Congrats on launch! As the agent cli’s and sdk’s were built for local use, there’s a ton of this infra work to run these agents in production. Genuinely excited for this space to mature.
I have been building an OSS self-hostable agent infra suite at https://ash-cloud.ai
Yeah with sandbox pre-warming and disk co-location its fast enough to avoid UX cold start penalty.
On write amplification — we persist at the message level, not per SSE chunk. The sandbox's workspace filesystem (claude code's native jsonl files) is the source of truth for resume, and the DB is for queryability, tracing, etc - so fire and forget works fine here.
You can fire them in parallel for simple cases. The issue is when you have multi-agent setups. If context isn't persisted before a sub-agent reads it, you get stale state. Single source of truth matters when agents are reading and writing to the same context.
I like this insight. We kind of always knew that we wanted good docs, but they're demotivating to maintain if people aren't reading them. LLMs by their nature won't be onboarded to the codebase with meetings and conversations, so if we want them to have a proper onboarding then we're forced to be less lazy with our docs, and we get the validation of knowing they're being used.
The bitter lesson strikes again… now for graphics rendering. Nerfs had a ray tracing prior, and Gaussian splats had some raster prior. This just… throws it all away. No priors, no domain knowledge, just data and attention.
This is the way.
It should be possible to call a GPL library in a separate process (surya can batch process from the CLI) and avoid GPL - ocrmypdf does this with ghostscript.
