Turning My Obsidian Vault Into a Local AI Engineer
Personal knowledge bases are messy, but engineering agents need memory: decisions, docs, TODOs, old PRs, architecture notes, incident notes. This talk shows how I made an Obsidian vault usable by an agent using local-first retrieval and small-model inference. The point is not “chat with notes”; it is how to build durable, inspectable agent memory.
About the Workshops Day 1 Track
Workshops Day 1 sessions at AI Engineer World's Fair 2026 in San Francisco.
When
Monday, June 29, 2026
1:15 PM - 2:15 PM·1h
Where
Track 8 · Room 2020
Capacity: 250 attendees
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Speaker
Filip Makraduli
Machine Learning Engineer
Superlinked
@f_makraduli
Filip Makraduli is an applied AI researcher and founding ML Developer Relations engineer at Superlinked, where he designs and ships small‑LLM inference systems for search, retrieval, and agents in production. He holds a master’s degree in Biomedical Data Science from Imperial College London. Before Superlinked, Filip worked in machine learning, data science, and developer relations roles across early‑stage AI startups and larger enterprises, building language understanding, retrieval‑augmented generation (RAG), and LLM pipeline tooling while partnering closely with product and platform teams. He is a frequent open‑source contributor, with contributions to kernel libraries, model‑inference providers, and hands‑on demos used by practitioners. Filip is a co‑author of several publications on efficient transformer architectures and inference, including work on faster normalization for LLMs. He is an experienced speaker at meetups and conferences such as AI Engineer Europe and Berlin Buzzwords, sharing practical lessons on efficient transformers, retrieval systems, and embedding inference for production AI teams.