How _safety nets_ fit into Compound Engineering In this channel's material on Compound Engineering, safety nets describe the practices that make it possible to adopt AI-native workflows at the right level of trust for your own work. Rather than handing work to agents all at once, you build up catch mechanisms — reviews, plans, and knowledge capture — so that a mistake in any single unit of work is caught before it compounds[^08532e97@0]. Why they matter The methodology's core promise is that every unit of work makes the next one easier. Safety nets are what protect that promise: they give you the confidence to let agents handle more over time, because each stage of the loop — plan, work, review — is backed by something that catches errors and feeds what happened back into your accumulated knowledge[^08532e97@0]. - Safety nets = the trust-building practices that let you adopt Compound Engineering incrementally.- They sit inside the plan–work–review loop, catching mistakes so they don't compound.- As your maturity grows, you can lean on them less heavily — but you choose the level of trust yourself.