--- title: "How much I'm paying for AI productivity software (and the future of AI use)" description: "What I was paying for AI tools in September 2024, roughly nine hundred dollars a month, and the harder question underneath it: why it is difficult to spend meaningfully more." published: 2024-09-24 tags: ["Tools and productivity"] importance: 3 docStatus: "finished" cover: "https://jacquesthibodeau.com/content/images/2024/09/Pantheon-Season-1-Trailer-0-54-screenshot.png" coverAlt: "A scene from the animated series Pantheon, seen from above: a man works across three green holographic screens while a girl stands behind his chair watching." audio: "https://pub-4ee2f71bc29541a7a6e8d9694f0a1b21.r2.dev/66f2be7d5c58d327551e44b7/audio.mp3" crosspost: lesswrong: "https://www.lesswrong.com/posts/CYYBW8QCMK722GDpz/how-much-i-m-paying-for-ai-productivity-software-and-the" figures: - src: "https://jacquesthibodeau.com/content/images/2024/09/pantheon-casper-brain.png" alt: "A scene from the animated series Pantheon: a young man holds a glowing blue projection of a brain in front of him while nine adults stand and sit around the table, watching." width: 1200 height: 675 viewer: "lightbox" - src: "https://jacquesthibodeau.com/content/images/2024/09/Pantheon-Season-1-Trailer-1-0-screenshot--1-.png" alt: "Another scene from Pantheon: a man and a child stand in a timber house whose whole volume has filled with green holographic blocks and beams, a huge watching face at the left and a figure leaping past the window behind them." width: 1920 height: 1080 viewer: "lightbox" author: "Jacques Thibodeau" canonical: "https://jacquesthibodeau.com/how-much-im-paying-for-ai-productivity-software/" --- This post is broken down into two parts: 1. Which AI productivity tools am I currently using? 2. Why does it currently feel hard to spend +$1000/month on AI to increase one's productivity drastically? # Which AI productivity tools am I currently using? Let's get right to it. **Here's what I'm currently using and how much I am paying:** - [Devin](https://devin.ai/) ($500/month): Devin is great if you know how and when to use it, but overall still needs a lot of work. It's good at doing things I wouldn't normally do, but I can use Devin to offload labour. I've used it for doing things like creating a test suite for one of my websites, fixing bugs, and implementing some complex React features. I'd say it's worth it for me as someone who 1) is using the experience to learn about AI tools and how to use them well so that I can re-use the principles in my own implementations, and 2) needs a junior web dev to delegate tasks to. - [Superwhisper](https://superwhisper.com/) (or other new Speech-to-Text that leverage LLMs for rewriting) apps. Under $8.49 per month. You can use different STT models (different speed and accuracy for each) and LLM for rewriting the transcript based on a prompt you give the models. You can also have different "modes," meaning that you can have the model take your transcript and write code instructions in a pre-defined format when you are in an IDE, turn a transcript into a report when writing in Google Docs, etc. There is also an [iOS app](https://apps.apple.com/us/app/superwhisper/id6471464415). - [Cursor Pro](https://www.cursor.com/) ($20-30/month). Switch to API credits when the slow responses take too long. (You can try [Zed](https://zed.dev/) (an IDE) too if you want. I've only used it a little bit, but Anthropic apparently uses it and there's an exclusive "fast-edit" feature with the Anthropic models.) - [Claude.ai Pro](https://claude.ai/new) ($20/month). You could consider getting two accounts or a Team account to worry less about hitting the token limit. - One reason I’ll use the chat website itself is that they typically have a better system prompt than I can come up with. It’s common enough that I’ll try to get something working in Cursor and fail, but then I'll try in the chat app and get to the solution faster. I also use extensions that interface with the chat website, like [https://glasp.co/youtube-summary](https://t.co/doODlFaNNy). I like using Artifacts and Projects. I also don't want to overuse my Cursor Pro fast responses when I don't have to. - [Chatgpt.com Pro](https://chatgpt.com/) account ($200/month). I use this to get essentially unlimited use of the o1-Pro model, which I milk for all its worth. I'm passing large prompts into it. I'm confident OpenAI is either losing money on me or close. - [Aider](https://aider.chat/) (~$10/month max in API credits if used with Cursor Pro). AI coding assistant that runs in the terminal. I use this with Cursor and lean on the strengths I feel like they both have. - [Google Colab Pro](https://colab.research.google.com/) subscription ($9.99/month). You could get the Pro+ plan for $49.99/month. - [Google One 2TB AI Premium](https://one.google.com/about/ai-premium/) plan ($20/month). This comes with Gemini chat and other AI features. I also sign up to get the latest features earlier, like Notebook LM and Illuminate. - [v0](https://v0.dev/chat) chat ($20/month). Used for creating Next.js websites quickly. - [jointakeoff.com](https://www.jointakeoff.com/) ($22.99/month) for courses on using AI for development. - I still have [GitHub Copilot](https://github.com/features/copilot) (along with Cursor's Copilot++) because I bought a long-term subscription. - [Grammarly](https://www.grammarly.com/) ($12/month). - [Reader by ElevenLabs](https://elevenlabs.io/text-reader) (Free, for now). Best quality TTS app out there right now. - [Bolt](https://bolt.new/) (~$9/month, though you can get started with the free version): This is a web chat app by [@stackblitz](https://x.com/@stackblitz) that helps you quickly build full-stack web apps. Find it useful because it is highly specific to web dev. I've started to use this to get started quickly on a project and then port over the code to Cursor to build on top of it. **Other things I'm considering paying for:** - [Perplexity AI](https://www.perplexity.ai/) ($20/month). Like Google, but it uses more AI features for the search. I will often find myself using it over Google. The paid version uses a better AI model. - Other AI-focused courses that help me best use AI for productivity (web dev or coding in general). - [Suno AI](https://suno.com/) ($8/month). I might want to make music with it. Apps others may be willing to pay for: - [Warp](https://www.warp.dev/), an LLM-enabled terminal ($20/month). I don't use the free version enough to upgrade to the paid version. **My typical workflow for a new project is something like:** 1. Back and forth with Claude Chat to think through my research project. Include code from relevant high-quality codebases so that Claude has a better idea for what I'm aiming at. Papers too. Iterate a few times until satisfied. 2. Brainstorm an MVP version of the project and ask (Chat) Sonnet to implement as well as it can. 3. Use project plan instructions with initial and create a prompts folder in the cursor repo. The prompt contains .md files for features of the codebase that came out of my interactions with Sonnet. 4. @ the instruction prompt(s) in Cursor's Composer or Aider and have it create the project files and structure based on the refined idea and initial code. Likely use o1-mini for this part. 5. Iterate on the codebase with Sonnet for more precise improvements. Use o1-mini for more complex changes across the codebase. I think spending time to provide good initial direction to your LLM is important and people should spend a bit of time really giving detailed instructions with examples to their LLM. Otherwise, your model will not focus give some generation that has dominated its pre-training. A simple example of this is that if you prompt an LLM to build a website, it will often try to build a dumb html/css/js website unless you specifically say you want a more professional and modern website with details about the tech stack (next.js, supabase, etc). **Total spending** There are definitely ways to optimize my monthly payment to save a bit of cash, but I'm currently paying roughly ~$900. That said, I am also utilizing research credits from Anthropic, which could range from $500 to $2000, depending on the month. In addition, I'm working on an "alignment research assistant" which will leverage LLMs, agents, API calls to various websites, and more. If successful, I could see this project absorbing hundreds of thousands in inference costs. **Why am I am spending more than most?** I am a technical AI alignment researcher who also works on augmenting alignment researchers and eventually automating more alignment research, so I'm biasing myself to overspend on products to make sure I'm aware of the bleeding-edge setup. So, I'm certainly paying more than the average person when it comes to using AI for productivity. However, I can certainly imagine that I'm *still* paying less than I should in terms of AI software. This leads me to consider: "What should I spend considerably more on regarding AI software? Why isn't it easy to know this? If AI will increase productivity as much as I think it will, why hasn't it already?" # How could I spend way more on AI? ![A scene from the animated series Pantheon: a young man holds a glowing blue projection of a brain in front of him while nine adults stand and sit around the table, watching.](https://jacquesthibodeau.com/content/images/2024/09/pantheon-casper-brain.png) As AI becomes increasingly powerful and entrepreneurs/developers figure out how to make better user interfaces and interconnected systems with AI, we'll be getting massive jumps in our ability to leverage AI for boosting productivity. Of course, people already see this with ChatGPT. However, I expect most people will underpay for AI tools. Someone asked [this question](https://www.lesswrong.com/posts/bX7q9NcoGpb5KdZzQ/if-i-wanted-to-spend-way-more-on-ai-what-would-i-spend-it-on): > Suppose I wanted to spend *much* more on intelligence (~$1000/month), what should I spend it on? This is a good question. I don't even know the obvious answer as someone who works in AI and even focuses on how to leverage these tools for safer development of AI. One reason for this is that most people have not given much thought about how to actually use *intelligence* and *automation*. Have you considered what you would do if you had three interns and an assistant? What if you had an intermediate-level software engineer? Here's an insightful comment (slightly rewritten) by Gwern on the question, "**If AI is so powerful, why hasn't it completely changed the world and increased GDP by several points yet?**": > If you're struggling to find tasks for "artificial intelligence too cheap to meter," perhaps the real issue is identifying tasks for intelligence in general. Just because something is immensely useful doesn't mean you can immediately integrate it into your current routines; significant reorganization of your life and workflows may be necessary before any form of intelligence becomes beneficial. > > There's an insightful post on this topic: [The Great Data Integration Schlep](https://www.lesswrong.com/posts/7L8ZwMJkhLXjSa7tD/the-great-data-integration-schlep). Many examples there illustrate that the problem isn't about AI versus employee or contractor; rather, organizations are often structured to resist improvements. Whether it's a data scientist or an AI attempting to access data, if an employee's career depends on that data remaining inaccessible, they may sabotage efforts to change. I refer to this phenomenon as **"automation as a colonization wave"**: transformative technologies like steam power or the internet often take decades to have a massive impact because people are entrenched in local optima and may actively resist integrating the new paradigm. Sometimes, entirely new organizations must be built, and old ones phased out over time. > > We have few **"AI-shaped holes"** of significant value because we've designed systems to mitigate the absence of AI. If there were organizations with natural LLM-shaped gaps that AI could fill to massively boost output, they would have been replaced long ago by ones adapted to human capabilities, since humans were the only option available. This explains why current LLM applications contribute minimally to GDP—they offer marginal improvements like better spellcheck or code generation, but don't usher in a new era of exponential economic growth. > > One approach, if you're finding it hard to spend $1000/month effectively on AI, is to allocate that budget to **natural intelligence** instead—hire a remote worker, assistant, or intern. Such a person is a flexible, multimodal general intelligence capable of tool use and agency. By removing the variable of AI, you can focus on whether there are valuable tasks that an outsourced human could perform, which is analogous to the role an AI might play. **If you can't find meaningful work for a hired human intelligence, it's unsurprising that you're struggling to identify compelling use cases for AI.** > > (If this concept is still unclear, try an experiment: act as your own remote worker. Send yourself emails with tasks, and respond as if you have amnesia, avoiding actions a remote worker couldn't perform, like directly editing files on your computer. Charge yourself an appropriate hourly rate, stopping once you reach a cumulative $1000.) > > If you discover that you can't effectively utilize a hired human intelligence, this sheds light on your difficulties with AI. Conversely, if you do find valuable tasks, you now have a clear set of projects to explore with AI services. Of course, this is beside the fact that we're *still* early, and we need a few more years to really see how powerful these AIs can become. I agree with Sam Altman (CEO of OpenAI) in his [new blog post](https://ia.samaltman.com/): > This may turn out to be the most consequential fact about all of history so far. **It is possible that we will have superintelligence in a few thousand days** (!); it may take longer, but I’m confident we’ll get there. Leveraging AI for productivity presents a massive opportunity in the next few years. In fact, I expect there will be companies that essentially leverage AI automation internally in ways that the rest of the market doesn't (of course, I've considered doing this myself). These companies (like consultancies) will involve human-human interactions instead of interfacing with an AI but will charge a high premium for that interaction. Basically, their customers will compare the price to the rest of the market and find the price reasonable, but the rest of the market is still leveraging way too much human intelligence (HI) in comparison to artificial intelligence. It will take HI companies significantly longer to do the project and will be much more expensive. * * *
Spoiler warning

Light spoiler for the TV show Pantheon ahead.

There's a TV show called [Pantheon](https://www.youtube.com/watch?v=wTgYeETwgKQ), which covers the entire singularity where humans can upload themselves into the cloud. One interesting point in the plot is when one of the uploaded humans is told that they are still being held back by how they work in their human body, and that character has a really difficult time grasping what that means. They simply couldn't imagine acting in the world in any way that they did in their past life. It just wasn't part of their ontology, how they imagined the world. Eventually, through enough effort, they figured out how to use their newly uploaded body in ways that allowed him to achieve an exponential increase in productivity per second. I think we'll experience several of these shifts in the coming decades, and those who can act on them early may benefit greatly. ![Another scene from Pantheon: a man and a child stand in a timber house whose whole volume has filled with green holographic blocks and beams, a huge watching face at the left and a figure leaping past the window behind them.](https://jacquesthibodeau.com/content/images/2024/09/Pantheon-Season-1-Trailer-1-0-screenshot--1-.png) ## Sources Every external link in this piece that has a captured card, with what that page said when it was captured. The quoted lines below are not the author of this piece writing: they are the linked page describing itself, recorded by `bun run link-cards` on the date given, and kept so that a reader still has them if the original moves or goes away. - **Superwhisper — AI Voice to Text for macOS, Windows & iOS** — superwhisper.com Captured 2026-08-28. > AI powered voice to text for macOS, Windows, and iOS. Dictate in any app with offline and cloud speech recognition, 100+ languages, and custom AI modes. - **Superwhisper - AI Dictation App - App Store** — apps.apple.com Captured 2026-08-28. > Download Superwhisper - AI Dictation by SuperUltra, Inc. on the App Store. See screenshots, ratings and reviews, user tips, and more apps like Superwhisper - AI… - **AI Coding Agent for Building Ambitious Software | Cursor** — cursor.com Captured 2026-08-28. > Built to make you extraordinarily productive, agents turn ideas into code. Accelerate development by handing off tasks to Cursor. - **Zed — Your last next editor** — zed.dev Captured 2026-08-28. > Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter. - **Claude** — claude.ai Captured 2026-08-28. > Claude is Anthropic - **YouTube Summary & Summarizer with ChatGPT & Claude | Glasp** — Glasp, t.co Captured 2026-08-28. > Free YouTube video summarizer & transcript generator. Paste any URL or install the Chrome extension to get AI summaries with ChatGPT, Claude, Gemini & Mistral. Trusted by 2M+ users. - **ChatGPT** — chatgpt.com Captured 2026-08-28. > ChatGPT helps you get answers, find inspiration, and be more productive. - **Aider - AI Pair Programming in Your Terminal** — aider.chat Captured 2026-08-28. - **Google Colab** — colab.research.google.com Captured 2026-08-28. - **Google AI plans with cloud storage – Google One** — one.google.com Captured 2026-08-28. > Explore Google AI plans. Access our most advanced AI, generate videos from text and get secure cloud storage. - **v0 by Vercel - Build Full-Stack Web Apps with AI** — v0.dev Captured 2026-08-28. > Your collaborative AI assistant to design, iterate, and scale full-stack applications for the web. - **MagicLearn** — jointakeoff.com Captured 2026-08-28. > Learn the most valuable skillset in the world. Master AI coding with expert-led courses. No experience required. - **GitHub Copilot · Your AI pair programmer** — github.com Captured 2026-08-28. > GitHub Copilot works alongside you directly in your editor, suggesting whole lines or entire functions for you. - **Grammarly: Free AI Writing Assistance** — grammarly.com Captured 2026-08-28. > Grammarly makes AI writing convenient. Work smarter with personalized AI guidance and text generation on any app or website. - **Read Aloud Online — Free AI Text Reader for Books, PDFs & Articles** — elevenlabs.io Captured 2026-08-28. > Listen to books, articles, PDFs, ePubs, and newsletters with ElevenLabs’ Text Reader app. Convert text to lifelike audio with AI voices on iOS and Android. - **Bolt AI builder: Websites, apps & prototypes** — bolt.new Captured 2026-08-28. > Build and scale high-performing websites & apps using your words. Join millions and start building today. - **StackBlitz** — @stackblitz, x.com Captured 2026-08-28. > Creators of http://bolt.new, http://webcontainers.io & more! Follow @boltdotnew for updates - **Perplexity** — perplexity.ai Captured 2026-08-28. > Perplexity is a free AI-powered answer engine that provides accurate, trusted, and real-time answers to any question. - **Suno | AI Music Generator** — suno.com Captured 2026-08-28. > Create stunning original music for free in seconds using our AI generator. Make your own masterpieces, share with friends, and discover music from artists worldwide. - **Warp — The Open Platform for Automating Development** — warp.dev Captured 2026-08-28. > Infrastructure to build, measure, and interact with agents across your SDLC — so you ship more and spend less. - **If I wanted to spend WAY more on AI, what would I spend it on?** — Logan Zoellner, lesswrong.com, 2024-09-15 Captured 2026-08-28. > Supposedly intelligence is some kind of superpower. And they're now selling intelligence for pennies/million tokens. Logically, it seems like I should be spending way more of my income than I currently am on intelligence. But what should I spend it on? For context, I currently spend ~$50/month on AI: * ChatGPT… - **The Great Data Integration Schlep** — sarahconstantin, lesswrong.com, 2024-09-13 Captured 2026-08-28. > Midjourney, “Fourth Industrial Revolution Digital Transformation” This is a little rant I like to give, because it’s something I learned on the job that I’ve never seen written up explicitly. There are a bunch of buzzwords floating around regarding computer technology in an industrial or manufacturing context:… - **The Intelligence Age** — ia.samaltman.com Captured 2026-08-28. > In the next couple of decades, we will be able to do things that would have seemed like magic to our grandparents. - **Pantheon Season 1 Trailer** — Rotten Tomatoes TV, youtube.com Captured 2026-08-28. ## Terms used The author's own definitions for the glossary terms this piece uses. These are his words, not a standard reference. - **API** — Application programming interface: the contract one program uses to call another. - **GDP** — Gross domestic product: the usual single number for the size of an economy. - **IDE** — Integrated development environment: an editor that also knows how to build, run and debug the code in it. - **LLM** — Large language model: a neural network trained on very large amounts of text to predict what comes next. - **MVP** — Minimum viable product: the smallest version of a thing that can be put in front of a user. - **STT** — Speech to text: turning spoken audio into written text. - **TTS** — Text to speech: turning written text into spoken audio, which is what narrates the posts on this site.