How the pieces actually work.
Short, honest write-ups on the parts of Open Swarm worth explaining — the trade-offs, the things that broke, and the design decisions behind them.
How an operations swarm finds root cause
Most "AI SRE" tools hand the model a shell and hope. The operations swarm does the opposite — prep, box-in, orchestrate: it pre-fetches the evidence, hardens the scope, then reasons over a frozen snapshot instead of poking at production.
Read the write-up ->How the trading swarm justifies a trade
A signal is not an order. Walk through how a candidate moves from the research layer, through risk sizing, to a fill that is logged and tied back to the reason it happened — and how the day closes itself out as a video.
Read the write-up ->Isolating tenants with Postgres row-level security
Isolation enforced in application code is isolation you can forget. Why the platform dropped its database superuser, moved to a least-privilege role, and let the database scope every row to its owner.
Read the write-up ->Loading 1,300+ connectors on demand
A bot does not need every API at once. How a shared connector runtime plus a marketplace lets the swarm import a public API spec and turn it into governed tools only when a task calls for it.
Read the write-up ->More posts in progress: the workflow generator, the daily recap video pipeline, and tenant-aware cost accounting.