all the companies selling you a software factory produce a shockingly tiny amount of software
@WishWithWe the tps is slower, and this is a function of how much hardware we have. this will improve as we get more capacity
with current token prices i wouldn't really say "cost of software is going to zero"
our token cost is double our payroll which means even though we're 25 it's like we're 75
and i feel like our output is similar to a team of 75 pre-ai. we're just able to do it without all the downsides of a larger team
this is still a good thing. we couldn't hire 50 more people. so much overhead and impossible to retain a high bar
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our team uses gemini quite a bit now
whenever we have a tricky architectural problem, complex system design questions, or need to simplify something we ask for a gemini subagent
it's pretty good here. i don't see this talked about much
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here are our teams commits since january
something is happening
this is one of those moments that makes you wonder what kind of information you've been ingesting from areas you aren't familiar with
“Is this just a big circle jerk?” Jon welcomes Ed Zitron (@edzitron), host of the podcast Better Offline, to make sense of the financial house of cards propping up AI and big tech. New pod out now!
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if you report an issue well it will get fixed and in your hands incredibly quickly
hokum, notifications for wayland
- theme it however you want
- nice springy animations
- control notifs per app
i have bad news
seeing early signs than LLMs can be funny
you just have to give them a weird medium that isn't just text
we have an internal alternative to slack huddles with higher quality video, audio, screenshare
we will release it publicly but some weird ux issues to fix first...
we have cloudflare enterprise now
which means we're paying for all your cheap worker deployments on all your side projects
you're welcome
lot of people making stuff up so here's some more context
you can imagine there's hidden enterprise demand for open source models that isn't visible
but if you look at the top inference providers that aggressively go after this business, they have shared some numbers and they are all roughly the same size as us. and at best there's 5 of them
if you think enterprises are self hosting inference on their own GPUs, there are so few people who can run reliable inference and they get paid a lot and work at ai labs. and if they really want sovereignty they're not getting that by leasing GPUs from a third party
the root point here is this is entirely the wrong way to look at things, you just have to look at products
how many products exist with a lot of traction that can use open models? this is what creates demand, it's not some magic thing that grows on its own
OpenCode is one of those and we do see a lot of enterprise inbound. but it's so early, all of these companies are just starting to look at mixing in some OSS inference
so yes demand will probably go up in the future but everyone in this industry is investing resources in preparing for that future. and so few people are building the products that will make it happen
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with supply chain attacks becoming a bigger problem AUR really has to become more sophisticated or get replaced
it's impossible to securely publish packages there
there's few people betting on opensource models more than us
but it's important to be realistic about where they are and the demand for them
there's a big gap still. they are fulfilling an interesting spot in the market but too many people are acting like they're on the verge of killing frontier
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Open weights models fall further behind in v5. The leader, Kimi K3.1 Pro (weights not yet released), scores 46, 12 points behind the leader, compared with a 3-point gap in v4.3. Of models with released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) score highest at 32, and Claude Haiku 5.5 (max) outscores all of them.
The gap is widest on HLE-Diamond and Terminal-Bench-Science, where Kimi K3.1 Pro scores 37% and 34%, compared with 68% for Claude Opus 5.5 (max) and 63% for GPT-6 Astra (max).
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something useful to remember esp in times of change like this is when people make predictions they are not making predictions
they are praying
it's getting close to 2 years of coding agents being a thing
looking back on that time the majority of discussion on here on where they're going, what's cutting edge, what matters has been primarily wrong
you had to actively ignore what was going on here to win in this space
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OpenCode 2.0 now has 1M daily active users
that happened in 2 weeks
go upgrade everyone is having fun without you
our team has been using this for months now and it's probably why no personal assistant agent product has stuck for us
