This is Pele, my new rendering library for diagrams and charts, compatible with the latest Mermaid syntax.
- 100-500× faster than mermaid.js
- 6× smaller bundle
- No dependencies
- Easy to theme
- Responsive to device width
In pursuit of making Obsidian insanely fast and cohesively designed, I always found the Mermaid library to be too big, too slow, and too hard to theme. Pele will be the new renderer in the next version of Obsidian, but you can start using it now.
Pele [ˈpɛlɛ] is named after the goddess of volcanoes and fire. It's open source under the MIT license. Try the playground!
something that keeps bothering me is how some people see slop as something that is happening to them, like they're some kind of helpless bystander powerless to do anything about it
excuse me but you are a software engineer, you literally learned how to make sand think and make computers do your bidding?! and now you can't do anything about it? please
the 2 things you should know to cut through all the noise:
1. you need to give your agent a way to verify its own work (i just posted about this so won't rehash)
2. your codebase is memory
the 2nd is not new either, we have always had lint rules, compilers with good diagnostics and strong type systems, LSPs, etc to help us write better code. there is no difference when agents write the code instead, you just need more of them, and stronger ones.
forget rules and skills. you can add those later.
yes, your codebase is a form of memory to agents! agents love extending what already exists. so every nit and every annoyance you've ever seen, every mistake and bad pattern you observe from agents, needs to turn into a constraint, or the agents will just keep repeating those same mistakes like a virus in your code. then you keep observing and repeating this process until your codebase is locked down enough that even agents with little context can one shot a high quality PR.
an even better direction is to refactor/rewrite your code such that agent anti-patterns become categorically impossible. use type systems to your advantage, use libraries/frameworks that reduce the architectural search space, or heck, create your own framework like we did for grok bot and design high quality primitives and well thought out APIs
Not the most minimalistic About page, design-wise, but at least I can say it's truly mine: the fonts, the colour palette, the aesthetics, all the good and the flaws that came along with it.
I wanted:
- no lock-in to one AI lab
- cloud agents that can’t touch my laptop
- to stay connected to the code, even when I don’t write it by hand
For months I’ve done all my coding in a tool that does exactly that. Today I’m shipping it. It's free. 🧵
This is an extremely good watch.
The things that felt novel/interesting to me:
1. Lock down your agents
Humans tend to like 'sharp knife' abstractions - that are powerful, but you can cut yourself if your use them wrong. Lauren says agents perform much better in extremely locked-down environments. Abstractions are designed so they can't screw up, and lint rules enforce it.
They built a whole internal framework (Dune) to keep the agent on track.
That helps optimise agents that don't have a large context window to work productively in your codebase.
2. Create verification infrastructure
To trust the results of any agent, you either need to sit and watch it OR have it provide evidence of its improvement. This has always made sense to me, but Lauren really pushes it hard here:
- Invest in custom CLI's that let the agent drive the app and measure its performance
- Make the app "factory ready" from the get-go - i.e. deployable to an environment where the agent can mess about with it
3. Feature Maps
Lauren's software factory (what she calls an 'outer loop') often requires the agent to break down vague bug reports from users and to turn those into potential fixes.
To aid that, they built a 'feature map' of all the main features in their application, which describe exactly how the app is supposed to function.
This has become essential for helping the agent navigate the codebase, and figure out quickly how things are supposed to work. It's maintained along with the codebase, and kept in sync via automations.
This is the kind of documentation I usually warn against. It goes stale quickly and can confuse agents if it's not kept up to date.
But Lauren's team are using it as critical navigation infrastructure, and it makes it possible for agents to explore faster and better - even on a large codebase. So it sounds like navigation docs like this are worth it if they enable new behavior.
Banger talk - watch the whole thing on 2x.
Alright, mea culpa on solana:METvsvVRapdj9cFLzq4Tr43xK4tAjQfwX76z3n6mWQL
About a year ago, I was very vocal and critical of the token launch. Some of you probably remember.
I call things out when I disagree, but I also give credit where its due.
And what @MeteoraAG has built since then is exceptional. The staking, revenue sharing and referral system is the best I've seen on chain.
Even if you never touch a liquidity pool, staking solana:METvsvVRapdj9cFLzq4Tr43xK4tAjQfwX76z3n6mWQL gives you a share of 10% of the protocol's revenue. Looking at the past 30 days, I'm seeing roughly 35% annualized yield.
Obviously that fluctuates, but 35% APY backed by actual protocol activity is just insane.
To me, @MeteoraAG is one of the strongest protocols on Solana. Whatever the next meta is, tokens need liquidity and traders generate volume. And guess what? @MeteoraAG is the best place to turn that volume into fees. Period.
But the part I'm most excited about is what happens when you actually use the product and share what you're doing.
I'm already spending time on @MeteoraAG, trying strategies, making mistakes and figuring out what works. Sharing that here helps other people get started, and the referral system rewards me for it.
And not just a little. I've claimed over $5,000 in referrals reward in two months, that's fucking huge!
People discover the product through someone who actually uses it. They get a rebate, I earn referral rewards, and more activity means more revenue for the protocol and its stakers.
It's basically the perfect flywheel.
Hats off to the @MeteoraAG team, and please never stop cooking! 🫡
herdr-projects hit top 15 all-time @herdrdev plugins in 48h - and it just leveled up 🐏
→ talk to one coordinator, any agent
→ parallel threads, each on its own branch
→ live progress % in the herdr sidebar
→ prefix+a: every project in one popup
→ threads clean up after they merge
install: herdr plugin install eliasstravik/herdr-projects
(video oneshotted from my phone with opus 5.5)
The Antigravity SDK now supports local models! 🚀
You can now run models like Gemma 4 with the Antigravity harness on your own local computer at no cost, with full data privacy.
Would love to see local model support come to Antigravity 2.0 and the CLI next 🤞