A developer built a search engine over 50k saved tweets using hybrid retrieval and reranking, then added a single endpoint to turn it into an answer engine. By wiring Gemma 4 MoE to the retrieval pipe…
A developer argues that pure vector search is insufficient for production RAG systems, as it fails on exact-match queries like product codes or legal citations. Hybrid search, combining BM25 sparse re…
A developer built a Code-RAG benchmark on Apache Kafka 4.0.0 to study how retrieval pipeline choices affect model rankings. Comparing 16 embedding models, 5 chunking strategies, and 3 retrieval modes …
A developer built neuro-skill, a hybrid skill router that runs entirely on a local machine without API calls or GPUs, achieving 95% Hit@1 accuracy on core domains. The system fuses five signals via Re…
Agentic RAG systems that learn from past interactions are vulnerable to memory poisoning attacks, where attackers plant false memories that the system treats as ground truth. Researchers at the Univer…
A developer built a RAG (Retrieval-Augmented Generation) system to let their team chat with internal documentation, replacing a wiki search that failed to answer common questions. After experimenting …
Researchers from a study on arXiv introduce HieraRAG, a hierarchical framework for determining optimal granularity in RAG benchmark construction, using 5,872 synthetic QA pairs from FineWeb-10BT acros…
A developer built a Quantified-Self RAG (Retrieval-Augmented Generation) system that ingests a decade of personal medical records from messy PDF scans using Unstructured.io, Sentence-Transformers, and…
A developer built a production-grade RAG pipeline that achieves 95.6% retrieval accuracy and 99/100 answer quality by fusing BM25, TF-IDF, and dense vectors with weighted Reciprocal Rank Fusion, addre…
AgentMemory launched a persistent memory runtime for coding agents that captures every session, tool call, and prompt through 12 auto-hooks, enabling millisecond recall via triple-stream retrieval com…
A developer built Vektr, a custom RAG engine implementing HNSW graphs from scratch, achieving recall@10 of 0.984 — meaning 98.4% of queries returned all 10 true nearest neighbors in the top results. T…
A developer found that retrieval systems retrieving sensitive memories mislabeled as ordinary context produce false-certainty errors, where agents confidently act on sensitive content without verifica…
A company's internal omni-search system, built using Retrieval Augmented Generation (RAG), gave an on-call engineer the wrong runbook instructions for enabling a feature flag in production. The system…
A developer built a production-grade Medical Retrieval-Augmented Generation (RAG) system that cures LLM hallucinations by grounding clinical AI responses in peer-reviewed evidence from the PubMed API.…
Developer Dharanidharan J (JD) has built FileRAG, a memory architecture for personal AI that stores a distilled understanding of each user in a single plain-text `.txt` file. The system uses hybrid BM…
An engineer built a documentation Q&A engine that returns `null` instead of hallucinating answers when a query has no match in the corpus. The Knowledge Base API uses BM25 retrieval with POS-aware lem…
Second-brain-mcp is a self-maintaining personal knowledge database that uses MCP, DuckDB, and biological memory models to automatically link, compress, and index saved papers, notes, and figures. The …
A developer built Provenant, a system that generates human-readable wiki pages for every file and module in a codebase, then searches those pages instead of raw source code. On SWE-bench Verified acro…
Auto-itera, an autonomous experimentation engine, now automates AI engineering decisions by running controlled experiments on real production data. Users define a goal, provide candidate arms, and set…
To build a production-ready Retrieval-Augmented Generation (RAG) pipeline in Python using BM25 retrieval via Meilisearch instead of a vector database, arguing that BM25 achieves 85–95% of the recall o…