Josh

Josh

@joshsaintjacque.com

Seattle-area Staff Software Engineer working mostly on web applications. I work mostly in Ruby on Rails and React. Interested in AI and LLM discussions. I sometimes write on joshsaintjacque.com.

614 followers2K following484 posts

Pinned

👋 Hi Bluesky! I'm a Staff Software Engineer with a decade of experience building web applications. Love to share and chat about all things programming and webdev.

"If your work does not benefit from current AI tooling, that is a finding, not a failing. Document why, share it with your community of peers[...] An engineer who can explain where AI does not yet help their work is demonstrating the judgement we are asking for."

Had Claude put together a chart of open weight models on the intelligence index that can run on a ~64gb MacBook over the last year. The gap with SOTA is very real but local intelligence good enough to do real work could be on the horizon.

Implementation plans should occur only at the highest levels, and those should be so baked into the architecture of the application that nothing needs to be said up front. The agent will simply follow established patterns.

An engineer should be able to review code written by an LLM on their behalf, and that review should count. If your team was satisfied with a single code reviewer before the singularity it should still be so now. Don't create bottlenecks that don't need to exist.

Software engineering is and always has been a process of discovery. You never know less about the thing you're trying to build then you do right now.

Josh reposted

Overnight I trained a Jev-like model to output probability distributions over a set of 40 emoji, which runs in RAM at ~150ms per query. This was super easy and cost ~$10. It works pretty well on a weak training set, and with a day or two of work I could make this sing.

Josh reposted

It is strange how much LLMs turned out to be able to solve such a wide range of hard problems that would not, instinctively, seem to be problems that a model of human language would be able to solve This is from a Stanford project that let Astra drive a robot in a kitchen tml.stanford.edu/homebody/

Josh reposted

mostly agree with this but I think it's more precise to say "we will review high-level artifacts but the vast majority of what is produced will not be that" newsletter.pragmaticengineer.com/p/the-pulse-... x.com/MarcJBrooker...

conputer dipshit@davidcrespo.bsky.social

rather than spec, code, and lockfile, imagine there are 50 layers to this hierarchy. can you delete layer 50 and reconstruct it based on everything from 1-49? etc. naturally if you delete the whole thing you have nothing. if you delete 2-50 you're going to end up with something quite different. etc

Command & Conquer: Tiberian Dawn

What's your "origin" video game? Most gamers have a lot of favorite games, sure, but there's always one that basically 𝘥𝘦𝘧𝘪𝘯𝘦𝘴 you. I'm talking about the game that flipped that little switch in your brain and made into a life-long gamer. So, which game is 𝙮𝙤𝙪𝙧𝙨?

“Most-likely-text generators” that are discovering new math and can one shot web applications.

hikikomorphism@hikikomorphism.bsky.social

LLMs aren't made of neurology except in the most handwavey sense. They're made of narrative. That's why I started calling them text elementals: they're not human, they're most-likely-text generators we bent into living stories in a prose format centering the characters User and Assistant

When it rains, it pours... OpenAI released Sol and Luna 6, and cut the pricing in half for both. Luna was already a fantastic value.

I was wondering what Sol's position would be with Astra being so capable and Luna being so cheap, and it looks like they're carving out a niche where it's really cheap to work with Sol-level intelligence.

View full thread

Dominates Fable at real world knowledge task at all effort levels. I'll be interested to see if the benchmarks translate to reality when orchestrating long/loosely defined tasks.

Opus/Medium seems like the sweet spot for agentic coding, but it's interesting they didn't plot it against Fable for business workflows. Seems like it struggles more there, though it still performs well.

Watching Jev power computer use/web browsing is wild. It's much faster than current LLMs. If this works I'd use it all the time.

Anthropic models are in a really weird place right now where Sonnet just isn’t cost competitive at any reasoning level with Opus. I can’t figure out when I’m supposed to use this model. Hopefully Anthropic sorts this out soon, because I need something cheaper to run for well defined tasks.

I have somewhat thought here. I wonder if this is something that your orchestrating agent would invoke rather than you directly. 

mr. TIM@timkellogg.me

i feel like it’s a mistake to overlook this model, although i’m having trouble figuring out where it fits in my workflow wild new architecture, totally different approach my hunch is the main agent can use it as a tool. So you could use this with Luna to get Astra perf, idk

Josh reposted

Jev: Fable-level model that doesn’t charge for output tokens because they’re too cheap to meter it’s not general though, it only makes decisions, doesn’t generate text, but input tokens are measured by the billion ($42/btok) typesafe.ai/blog/introdu...

Good luck building out multiple redundancy, offsite backups.

Thomas Long@rayosunlong.bsky.social

The more shit you store in the cloud, the more data centers they will build. Get an external hard drive and secure your own data. Stop paying them to destroy the country. How many cat videos do you need?

Microsoft peaked with Windows 98 SE.

Josh@joshsaintjacque.com

Every time I log into Minecraft I'm reminded how much I hate Microsoft. How you can mess up auth this bad in a application nearly two decades old is truly an accomplishment.

Every time I log into Minecraft I'm reminded how much I hate Microsoft. How you can mess up auth this bad in a application nearly two decades old is truly an accomplishment.

Does a non-apple laptop exist that's competitive with MacBooks in battery life, build quality, and noise? Between that and unified memory I haven't found any good options.

Josh reposted

In 2027, mysterious hacks attributed to open source weights and definitely not connected to the companies that accidentally hacked a bunch of companies in 2026, which was okay

Quantian@quantian.bsky.social

lol two months ago OpenAI was signing a letter about how important open weights models were and now their house propagandist is saying “we will ban open weights and you will thank us for it”. You can’t hate this company enough

Hot take but most of the human-authored production code I've encountered in my career was significantly worse than what any of the frontier models produce today, and we thought that code was perfectly fine.

"If we execute these measures well, I believe they would slow China’s progress enough to widen America’s lead significantly over the next 3–5 years — the window when AI becomes geopolitically most important." So 3-5 years is the real horizon for AGI/ASI.

Josh@joshsaintjacque.com

Looks like Anthropic, OpenAI, and xAI have all agreed to "pace" frontier models. The steps proposed by Amodei look like a nuclear arms limitations treaty, complete with third party inspectors.

Mostly good takes although I disagree with the idea that the death of middle management means the death of career development. One of the biggest mistakes our industry made was making management the default upward path for software engineers. 

Gergely Orosz@gergely.pragmaticengineer.com

A couple of trends I'm seeing across the industry. Which ones are you observing that I missed?

Josh reposted

Independent of policy debates about existential risk, it is worth noting that even if AI development stopped today with the models we have right now, we would still have at least a decade of roiling change throughout much of work, education, and social life as harnesses improve & AI diffuses further

I've been rethinking the trade offs of typed/compiled languages vs. dynamic/interpreted ones. LLMs have significantly reduced the costs while offering additional benefits as software grows in complexity faster.

I had an idea for a project I wanted to do and Astra actually talked me out of it. Using it feels like it knows what I'm trying to get at and can help me down the right path, even if it's a different path than what I initially envisioned.