If you’ve made it this far, we hope you learned something along the way.

Evidence is piling up that the capabilities of GenAI will have a major impact on the world, something akin to the emergence of cloud computing. Getting your organization prepared to take advantage of this new technology won’t be simple, but it’s certainly not out of reach, no matter the size of your business.

If you work at a company with an existing data team or have experts in machine learning on staff, the world is your oyster. You can take a lot of your existing data pipeline and adapt it for vector databases, embedding models, and retrieval-augmented generation. If you want to create your own foundation model, there are lots of open-source tools and well-written tutorials on how to get started, not to mention vendors who can help you do it relatively cheaply.

For most folks, creating your own foundation model won’t be necessary, since you can order them as a service from many providers. There are also lots of off-the-shelf options for your vector database and embedding needs. You’ll want to focus on fine-tuning of the model on your own data, the way you chunk your data for RAG, and the process of human feedback and reinforcement learning that will optimize the LLM’s responses for your intended use case.

The one thing you can’t buy

The latest research continues to highlight the fact that data quality is the most important factor in improving the performance of a GenAI model. Training your system on information it can properly digest provides a far greater return on investment than optimizing your algorithm or adding more compute.

For high-quality data, you’ll need to work closely with different teams inside your organization to understand where you can find data for your use case. Don’t forget to include your legal and infosec teams, who’ll ensure that the data you’re using doesn’t risk exposing private information or compromising any licenses or copyrights.

Take some time to think about where you can best apply an LLM with your data. Maybe it’s your codebase: creating an AI agent that can improve your developers' productivity. It could be trained on your help documentation and forum posts, giving it the data it needs to be a useful tech-support bot. Or it could ingest your internal documentation, allowing it to serve as an intelligent layer on top of enterprise search.

Fortunately, our internal approach to documentation was already well-suited to this challenge. Stack Overflow for Teams uses the wisdom of your employees to ensure the best answers rise to the top and keeps an eye on your content health to prevent information from becoming inaccurate or outdated.

And coming soon with the power of OverflowAI, you could have:

  • Instant solutions to your teams’ most common technical challenges.
  • New insights created as answers are summarized across your knowledge base.
  • The power of coding with context with Stack Overflow inside your coding environment.
  • The ability to capture and convert knowledge from other sources into an easily accessible and digestible format.

If you’re ready to partner with us to enter the era of AI-powered knowledge management, get in touch with us below!

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