valzam

Of course, invoking 'there are two kinds of languages: one that people complain about and one that nobody uses', there are two kinds of language designs: one that is perfectly consistent and one that has had contact with the real world.

What experience have people had with Mistral models for cyber research? are they as constrainted as Anthropic models? I use claude day2day but have the need for a model with fewer guardrails to pentest our own APIs.

I realised I linked super cringe docs instead of the actual skill:

https://github.com/mattpocock/skills/blob/main/skills/produc...

I have been using this super simple skill[0] to make Claude ask exhaustive questions about the implementation of larger features. It has been absolutely amazing and felt like a step change in the output quality.

For complex features there can be 10 or more questions but I have a very strong sense of understanding the changes about to be made and Claude is very good at following all the decisions exactly. It's like working with an engineer who is both excellent at soliciting requirements and fast at implementation.

[0]https://github.com/mattpocock/skills/blob/main/docs/producti...

Also Claude Code is very good at writing small scripts/on-off test cases to confirm bugs, so I wouldn't even say the initial premise is correct.

> https://modolap.com

Redirect to a 2k USD stripe payment with no explanation when clicking on the main callout button is a pretty baller move.

The big problem is that raw SQL has pretty bad type inference and linting support in most editors. A query builder can still give you a lot of type safety benefits.

I mean the easiest explanation would be that the model harness doesn't always take the most likely token but does top-k sampling or similar. temperatur just means that probabilities get more and more equalized, boosting the chance that an unlikely token gets picked. but even with temp 0 you could have 0.8 T1, 0.19 T2, ... and sometimes sample T2

> One of the great drawbacks of "Cloud Native Computing" as it now exists is that it's really, really complicated. It is often more complicated than the old, non-cloud, sort of computing. In order to deploy your app outside of Minerva you now need to know something about k8s, or Cloud Formation, or Terraform.

Highly agree with this. I think it's very underappreciated in startups that if you want people to deploy a lot of small services you have to make that really super easy. I always thought that the value of things like Spark is that you can run "things" without having to worry about how they run. K8s is similar but much more complex. AWS Lambda is nice but also comes with a lot of baggage at scale. I always wanted to try something like Dapr, which seems to provide a very opinionated happy path for application development.

OP wanted to set up a nested copmany structure. Instead of Person -> LLC it goes Person -> Limited Partnership --> LLC. The in between company is only for tax-efficiency and has nothing to do with limited liability.

The question is, is that really only due to data center geo? I am always amazed how low latency and high quality Facetime between Europe <-> Australia is. Seems like good engineering can overcome less optimal geographics.

Very unrelated: first time I see someone with the same last name as me in the tech community, it's somewhat odd :)

Async presumably happens in the JS runtime that bun calls into. Just need 1 thread to host that

If this works `git clone me@github.com:me/mine.git release_01 && ln -s release_01 /var/www/me/mine/current` then your Docker builds should also be extremely quick. Where I have seen extremely slow docker builds is with Python services using ML libraries. But those I reallly don't want to be building on the production servers.

"ECS would have worked for 99% of these apps, if they even needed that."

I used to agree with that but is EKS really that much more complicated? Yes you pay for the k8s control plane but you gain tooling that is imho much easier to work with than IaC.

I always feel like I am taking crazy pills when I read these threads. The k8s API and manifests config feels like a create standardardized way to deploy containers. I wouldn't want to run a k8s cluster from scratch but EKS has been pretty straightforward to work with. Being able to use kind locally for testing is amazing and k9s is my new favourite infra monitoring tool.

Even if you just run on 2 nodes with k3s it seems worth it to me for the standardized tooling. Yes, it is not a $5 a month setup but frankly if what you host can be served by a single $5 a month VM I don't particularly care about your insights, they are irrelevant in a work context.

I don't disagree that very numerical tasks like revenue forecasting are not a good fit for LLMs. But neither did a lot of data scientist concerns themselves with such things (compared to business analysts and the like). Software to achieve this has been commoditized.

Do those use cases need LLMs? Probably not. but if good results can be had with a day of prompting (in addition to the stuff mentioned in the article, which you have to do anyway) and a smaller model like Haiku gives good results why would you build a classifer before you have literally millions of customers?

The LLM solution will be much more flexible because prompts can change more easily than training data and input tokens are cheap.

As others have mentioned, one big issue is that every company does these things differently and just because someone texts you a link doesn't mean it's phishing, even though it feels shady. In Australia I have had calls by immigration officers on supressed numbers that wanted PII over the phone without being able to tell me what the purpose of the call is.

The average person self hosts literally nothing, why would it be different for inference? Which benefits severely from economies of scale and efficient 24/7 utlization

Ok but "Business Email" wasn't exactly invented yesterday...

I think people are mainly confused because the AirPod Pros are quite competitively priced compared to other higher end offerings. The Max are so far off the market that it doesn't seem to make any sense and it seems unlikely that apple couldn't make up for lost margins with higher volume. Maybe they just literally can't/don't want to produce many of the Max and price them accordingly.

Uff, COBOL written in Norwegian, talk about a narrow target to hit for hiring :)

I mean it's not like Stripe was founded yesterday. Stripe: 2010 Paypal: 1998

I'd argue that 99% of the "internet gdp" happened after Stripe was founded

I mean I know what it means but how can you corpo speak so hard that it's pretty much unclear what the change even is

We have an airtag in our cargo bike, connected to our ipad (neither my wife nor I have an Iphone). It never actually makes a sound and we can reliably track on the ipad. what gives? I never thought about this.

Except of course rollout will not be atomic anyway and making changes in a single commit might lead Devs to make changes without thinking about backwards compat

Do you have a pixel? On Samsung you cannot share WiFi, Hotspot only works with mobile connections. I learners above that this is possible with pixel phones, makes me want to get one...

Id argue that this isn't so much a fault of the MCP spec but how 95% of AI 'engineers' have no engineering background. MCP is just an OpenAPI spec. It's the same as any other API. If you are exposing sensitive data without any authz/n that's on the developer.

I mean given the computing devices most people use are you suggesting a large majority of the population switches to ethernet adapter's for their tablets and phones?

I assume this is similar to Ray?