I’m committing to read these 3 white papers. The one on foundational LLM, the one on prompt engineering and the one agents. I think they’ll will be helpful in helping eventually build an AI product.
Great choices Tope! 🚀 These three really set the stage - from the basics into action-oriented systems. I’d love to hear what stands out as you dig in. Good luck with your AI product! 🤖
Thanks and great question Chintan! I’m definitely an Agents guy 🤖 That whitepaper pulls everything together: planning, memory, vector search, tool integration. It’s where LLMs go from passive responders to active problem-solvers. It’s the most forward-looking piece in the set, and I think it hints at where GenAI is really headed ⏩
Excellent breakdown! I like all the added deep dive resources
Thanks so much Joel 🙏🏻 I’m really glad the deep dives resonated! Curious: which whitepaper stood out the most for you? 😃
Solving Domain-Specific Problems Using LLMs, made me think of a few new things. Good work, look forward to your next post.
I’m committing to read these 3 white papers. The one on foundational LLM, the one on prompt engineering and the one agents. I think they’ll will be helpful in helping eventually build an AI product.
Great choices Tope! 🚀 These three really set the stage - from the basics into action-oriented systems. I’d love to hear what stands out as you dig in. Good luck with your AI product! 🤖
Thank you!
Thanks for sharing these whitepapers Jakub. Which one is your favorite? 😄
Thanks and great question Chintan! I’m definitely an Agents guy 🤖 That whitepaper pulls everything together: planning, memory, vector search, tool integration. It’s where LLMs go from passive responders to active problem-solvers. It’s the most forward-looking piece in the set, and I think it hints at where GenAI is really headed ⏩
For sure jakub agentic AI is where it’s at in 2025. Sounds like an interesting whitepaper!