BestHub
Sign in
Tagged articles
11 articles
Page 1 of 1
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 codingCLAUDE.mdClaude Code
0 likes · 18 min read
Claude Code Best Practices and Getting Started Guide for Large Codebases
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.

Claude CodeHarnessLSP
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.

MultimodalPixel-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 agentsCLAUDE.mdClaude Code
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 codingClaude CodeContext Engineering
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 contextAttention optimizationDeepSeek
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.

AICode Graphagentic search
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.

LLMMulti-hop reasoningRAG
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.

Multimodal RAGOpen Sourceagentic search
0 likes · 11 min read
How JoyAgent Enables Multimodal RAG for Enterprise Knowledge Management