building an app is becoming one prompt. knowing it actually works isn't.
an agent's effectiveness is proportional to its ability to verify its work.
no tests it can run itself? you get a first draft.
good, better, best verification for claude code & codex 👇
https://t.co/wvJM9oKcFo
the old bet: the value is in the harness, the model just needs to be competent. the new reality: models are eating the harness. subagents, planning, tool use, all built in. does the model always win?
agent verification is all you need and it’s analogous to TDD. Use a process that constraints and shapes the output for agent to maximize https://t.co/oAG14vBUiy
building an app is becoming one prompt. knowing it actually works isn't.
an agent's effectiveness is proportional to its ability to verify its work.
no tests it can run itself? you get a first draft.
good, better, best verification for claude code & codex 👇
https://t.co/wvJM9oKcFo
@ibuildthecloud@wesleyboland This looks a lot like what we’ve built at atomic with intents. Cool part is they are then linked together with the change in the semantic change graph.
for example, datadog/sentry’s internal metrics must scale higher than the app its monitoring (sampling be damned). for a software factory to effective it must understand the meta properties of the product being built - does seo matter? does compile time matter? is the product gaining traction? are stories/issues being stuck in some dev state?
the analytics tell me what to do next, but the direction feels ‘copy what everyone else is doing’ and less ‘be unique and special’. i guess the ‘work’ begins...