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How to get started with AI agents (and do it right)
- Enterprises need to choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models for AI Systems.
- Organizations that attempt to build agents on their own often struggle with retrieval augmented generation (RAG) and vector databases.
- RAG systems take 6-8 weeks to build and optimize, and developers require an understanding of data availability and quality.
- It's important to factor in existing licenses and subscriptions while looking at options for deploying AI agents third party, open-source or custom.
- When developing an enterprise AI strategy, it is important to take a cross-functional approach.
- Successful organizations involve several departments in this process, including business leadership, software development and data science teams, user experience managers and others.
- Organizations that attempt to build AI agents in-house may face difficulties that lead to failure.
- Enterprises must factor ongoing, post-deployment needs into their AI strategies from the very beginning.
- Third-party providers will likely have the bandwidth to keep up with the latest technologies and architecture to build this.
- All of these systems require some type of post-launch maintenance and support, ongoing tweaking and adjustment to keep them accurate and make them more accurate over time.
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