rongenre

I applaud Kimi and the open weight models - for the simple reason that they provide a price ceiling for AI.

I've found minimax to be quite good

Location: SF Bay Area (commutable from Berkeley) Remote: Yes Willing to relocate: No, but I'll travel Technologies: Java, Python, Relational Databases, Microservices, Queues, Temporal, LLM orchestration packages Resume/Email: Check profile

I'm an experienced individual contributor who's done a lot of work building and scaling distributed backend systems in a bunch of different industries. I've worked for both startups and large enterprises.

  @book{Kuhn1962,
    author    = {Kuhn, Thomas S.},
    title     = {The Structure of Scientific Revolutions},
    publisher = {University of Chicago Press},
    year      = {1962},
    address   = {Chicago},
    note      = {Often cited with various editions, e.g., 50th ed. 2012},
    keywords  = {paradigm shift, normal science, scientific revolutions}
  }

I was screwing around with gemini-cli and vibe-coded (or vibe-engineered?) a git extension to turn commit history into a pandas dataframe.

Curious if anyone would find this useful: https://github.com/rbagchi/git-dataframe-tools

Sharpe ratio is just the start: it gives you a metric on your portfolio. If it gave an interpretation of what that means, or give guidance on how certain actions would adjust the Sharpe, that might add a lot more value.

https://en.wikipedia.org/wiki/Productivity_paradox

If AI is roughly where IT is in the 60's, we might see actually decreased productivity for a while until people (yes people) figure out how to use it effectively.

I love SICP, but in industrial software I'd point to "The Mythical Man Month".

There's a couple uses cases (beyond the obvious) that I like with the chatbots

1. Brainstorming building something. Tell it what you're working on, add a paragraph or two of how you might build it, and ask it to give you pros and cons and ways to improve. Especially if it's mostly a well-trod design it can be helpful.

2. Treating it like a coach - tell it what you've done and need to get done, include any feedback you've had, and ask it for suggestions. This particularly helps when you're some kind of neurospicy and "regular human" responses sort of escape you.

Fundamentally a dev owns the code they write - it doesn't matter if it's copy/pasted from search results or filled in via an LLM.

The future is here, it's just not evenly distributed..

I'm on a 6 year old XS. When I upgrade, I get 5G and USB-C, and a chip that's now ahead of the OS.

I had a GSD who remembered everyone who threw a tennis ball for her. To the point that I had to warn people that if they tossed it once, she'd be dropping a tennis ball in their laps for the foreseeable future.

I miss that girl.

There needs to be a pattern for including AI-generated code, recording all the context which led to the generation.

EVs are the clear choice if you've got an ICE car as a backup.

I mostly do commuting, grocery runs, etc. EVs are great for that. But then I do road trips about once a year, and an EV just adds to the complexity of planning currently.

I'm sort of dreading the next year or so at big corps, in which engineers will hear from their management: "We've made a big investment in AI, and need you to make this work".

I had an A1000 - even worked in high school at a Commodore/Amiga dealer.

What they really didn't understand is that software sells hardware: The OS was so far ahead, but in terms of basic productivity software? Even the Mac was ahead.

And [IMO] markets can maintain a leader and one strong competitor. But just one. So it became PC/Mac throughout the 90's on the desktop.

The awesome cube, which apparently didn't look good when faxed...

I played with SGI machines in college and they felt like.. the future. I really hoped they would hire me when I graduated.

Incredible, though, how the relatively cheaper Windows NT machines and 3dfx cards and graphics software just killed them. I was a little sad when I wandered around the campus of an employer in Mountain View and noticed the fading sign that had what was left of the SGI logo.

Location: San Francisco / Berkeley / Oakland

Remote: Yes, will travel within 30-45 minutes

Willing to relocate: No

Technologies: Python, Java, Spring Boot, Relational Databases, Kubernetes, public clouds

Résumé/CV: ask me

Email: in my profile

Mostly a backend developer, but I've done full stack before and I'm open to doing more of that. I also have a strong interest in AI and LLM (like everyone else here)

We use this at my ginormous employer in order to give devs limited access to production data.

PDF of GEB: https://archive.org/details/GEBen_201404

Jason Lemkin's advice for startup SaaS businesses is to heavily invest in customer success: you need to give a shit. Otherwise your customer churn numbers are going to be high, and it makes failure increasingly likely.

When I was being courted by a startup for an IC position, the best question I asked was "What does your churn look like?". It was really low, and despite some other reservations I ended up taking the job, and we had an awesome exit. Because our customers really loved us, and we worked hard to make them successful.

Wiki link: https://en.wikipedia.org/wiki/Club_of_Rome

This makes me think of my experiences in Europe.

In my native language (English), I can twist and weasel with the language to keep from committing to... anything. It has -- too many degrees of freedom available to me.

With German, though [where I'm intermediate], I don't have that flexibility. My conversations are really straightforward and what comes out is simple enough that I can express it. I'd say that this does come at the cost of understanding and expressing nuance and condition, but maybe that's actually helpful.

https://archive.ph/hfNgR

I've had a huge amount of success using sqlite to collect and analyze logs. The obvious approach would have been to dump enormous csv or json files, but doing in sqllite gave me (a) much better reliability, and (b) the ability to come up with post-hoc analysis approaches without changing the main process.

I was really pleased to add it to my toolkit.

I'll tip for an espresso beverage, because there's skill involved in making a nice cappuccino - at a minimum you need to be sure to foam the milk without boiling it.

There was a place (in Berkeley of course) where I was pretty sure that if the barista didn't like your tip, they'd boil the milk for you.

Mine was with Wells Fargo - trying to get automated withdrawals from Apple Savings to Wells.

I decided to try again today, we'll see.

It's a very strange account - I tried to set up my auto loan to withdraw from Apple Savings, but it just didn't work.

When I deposit money from my bank, it takes a full week for it to be available for withdrawal.

Oddly, I have my employer put $20 into it every pay period (honestly on a lark), and it showed up on the expected date, and was available for withdrawal.