Agents Are Files
Like a game console with cartridges, one host runs different agents. Edit their files, turn failures into evals, and keep release checks with the host.
#agents
5 posts
Close the gap by iteration, not specification
A follow-up. The under-specification problem in coding agents does not close by writing better specs upfront. Models do not stick to instructions anyway. The gap closes by building better detection: catching deviation cheaply, often, and at the right level of abstraction. The lever is the loop, not the prompt.
Your coding agent is under-specified
Coding agents write impressive first drafts. But under the surface, corners are cut, details are missing, and technical debt accumulates with every change. The problem is not the model. It is that what we ask it to do is fundamentally under-specified.
The loop is the product
Agent frameworks hide the loop behind agent.run() and a graph DSL. But the loop is where every interesting decision happens: what the model sees, whether a tool call proceeds, when to stop, what to record. What if you owned the loop and the framework just made it composable?
The verification asymmetry
Offense asks 'does a bug exist?' Defense asks 'are all bugs gone?' The first is an existential claim you can check with one example. The second is a universal claim you cannot fully check. This difference determines where AI agents work in security more than model capability does.