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Artificial Intelligence & Next-Gen LLMs

AI Agents and Autonomous Swarms

AI agents go beyond chat by planning, using tools, and acting toward a goal. Swarms coordinate many agents on larger tasks. The promise is real automation, but so are the failure modes: loops, tool misuse, and runaway cost. Start small, bound the actions, and watch everything.

Ključne točke

  1. Give each agent a narrow role and a clear stopping condition.
  2. Limit tool access to the minimum needed for the task.
  3. Add human approval gates for destructive or costly actions.
  4. Cap steps, tokens, and spend per run to prevent runaway loops.
  5. Log every tool call and decision for debugging and audit.
  6. Use deterministic tools for math, dates, and lookups.
  7. Test agents on adversarial and edge-case tasks.
  8. Start with one agent before orchestrating many.

Pogosta vprašanja

Are agents reliable enough for production?

For bounded tasks with good tools and monitoring, yes; open-ended autonomy still needs oversight.

How do swarms avoid chaos?

Clear roles, shared state, and a coordinator that assigns and merges work.

What is the biggest risk?

Tool misuse and silent failures that look like success.

Do agents need their own memory?

Short-term scratchpads help; long-term memory needs careful curation.

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