Viewing profile — saezbaldo

Agree, and I'd add: the feedback loop between decision and consequence got dramatically shorter. You can test an architectural hypothesis in hours instead of weeks. That part is ge…

This is the under-discussed part. We spent decades building authorization layers around code deployment -- review gates, CI checks, staging, rollback. That infrastructure exists be…

The thread illustrates a recurring pattern: encrypting the artifact instead of narrowing the authority. An agent executing code in your environment has implicit access to anything …

This reframes the whole conversation. If implementations are cheap to regenerate, specifications become the durable artifact. Something like TLA+ model checking lets you verify tha…

The context window is the onboarding period. Every invocation is a new hire reading the codebase for the first time. This is why architecture legibility keeps getting more importan…

The cascading failure point is critical. A 1% miss rate per layer in a 5-layer pipeline gives you roughly 5% end-to-end failure, and that's assuming independence. In practice the f…

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The bigger gap isn't time vs tokens. It's that these metrics measure capability without measuring authorization scope. An agent that completes a 45-minute task by making unauthoriz…

Hi HN. I built IC-AGI because every AI agent framework I looked at gives the agent full authority once it gets an API key. That's fine for demos but scary for anything touching pro…

One underexplored reason: companies can't give AI agents real authority. The moment an agent needs to do anything beyond summarizing text — update a CRM, transfer funds, modify inf…

The fundamental issue here isn't the specific vulnerabilities — it's that these agent frameworks have no authorization layer at all. They validate outputs but never ask "does this …