LLMs, Agents, and Data Science's Future

Recent advances in AI like large language models, prompt engineering techniques, AI agents, etc. provide new opportunities as well as challenges for the development of data science, and data practitioners should adopt a balanced perspective when assessing and utilizing these new technologies.


  • The article highlights some of the best recent articles published by Towards Data Science (TDS), covering topics like prompt engineering, capabilities of large language models like ChatGPT, building AI agents, music AI, and the impact of generative AI on data science.
  • It discusses the winning strategies from a prompt engineering competition, stressing that prompt engineering blends both art and science.
  • When assessing if ChatGPT is truly "intelligent", the answer is no as per scientific review. However, its magical performance can seem intelligent to anyone unfamiliar with its limitations. Hence a balanced perspective is required.
  • Similar balanced perspective needed on the thinking capabilities of AI models - neither over-exaggerating nor under-representing them.
  • Discusses experiment to build an LLM-powered analytical agent to replace workflows currently handled by data analysts. Follow-up guide delves deeper into LLM agents.
  • Guide on developing a deep Q-learning based AI agent from scratch, useful for beginners.
  • New advances in AI can enhance decision-making capabilities and decision support systems.
  • Emerging music AI capabilities like music embeddings, new applications etc. outline promising future.
  • While doom of data science has been prematurely announced before, cautious optimism needed on impact of generative AI. These can affect workflows but also provide new opportunities.
  • TDS continues to build community, adding new authors each month.


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