AmazingTurtle

Location: Waldbröl, Germany (CET/CEST)

Remote: Yes, preferred; occasional travel possible

Willing to relocate: No

Technologies:

  Frontend & mobile: TypeScript, JavaScript, React, Next.js, React Native, Expo, Angular, RxJS

  Backend & APIs: Node.js, NestJS, Go, Python, Java/Spring Boot, C#, REST/OpenAPI, Prisma, Zod

  Data & messaging: PostgreSQL, MySQL, Redis, Kafka, RabbitMQ, Elasticsearch, OpenSearch, Neo4j

  Cloud & infrastructure: AWS, GCP, Azure, Kubernetes, OpenShift, Docker, Terraform, Ansible, Helm, Kustomize, Go Kubernetes operators

  CI/CD & operations: GitHub Actions, GitLab CI/CD, Azure DevOps, Argo CD, Tekton, Prometheus, Grafana, Loki

  Identity: Keycloak, Zitadel, OIDC, SSO, Entra ID, IAM/PAM

Résumé/CV: https://www.turtledev.net/en/cv

Email: [email protected]

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About me

I'm Felix, a freelance senior product engineer with 8+ years of experience building web applications and running production systems. I'm looking for remote freelance/B2B contracts, especially SaaS development, greenfield products, and modernization projects where I can own delivery from application code through deployment.

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Recent work

- Developed Go-based Kubernetes operators to automate deployment, configuration, and lifecycle management of IAM/PAM components, including Zitadel.

- Migrated a production Magento platform from on-premises hosting to GCP/GKE, including containerization, database replication, observability, and cutover preparation.

- Stabilized enterprise applications on OpenShift, improved CI/CD and GitOps delivery, and integrated Entra ID SSO into TypeScript services.

- Built the ALDI deals frontend from scratch with React, Next.js, and TypeScript, including API integrations and production deployment on Azure Kubernetes.

- Helped customers integrate AI coding tools and development workflows into their repositories.

seems like those subs are asking to become the new stackoverflow of reddit

whats the decode tok/s speed?

Whats the model total param size and will you release the weights? What does harness integration look like? Do you have an harness? Is it good at coding? What about tool calls? Do we have to wait a fixed amount of time for every step it takes?

If you have dyslexia and I know it, that brings it down to 20% of people. Combined with some other data, this is a pretty good factor to narrow it down to "who you are", right?

I tried it out today, was the new one: 1017.

so i did some apples to bananas comparison.

i let 4 different agents review the same dirty code base (200+ files changed, c++, game engine):

- deepseek v4.1 flash via deepseek API: took 20m to find one p1 issue that was relevant and a p2 issue that was irrelevant

- glm 5.3 flash NVFP4 via TP2 DGX Sparks: took 1h 5m to find a p3 documentation issue

- gpt 5.6 sol: took 5m30s for one p1 and one p2 issue. both relevant

- gpt 6.1 sol: took 4m30s for two p1 and one p2 issue. both relevant.

Worth to mention: none of those findings overlapped.

I let deepseek v4.1 flash and gpt 6.1 sol both plan fixes for the summary of the findings. in this particular scenario: gpt 6.1 sol planned to increase a buffer size from 128 to 256 to fit the 191 elements that blew past a test scenario. it included some headroom. deepseek v4.1 flash on the other hand decided to make it exactly 191 to satisfy the test, for example.

The TPS decode on deepseek is impressive. I never had a second / feeling of being left aone and though "damn this thing is working". Despite all my efforts, it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol. Wall clock time. I don't have token counts for comparison. If I were to grade those models from 1-10 (10 = top tier GG), I'd give deepseek a solid 6.5 and 6.1 sol a 7.5-8.0 maybe.

What do I need faster performance for anyway? My existing Apple TV from.. 2019? is still running cool and handles every app without sweating.

yeah the reason why i submitted the EN article and not original spiegel one is because HN isn't a german only platform and i found no english article on this, thought it was important news anyway

> If a story is spam or off-topic, flag it. Don't feed egregious comments by replying; flag them instead. If you flag, please don't also comment that you did.

Interesting, why is this spam or off topic? This is absolutely an AI topic that needs to be discussed. Not off-topic. Moderation? Hello?

Is Robert House involved?

quick reminder: this is a one shot pydantic token guess. if you try to use a model that was trained on reasoning? you're not getting any of the reasoning.

so basically dots is openclaw absorbed into chatgpt?

you can actually leverage 400k and 1M contexts in codex with very little code changes to the harness. note that excess context past the.. 250k or 400k mark (i don't remember) is charged at 2x the price.

regarding the new pro max subscription btw:

it's 500$ for 25x the plus usage, thats pro (max).

this implies that the old 200$ 20x pro (more) is now more like 10x the usage of plus.

they are slashing our subscriptions in half and make it "but we're more efficient!"

"Your scientists were so preoccupied with whether they could, they didn't stop to think if they should"

Had to be a team of circle jerk external advisories that want to become rich by inflating the effort here

Perfect, I will incorporate this as default as well as the commit from the other guy into my own codex fork https://github.com/AmazingTurtle/codex btw. I'm rebasing on 0.156.0 right now

My calculation (that is 3x 20x subscriptions) it will pay off after ~18.5 months, if I were to stop my subscriptions today. I will likely keep at least one though, so it's more like 27.5 months for a payoff. I am not doing it to save money though. I am doing it for security of supply. Constant quality - I know my model isn't getting lobotomized etc. - and open weight models mostly just lack very little behind. I'm sure I will have affordable, fast and efficient sol 5.6 capabilities with open weight models on my sparks within 12-18 months easily.

> Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?

Exactly what I am saying for months now. And it's exactly the reason why I am shifting to open weight models now. Just bought myself a 2x DGX Spark Cluster. Will run Qwen3.8 Flash Next on it, maybe Qwen4 when it comes out.

Not only do I have full control over quantization and inference, but also will I experience a constant level of quality. It won't be frontier. But it will be stable, and that's enough reason for me to switch. Also I will likely save some money on subscriptions.

This is the first time that I hope that china fucks this up

You better bet someone started their agents with a prompt "Make a salesforce clone but with 100% uptime"

thought this link is better / cleaner: https://unwall.app/www.economist.com/science-and-technology/...

Yeah only somtimes it rewrites the whole files and thats the models/developer instructions fault. a good AGENTS.md is all you need, change my mind

still half as cheap as in EU

gpt-6-astra is a bitch, it constantly scope creeps itself with "yet another thing" to give it that darn polished lick. the results are eventually a little bit better but at what cost? let's do the math.

gpt-5.6-sol: 1x base gpt-6-astra 2.5x base in subscription

then gpt-6-astra tends to spawn subagents a lot, often with all kinds of models such as gpt-5.6, 5.3-codex etc., which is neat. it's a good coordinator but even more cost.

and then it tends to run _full test suites_ over an over again (each costs like 15 minutes) just to verify that _one test_ was fixed etc., and does so for as long as until the test is fixed, eventually accumulating 2 hours or so.

yesterday I assigned it a task to rebase my changs in a repo onto the latest upstream changes. while gpt-5.6-sol consistently took like an hour to do so end-to-end, astra ran for more than 6 hours and still wasn't done. it kept finding "one more thing" that was goldplating that I didn't ask for.

I consider myself an advanced industry representative in these things and would also borrow some time for detailed investigation. I'd happily contribute some valuable assets (tacos with cheese dip) into the matter, straight out of my personal drawers.

I use cachyos as my daily driver for a long time now. I play quite a few games. Only league of legends forces me to dual boot into windows every once in a week or so - fuck the anticheat cartel

Yeah that must be it. OpenAI doesn't want to disclose internal reasoning, that's why thats typically encrypted_content in OpenAI codex session ledgers etc.; leveraging responses API preserves reasoning server side all the way till a final answer is made; so that's very impressive and to me the score that matters.