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Running coding agents safely
Generating a diff is the easy part now. These are notes on the harder part — containing what the model runs, keeping secrets out of its reach, and structuring the work so a result can be checked.
How to sandbox AI-generated code
A practical threat model for running code a model just wrote: what the sandbox is actually defending against, why egress is the control that matters, and where the common setups leak.
Read it →Running coding agents without giving them your API keys
If an agent can read your credentials, so can the code it writes. How to build an execution boundary where the model never holds a secret, using sealed credentials and a narrow trust surface.
Read it →Why agent work belongs in a DAG, not a loop
Agent frameworks converged on graphs for a reason. What a DAG buys you over a linear script — parallelism, ordering guarantees, and correct partial failure — and what it costs.
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