AI & ML Research 3 Days

Last updated: July 13, 2026, 11:30 AM ET

AI & ML Research Briefing

Agentic AI and Alignment

A framework for aligning agentic AI with enterprise intent for consistent autonomous behavior. Developers are also learning to using Claude Code for parallel execution.

LLM Development and Challenges

Researchers are exploring techniques to manage LLM performance, noting that, as accumulated tokens increase cost and latency. Even frontier AI models, leading to hallucinations that can be costly or damaging. Two distinct approaches, RAG and fine-tuning, are, with the discussion focusing on their appropriate use cases rather than direct competition.

Data Engineering and Model Building

One engineer shared their experience, adopting a data engineering mindset using Python, Docker, Postgre SQL, and Kestra. In model development, a distinction is made between academic models explaining "why" and industry models predicting "who," with the observation that the statistics barely changed while the surrounding context evolved significantly.