AI work often moves between agents, models, machines, or people.

The handoff fails when the next worker inherits a summary instead of the actual state of the work.

An AI run that fails is not automatically wasted work.

It becomes wasted work when nobody can tell why it failed, what was learned, and what the next attempt is allowed to do differently.

Some software work does not fit into one AI session.

That is normal. The problem is what happens when the next session has to continue from memory, a long chat, or a half-understood diff.

More context is not the answer.

The agent needs something it can obey.

Otherwise it will guess.

Speed is easy.

Consistency is not.

The failure shows up late.

The change is easy.

The hidden dependency is not.

That is where fast work turns expensive.