That's a fair point and yet I deeply believe Codex is better here. After finishing a big task, I used two fresh instances of Claude and Codex to review it. Codex finds more issues in ~9 out of 10 cases.

While I prefer the way Claude speaks and writes code, there is no doubt that whatever Codex does is more thorough.

My (admittedly one person's anecdotal) experience has been that when I ask Codex and Claude to make a plan/fix and then ask them both to review it, they both agree that Codex's version is better quality. This is on a 140K LOC codebase with an unreasonable amount of time spent on rules (lint, format, commit, etc), on specifying coding patterns, on documenting per workspace README.md, etc.

Every time Claude Code finishes a task, I plan a full review of its own task with a very detailed plan and it catches itself many things it didn’t see before. It works well and it’s part of the process of refinement. We all know it’s almost never 100% hit of the first try on big chunks of code generated.

Agreed. The $20 plans can go very far when you're using the coding agent as an additional tool in your development flow, not just trying to hammer it with prompts until you get output that works.

Managing context goes a long way, too. I clear context for every new task and keep the local context files up to date with key info to get the LLM on target quickly

> Inference is almost certainly very profitable.

It almost certainly is not. Until we know what the useful life of NVIDIA GPUs are, then it's impossible to determine whether this is profitable or not.

Is there a possible future where the inference usage increases because there will be many many more customers and R&D grows Lower than inference?

Or is it already saturated?

>> "In my mind, they're hardly making any money compared to how much they're spending"

> everyone seems to assume this, but its not like its a company run by dummies, or has dummy investors.

It has nothing to do with their management or investors being "dummies" but the numbers are the numbers.

OpenAI has data center rental costs approaching $620 billion, which is expected to rise to $1.4 trillion by 2033.

Annualized revenue is expected to be "only" $20 billion this year.

$1.4 trillion is 70x current revenue.

So unless they execute their strategy perfectly, hit all of their projections and hoping that neither the stock market or economy collapses, making a profit in the foreseeable future is highly unlikely.

[1]: "OpenAI's AI money pit looks much deeper than we thought. Here's my opinion on why this matters" - https://diginomica.com/openais-ai-money-pit-much-deeper-we-t...

To me it seems that they're banking on it becoming indispensable. Right now I could go back to pre-AI and be a little disappointed but otherwise fine. I figure all of these AI companies are in a race to make themselves part of everyone's core workflow in life, like clothing or a smart phone, such that we don't have much of a choice as to whether we use it or not - it just IS.

That's what the investors are chasing, in my opinion.

> They are obviously making awful lot of revenue.

It's not hard to sell $10 worth of products if you spend $20. profit is more important than revenue.

Revenue != profit.

They are drowning in debt and go into more and more ridiculous schemes to raise/get more money.

--- start quote ---

OpenAI has made $1.4 trillion in commitments to procure the energy and computing power it needs to fuel its operations in the future. But it has previously disclosed that it expects to make only $20 billion in revenues this year. And a recent analysis by HSBC concluded that even if the company is making more than $200 billion by 2030, it will still need to find a further $207 billion in funding to stay in business.

https://finance.yahoo.com/news/openai-partners-carrying-96-b...

--- end quote ---

I think it's difficult to estimate how profitable both are - depends too much on usage and that varies so much.

I think it is widely accepted that Anthropic is doing very well in enterprise adoption of Claude Code.

In most of those cases that is paid via API key not by subscription so the business model works differently - it doesn't rely on low usage users subsidizing high usage users.

OTOH OpenAI is way ahead on consumer usage - which also includes Codex even if most consumers don't use it.

I don't think it matters - just make use of the best model at the best price. At the moment Codex 5.2 seems best at the mid-price range, while Opus seems slightly stronger than Codex Max (but too expensive to use for many things).

Ive had the same but i only use it through zed so I wasnt sure if it was a codex issue or a zed issue