I don't know who made those numbers up, but for me... I can almost certainly guarantuee, I have never been so relaxed before. Doing multiple paid projects simultaneously due to AI, still leaning back, customer's are happy. I can confidently say: if you know how to leverage it properly, you can be both more efficient and relaxed at the same time. I'd also argue, if you use a combination of SOTA models to code and review and put in some own thoughts, too, then code is also GG.

Also, I was wondering, what does 2.5B gallons of water equate to? Here's the answer for curious minds:

> Using EPA’s cited 82 gallons per person per day figure, 2.5B gallons/year equals the annual household water use of about 83,500 people.

I did some further math... If 1bn users world wide leverage AWS services in their daily routine (netflix, whatever, ...), the formula becomes this one:

2.5B gallons/year ÷ 1B users = 2.5 gallons/user/year

> Compared with the EPA-style U.S. household benchmark we used earlier of about 82 gallons/person/day, that would be: > > 0.00685 ÷ 82 ≈ 0.0084%

So the AWS data centers make up roughly an additional 0.01% of daily water usage. Why is this worth a bloomberg article?

nvidias master plan may be making it the new normal to have "only" 400GB/s bandwidth, thus gatekeeping local model usage further behind "more memory but not as fast as the cloud can do it"

For a little complex changes, I always run codex (5.5-high) in planning mode first. I have linked various docs/{ARCHITECTURE,BACKEND-GUIDELINES,NESTJS-DI,..}.md etc. from AGENTS.md so they can quickly discover relevant docs at planning time, only if they are needed. No need to know react specific stuff when it's dealing with a backend problem for example. I typically blindly approve plans made by the agent with a fresh context, because that's as if I had prompted it. Works the best for me.

Using /goal however, it's really just constantly compacting and doing it's thing, of course it gets sloppy. If only there was a state machine that would transform tickets into a Planning Mode Prompt, then use, idk. guardian approvals (somehow a "Product Management Perspective Lens" approving or making changes to the plan) and then letting a less capable or less reasoning agent execute the plan, I think that would work the best.

https://news.ycombinator.com/item?id=45349476

lmao, chuckled

which is basically maxxed out quickly. So there is 2x (the first lever)

Then there is the /fast mode, which they state costs 2x more (for 1.5x speedup)

And then there is the model base price ($2.50 vs $1.75), well yeah thats 42% increase. It is in fact a 5.7x total increase of token cost in fast mode and large context. (Sorry for the confusion, I thought it was 8x because I thought gpt-5.3-codex was $1.25)

1. Fast mode ain't that fast

2. Large context * Fast * Higher Model Base Price = 8x increase over gpt-5.3-codex

3. I burnt 33% of my 5h limit (ChatGPT Business Subscription) with a prompt that took 2 minutes to complete.

At that point I questioned myself: I really should have installed linux for him.

Remote: Yes

Willing to relocate: No

Technologies: Kubernetes, OpenShift, GitOps, Argo CD, Helm, Docker, CI/CD, Azure DevOps, GitLab CI/CD, Terraform, Ansible, Prometheus, Grafana, Observability, PostgreSQL, Neo4j, OIDC, SSO, Entra ID, Cloudflare, AWS, Azure Kubernetes Service (AKS), Google Cloud Platform (GCP), Kafka, Node.js, TypeScript, React, Next.js, Turborepo, Angular, RxJS, JavaScript, Java, Spring Boot, Gradle, C#, PHP, WordPress, Jira, Confluence, JetBrains IDEs, GitHub Copilot, Figma, Linux (Manjaro/Arch)

Résumé/CV: https://turtledev.net/cv

Email: hiring@turtledev.net

---

I'm mostly the devops guy (kubernetes, CI/CD etc) but I also love typescript (backends + react/nextjs). Available March/April 2026 fulltime, 100% remote.