Agent Internals — Page 3

When AI agents can act, prompt injection becomes a multi-step attack chain.

Agents executing tools need guardrails at the architecture layer, not just the prompt.

Detect when agents repeat the same tool calls endlessly, before token budgets vanish.

Three distinct failure modes compound to derail long-horizon agent tasks.

Open-weight models now make local inference viable for serious agent work.

Engineering frameworks, visual builders, and agent operating systems serve three different teams.

Four moving targets break agents; catching regressions requires rethinking how tests work.

Runtime layers need to actively govern context windows like managed resources, not passive buffers.

How to build a shared context layer that keeps multiple agents aligned.

Persistent agent memory across sessions separates true automation from stateless chatbots.

GPU schedulers must treat multi-step agent workflows as single units, not isolated requests.