How many Kubernetes administration headaches trace back to the need for automated systems to surgically edit YAML? It’s absurd and YAML may be the worst choice for this use case.
If you are paying API rates (not using Max subscriptions) there's no reason to use Anthropic's API directly, the same models are hosted by both AWS and Google with better uptime than Anthropic.
You may want to optimize the content serving a bit, since it's currently hotlinking multiple large (30MB) videos at 2K resolution from https://svs.gsfc.nasa.gov.
Sonnet/Claude Code may technically be "smarter", but Qwen3-Coder on Cerebras is often more productive for me because it's just so incredibly fast. Even if it takes more LLM calls to complete a task, those calls are all happening in a fraction of the time.
SlateDB offers different durability levels for writes. By default writes are buffered locally and flushed to S3 when the buffer is full or the client invokes flush().
While your technical analysis is excellent, making judgements about workload suitability based on a Preview release is premature. Preview services have historically had significantly lower performance quotas than GA releases. Lambda for example was limited to 50 concurrent executions during Preview, raised to 100 at GA, and now the default limit is 1,000.
Grok are the first models I am boycotting on purely environmental grounds. They built their datacenter without sufficient local power supply and have been illegally powering it with unpermitted gas turbine generators until that capacity gets built, to the significant detriment of the local population.
Reading about mainframes feels very much like reading science fiction. Truly awesome technology that exists on a completely different plane of computing than anything else.
This thinly veiled advertisement claims it's a waste of time to understand the tradeoffs in the models you're using, and you should instead pay them to make those decisions for you. No thank you.
Per the ongoing Freedesktop discussion, AWS offered to host but Freedesktop is leaning towards self-hosting on Hetzner so they can control their own destiny and sponsors can contribute cash towards the bill instead of donating hardware.
Because they own the CDN and most of the bandwidth is from peering, so it essentially costs them nothing.
Netlify on the other hand has to pay per GB to AWS.
Both these issues can be resolved by adding some sample code to context to influence the LLM to do the desired thing.
As the op says, LLMs are going to be biased towards doing the "average" thing based on their training data. There's more old backend code on the internet than new backend code, and Tailwind is pretty dominant for frontend styling these days, so that's where the average lands.
Counterpoint: I also used to fix Lexmark printers as a field tech servicing pharmacies. It was routine to see Lexmark MS711dn printers with page counts in the millions. They did not need more than basic maintenance.
How many Kubernetes administration headaches trace back to the need for automated systems to surgically edit YAML? It’s absurd and YAML may be the worst choice for this use case.