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Getting started with AI agents (part 2): Autonomy, safeguards and pitfalls
Success in building AI agents hinges on mapping roles and workflows and establishing safeguards such as human oversight and error checks.
I explained how, unlike standalone AI models, agents iteratively refine tasks using context and tools to enhance outcomes such as code generation. I also discussed how multi-agent systems foster communication across departments, creating a unified user experience and driving productivity, resilience and faster upgrades. Success in building these systems hinges on mapping roles and workflows, as well as establishing safeguards such as human oversight and error checks to ensure safe operation.
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