Crossposted from the AI Alignment Forum. May contain more technical jargon than usual.

OpenAI is currently charging 100,000 times less per line of code than professional US devs.[1]

An LLM's code output is of course less reliable than a professional's. And it is hard to use a text-completion API effectively in large projects.

What should you do if you've got a model on your hands that solves those problems?

You could operate as a software development company. They tend[2] to charge $100-200k for simple mobile apps and there's basically no ceiling on the cost for complex apps over their lifetime. Devs make up the majority of a normal firm's personnel and costs; coding takes most of the app development time; bugs in code are one of the primary sources of project extension and failures. By using your model you can make better software, complete it faster, succeed more often, charge a lower price, and make a higher profit.

Going further, if you've really got a good model, then you can do very well by building competitors to adobe products, salesforce products, SAP products, google search, mongodb, etc.

Someone who has a build-anything machine would be a fool to sell a cheap build-anything service instead of using it themselves and selling the result. Particularly because selling the general service directly is likely to encourage and inspire copycats, including open-source ones who will delete your market. If it really builds the entire thing then you'll probably also be liable for negative consequences, which again have no ceiling.

Fewer risks, big and small

Some common misuse risks you can avoid/reduce (and eliminate associated liability):

  • Someone tricks your API into doing something awful and pastes it into a tweet
  • Spam generation for political campaigns, cryptocurrencies, etc
  • Common hacking ("write a test to see if my server has a log4j vulnerability")
  • Targeted manipulation and spearphishing

Larger risks you can avoid/reduce:

  • Your incredible model motivates countless AI researchers. People reverse-engineer some of the architecture in online discussions. The state of the art is quickly advanced. We have less time to prepare for strong general AI.
  • Hackers steal your model weights (if you don't advertise your model then you'll attract less attention from hackers)
  • People try to get your model to act like an agent and copy itself around. They succeed. You have no way of shutting it down or monitoring what it is doing.
  • Someone tries to get your model to order and mail smallpox or a novel virus. The screenshot would be an epic tweet. They succeed oh no
  • Your own AI devs' ambitions and risk-tolerance know no bounds because you've positioned yourself as an AI company instead of a product company; there is nothing to keep their hands busy except make the AI more generally capable and efficient. They are careless with the training runs and one day your model gets loose and wreaks havoc.

Biology, robotics, R&D, etc

The benefits of selling/publishing derived products and the downsides of offering direct access remain in other domains:

  • A drug is more profitable and less risky (for the world at least) than a general drug designer
  • A vaccine is more profitable and less risky than a general mRNA designer
  • There's more people who want to buy a house than a house-building robot
  • There's more people who need a (highly efficient, AI assisted) lawyer than a general lawyer's assistant.
  • More people need a cleaning robot than a robot-maker
  • Releasing or building an effective fusion power generator gets you more clout than releasing the design assistant
  • Even if you're evil and want to make AI-astroturf campaign spam, you presumably want to help one side more than the other, but if you release your model/tooling then both sides will use it.
  • If you have a mathomatic it would be pretty epic to slowly release proofs for millennium problems for a while before revealing it was the mathomatic all along.
  • Would be epic to release your unified theory of physics and wait a bit to reveal it was the physicsomatic all along.
  • A factory optimization consultancy / management company would make more money than a factory optimization software package.
  • There's more customers for long-lived dogs than a live-long-gene-editor. More customers for a livelong injection than the injection designer.
  • If your hackomatic can edit Chase balances without a trace then you should just edit your own, not sell it


Whether you're a startup, a big commercial lab, an enormous company, a research lab in a university, an independent AI researcher, or a criminal — whatever domain you're working in — whatever your goals — if you possess a uniquely powerful model then you'll likely have greater rewards and fewer risks by putting its products into the world instead of the model itself.

  1. A particularly speedy software dev might type 400 lines of working code in 8 hours. If they cost $100/hour that's $2/line. GPT3.5-turbo costs $0.002 per 1000 tokens, and 40 characters/line ≈ 10 tokens/line = $0.00002 / line. ↩︎

  2. "The actual costs are much higher with a median total app development cost of $171,450." And the GoodFirms article they quote actually has numbers 3x higher than quoted, in the 100-200k range. ↩︎

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3 comments, sorted by Click to highlight new comments since: Today at 5:47 PM

I agree with the main thesis "sell the service instead of the model access" , but just wanted to point out that the Upworks page you link to says:

GoodFirms places a basic app between $40,000 to $60,000, a medium complexity app between $61,000 to $69,000, and a feature-rich app between $70,000 to $100,000.

Which is significantly lower than the $100-200k you quote for a simple app.

Personally I think even $40k sounds way to expensive for a what I consider a basic app.

On another note, I think your suggestion of building products and selling to many clients is far better than developing something for a single client. Compare developing one app for 40k and sell to one company, with developing one product that you can sell for 40k to a large number of companies.


Added footnote clarifying link (goodfirms seems misquoted and also kind of looks fake?)

I mentioned the software development firm as an intermediate step to products because it's less risky / easier than making a successful product. Even easier would just be to hire devs, give them your model, put them on upwork, and split the profits.

I suppose the ideal commercialization plan depends on how the model works and the size of the firm commercializing it. (And for govts and universities "commercialization" is completely different.)

Thanks for the clarifications, that makes sense.

I agree it might be easier to start as a software development company, and then you might develop something for a client that you can replicate and sell to other.

Just anecdotal evidence, I use ChatGPT when I code, the speedup in my case is very modest (less than 10%), but I expect future models to be more useful for coding.