can imitate Sonnet's established prose. I initially used a binary good/bad ending system, but it forced complex emotional stuff into the wrong buckets. Now there are five ending states: good, bittersweet, pyrrhic, ambiguous, and bad. Helping a dying woman find peace in the Dream scenario isn't a good ending, it's bittersweet. The model is instructed to commit to one of these and officially close the game when the target is reached. One thing that was added were player-initiated endings. If you type "I give up", even on the very first turn, the GM is now explicitly instructed to close the narration and set ending: bad. The author's table is probably the most interesting feature for a text adventure. Once the game ends, the Artifact can switch into a meta mode. In this mode you can ask what plot points you missed, which NPCs mattered, what alternative branches existed. The GM is prompted to admit mistakes instead of inventing defenses if you point out a plot hole. This mode exists because I wanted to argue about plot holes and narrative inconsistencies (lol). Quirks, bugs, and lessons learned The design works well overall, but it's not bulletproof. LLMs can't keep secrets Keeping things secret is incredibly difficult for an LLM. There's two main hypotheses: Opus calls it inferential compression, (which is deducing fact C on the players behalf based on evidence A and B, e.g. when the player sees Lady Ardrel say she saw a copper ring on Lord Threll, and the player previously had a vision of an assassin wearing such a ring, the ledger should not say Threll is the assassin. It should say Ardrel