BestHub
Sign in
Tagged articles

Agentic Search

19 articles · Page 1 of 1
DataFunTalk
DataFunTalk
Oct 25, 2026 · Artificial Intelligence

Agentic Search: Alibaba Cloud Shifts AI Search from Answers to Task Execution

At Yunqi 2026, Alibaba Cloud unveiled Agentic Search 2.0, evolving AI search from answer generation to task execution via Search Agents, Elasticsearch Agent for ops and insights, FalconSeek engine, and a knowledge engine, with benchmarks showing 96.69% on LoCoMo, 81.37% on LongMemEval-V2, 68% token savings, and 70% cost reduction.

AI SearchAgentic SearchElasticsearch
0 likes · 13 min read
Agentic Search: Alibaba Cloud Shifts AI Search from Answers to Task Execution
DataFunTalk
DataFunTalk
Sep 28, 2026 · Industry Insights

JD Health Replaces RAG with Deterministic Engineering Stack for Medical AI

JD Health rebuilt a four-layer engineering stack — model, knowledge, harness, and delivery — replacing probabilistic RAG with deterministic Agentic Search and structured knowledge base LLMwiki to achieve verifiable, auditable medical AI across clinical tasks.

Agentic SearchDeterministic AIEngineering Stack
0 likes · 5 min read
JD Health Replaces RAG with Deterministic Engineering Stack for Medical AI
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Sep 24, 2026 · Artificial Intelligence

Alibaba Cloud Agentic Search: From Finding Answers to Completing Tasks

At the 2026 Yunqi Conference, Alibaba Cloud unveiled Agentic Search 2.0, a new AI search paradigm that evolves from answer generation to autonomous task execution via planning, tool use, and self-evolving memory, backed by a re-architected Elasticsearch engine delivering 60ms hot-query latency and 70% cost savings at hundred-billion-vector scale.

AI SearchAgentic SearchElasticsearch
0 likes · 13 min read
Alibaba Cloud Agentic Search: From Finding Answers to Completing Tasks
DataFunTalk
DataFunTalk
Aug 25, 2026 · Artificial Intelligence

Turning Search Tools into Enterprise Cognitive Engines with OpenClaw’s Agentic Search and Memory

The article explains how OpenClaw tackles the bottleneck of information overload in enterprise research by replacing static keyword search with an Agentic Search loop that iteratively understands, plans, executes, and learns, while Agentic Memory captures and reuses findings across sessions, creating a self‑reinforcing research flywheel.

Agentic SearchEnterprise AIKnowledge Management
0 likes · 12 min read
Turning Search Tools into Enterprise Cognitive Engines with OpenClaw’s Agentic Search and Memory
Machine Heart
Machine Heart
Jun 11, 2026 · Artificial Intelligence

Can Agents Search Without a Vector Database? A Simple Grep Is Enough

The paper introduces Direct Corpus Interaction (DCI), letting LLM agents bypass vector indexes and use command‑line tools like grep to directly search raw text, achieving higher accuracy and lower cost on complex multi‑hop QA and retrieval benchmarks.

Agentic SearchDirect Corpus InteractionLarge Language Models
0 likes · 12 min read
Can Agents Search Without a Vector Database? A Simple Grep Is Enough
AI Engineer Programming
AI Engineer Programming
May 28, 2026 · Artificial Intelligence

Claude Code Best Practices and Getting Started Guide for Large Codebases

This guide explains how Claude Code can be deployed in massive monorepos, legacy systems, and distributed repositories, detailing navigation methods, the limits of RAG, the benefits of agentic search, and a five‑layer support system—including CLAUDE.md, hooks, skills, plugins, and MCP servers—to help teams of thousands achieve reliable AI‑assisted coding.

AI codingAgentic SearchCLAUDE.md
0 likes · 18 min read
Claude Code Best Practices and Getting Started Guide for Large Codebases
DeepHub IMBA
DeepHub IMBA
May 27, 2026 · Artificial Intelligence

Testing Four Non‑Vector RAG Approaches: BM25, GraphRAG, Tree Search, and Agentic Search

The article evaluates four non‑vector Retrieval‑Augmented Generation methods—BM25 lexical search, GraphRAG graph traversal, Tree‑Search document navigation, and an Agentic search loop—using a small JSON‑based corpus, showing each method’s strengths, weaknesses, and when to combine them for production‑grade retrieval.

Agentic SearchBM25GraphRAG
0 likes · 12 min read
Testing Four Non‑Vector RAG Approaches: BM25, GraphRAG, Tree Search, and Agentic Search
IT Services Circle
IT Services Circle
May 27, 2026 · Artificial Intelligence

Can Claude Code Handle Million‑Line Codebases? Why the Harness Beats the Model

The article breaks down seven common pitfalls when using Claude Code on massive codebases, explains Anthropic’s agentic‑search approach, and shows how a well‑designed harness—including concise CLAUDE.md files, LSP integration, subdirectory launches, hooks, skills, plugins, and MCP servers—outperforms simply upgrading the model.

Agentic SearchClaude CodeHarness²
0 likes · 23 min read
Can Claude Code Handle Million‑Line Codebases? Why the Harness Beats the Model
AIWalker
AIWalker
May 17, 2026 · Artificial Intelligence

From Image Captioning to Detective‑Style Perception: Pixel‑Searcher Beats Closed‑Source Models

Pixel‑Searcher introduces an agentic search‑driven visual perception framework that integrates web‑based evidence with pixel‑level grounding, and the new WebEyes benchmark demonstrates its superiority over existing open‑ and closed‑source multimodal models across localization, segmentation, and VQA tasks.

Agentic SearchPixel-SearcherWebEyes
0 likes · 16 min read
From Image Captioning to Detective‑Style Perception: Pixel‑Searcher Beats Closed‑Source Models
Architect
Architect
May 16, 2026 · Artificial Intelligence

Turning Massive Codebases into Agent‑Ready Workspaces with Claude Code

The article analyzes how Claude Code can operate reliably in monorepos and large codebases by reorganizing the repository into an agent‑friendly environment, detailing the seven‑step agentic loop, the role of CLAUDE.md, LSP navigation, Subagents, and a three‑layer architecture that balances context, execution, and governance.

AI agentsAgentic SearchCLAUDE.md
0 likes · 30 min read
Turning Massive Codebases into Agent‑Ready Workspaces with Claude Code
Architect
Architect
May 8, 2026 · Artificial Intelligence

From Code Retrieval to Context Operations: The Next Architecture Shift in AI Programming

The article argues that AI programming is moving from asking whether models can write code to whether agents can autonomously locate, read, modify, execute, and verify context within real engineering environments, emphasizing the migration of context control from pre‑processing pipelines to agentic loops and the need for a robust harness.

AI codingAgentic SearchClaude Code
0 likes · 22 min read
From Code Retrieval to Context Operations: The Next Architecture Shift in AI Programming
Architect
Architect
Apr 25, 2026 · Artificial Intelligence

DeepSeek V4: 1M‑Token Context’s Impact on Model, Inference, Cache & Agents

The DeepSeek V4 technical report shows how a 1 million‑token context forces a redesign of attention, KV‑cache, optimizer, quantization and inference budgeting, turning long‑context capability from a costly showcase into a production‑ready feature for agents, search and Chinese professional tasks.

1M contextAgentic SearchAttention optimization
0 likes · 28 min read
DeepSeek V4: 1M‑Token Context’s Impact on Model, Inference, Cache & Agents
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 19, 2026 · Artificial Intelligence

How Engineering Knowledge Engines Turn AI Coders into Reliable Collaborators

The article analyzes the limitations of current AI coding agents—narrow perception, fragmented knowledge, and missing high‑dimensional context—and presents an Engineering Knowledge Engine that integrates vector retrieval, code and commit graphs, RepoWiki, memory, and Agentic Search to provide structured, evolving context, dramatically improving task success, token efficiency, and code quality.

AIAgentic SearchKnowledge Engine
0 likes · 11 min read
How Engineering Knowledge Engines Turn AI Coders into Reliable Collaborators
PaperAgent
PaperAgent
Jan 27, 2026 · Artificial Intelligence

How Agentic‑R Boosts Multi‑Turn Retrieval for LLMs by 2–3 EM Points

This article analyzes the Agentic‑R framework, which upgrades traditional single‑hop Retrieval‑Augmented Generation by introducing dual‑perspective scoring and a bidirectional flywheel, resulting in 2–3 absolute EM improvements across seven QA datasets and a 10–15% reduction in search rounds.

Agentic SearchContrastive LearningLLM
0 likes · 6 min read
How Agentic‑R Boosts Multi‑Turn Retrieval for LLMs by 2–3 EM Points
JD Tech Talk
JD Tech Talk
Dec 1, 2025 · Artificial Intelligence

How JoyAgent Enables Multimodal RAG for Enterprise Knowledge Management

JoyAgent, JD's open‑source intelligent‑agent platform, now adds multimodal Retrieval‑Augmented Generation (RAG) capabilities, combining graph‑based knowledge, hierarchical chunking, and vision‑language models to handle text, images, tables, and API data for enterprise knowledge processing and evaluation.

Agentic SearchEnterprise AIhierarchical chunking
0 likes · 11 min read
How JoyAgent Enables Multimodal RAG for Enterprise Knowledge Management