Riak was one of the OG k/v stores by [basho](https://en.wikipedia.org/wiki/Basho_Technologies). They were kind of early to the world of distributed k/v stores and flourished quite a lot but ultimately got usurped by the cloud giants.
Readit Newssrinathkrishna commented on Chaos in the Cloudflare Lisbon Office blog.cloudflare.com/chaos... · Posted by u/jgrahamc
I've been to Cloudflare's SF office many times for meetups and even for an interview and their lava lamp wall is one of the coolest stuff I've seen in an office.
So cool to see that they've built something similar in their Portugal office.
Given the fact that multi-modal LLMs are getting so good at OCR these days, is it a shame that we can't do local OCR with high accuracy in the near-term?
srinathkrishna commented on Thank HN: My bootstrapped startup got acquired today · Posted by u/paraschopra
Congrats and inspiring to hear your journey! :)
srinathkrishna commented on I've acquired a new superpower danielwirtz.com/blog/spot... · Posted by u/wirtzdan
Wow! That was amazing!
srinathkrishna commented on Ask HN: How to deal with AI generated sloppy code · Posted by u/ilrwbwrkhv
LLMs are always going to generate output (prose or code) in the same style as the training data. The Java training data corpus is both bloated/Enterprise-y, and mostly written by junior engineers or even students (because there are so many publicly-accessible Java school-project personal GitHub repos.)
If you're working on a Java project, consider prompting the AI to first write a "pseudocode solution" in a more concise/low boilerplate/"highly expressive" language — Ruby, for example — and then asking it to translate its own "pseudocode" into Java.
(Mind you, I'm not sure if you can modify the implicit system prompt used by automatic coding-assistance systems like Cursor. [Can you? Anyone know?] I'm more just thinking about how you'd do this if you were treating a ChatGPT-like chatbot as if it were StackOverflow — which is personally where I find most of the value in LLM-assisted coding.)
Alternately, consider prompting the AI to "act like a senior $lang engineer forced to write in Java for this project, who will attempt to retain their existing opinionated coding style they learned from decades of experience in $lang, in the Java code they write" — where $lang is either, once again, a more expressive language; or, more interestingly, a language with a community that skews away from junior engineers (i.e. a language that is rarely anyone's first programming language) and toward high-quality, well-engineered systems code rather than slop CRUD code. For example, Rust, or Erlang/Elixir.
(Funny enough, this is the exact same mental through-line that would lead a company to wanting to hire people with knowledge of these specific languages.)
> mostly written by junior engineers or even students (because there are so many publicly-accessible Java school-project personal GitHub repos.)
I used to work at a Java shop a few years ago. Hated my time there since a. I was coming from a more pragmatic way of writing software in C and Java and its ecosystem made me pull my hair out and b. came across several very senior engineers who insisted on writing code with factories and builders and obscure design patterns which made no sense to me. They were all straight from praying at the altar of Design Patterns and always found a way to give comments about a future scenario where this would be refactored.
I was fairly convinced that design patterns in OOP languages were conceived by relatively senior folks as a form of gate keeping.
srinathkrishna commented on Almost all new car sales in Norway last month were EVs qz.com/almost-all-new-car... · Posted by u/jayantbhawal
Does Norway allow Chinese car makers into the market? Skoda is popular but I wish the article also mentioned the median value of an EV in Norway.
At least in the US, the cost of acquiring an EV is the major deterrent from what I can see. If you live in a city and you want to just get a cheap EV for under $25k for your typical commute, there's just no option in the US!
srinathkrishna commented on NexDock turns your smartphone into a laptop nexdock.com/... · Posted by u/Bluestein
For the most part, one should also likely get a compatible phone and Samsung phones that support DEX are not cheap!
I have a Pixel and have owned Pixel phones for a while and it's a shame that Google is only just opening up HDMI external display on the Pixel 8!
It's a neat idea but I find it hard to succeed at scale.
I'm glad someone asked this question and one of my often quipped quotes is - if you squint hard, every software project is some kind of a migration. And there are some excellent suggestions by others.
Having led my fair share of migrations in the past and going through one right now, here are my tips.
- Understand your stakeholders and the teams that are impacted. Spend enough time understanding how the system is being used today. Proxying and abstractions are you friend here. Just get as much data as possible.
- Once you get enough data, make sure to crunch and very importantly, have a means to surface this to the users. More often than not, for systems that have organically grown, you'll be surprised that users themselves don't know how they use an API.
- As much as possible, try to move things seamlessly. You can always do some portion of the migration without users knowing it. This can be as simple as introducing a translation layer or even you making code changes for the users to review them.
- If you're working on a timeline here owing to external factors like vendor contracts, cert expiry dates etc., make sure to buffer in at least a quarter (or possibly more). There will be new discoveries along the way.
- There will always be teams/stakeholders who will oppose to you asking them to do this work. I can't stress this enough - make sure to get your leadership on board. If you have a Program Management Office, make them your best friends. For anything that escalates and gets political, you as an engineer are better served to get the job done and an aligned leadership that backs you will help you fight these stragglers.
- Ultimately, love what you're doing. There's a mistaken understanding that migration work is not as sexy as greenfield work. I truly believe greenfield work is manifold simpler than migration. A migration is more like changing the wheels and the engine of a car as its running. There will be a lot of tradeoffs that have to be made and this is where engineering skills come into the picture!
All the best! :)
Your first prompt is testing Claude as an encyclopedia: has it somehow baked into its model weights the exactly correct skeleton for a "Zephyr project skeleton, for Pi Pico with st7789 spi display drivers configured"?
Frequent LLM users will not be surprised to see it fail that.
The way to solve this particular problem is to make a correct example available to it. Don't expect it to just know extremely specific facts like that - instead, treat it as a tool that can act on facts presented to it.
For your second example: treat interactions with LLMs as an ongoing conversation, don't expect them to give you exactly what you want first time. Here the thing to do next is a follow-up prompt where you say "number eight looked like zero, fix that".