ReAct thinks and acts one step at a time, Plan-and-Execute plans before moving, and Reflection checks the work afterward. This guide explains the problem each common Agent pattern solves, the cost it introduces, and how to combine the three in practice.
Agent loss of control is not a science fiction problem but an engineering one: overly broad tool permissions, injection of instructions via external content, contaminated memory, and undefined task boundaries. This article dissects the four most common failure modes and provides a practical framework for protective design.
A guide for technical and product professionals changing direction or upgrading their capabilities, ranking the AI skills worth investing in during 2026 by employment value, learning difficulty, salary premium, and future demand.
PDF is one of the hardest inputs for RAG: scans require OCR, tables get flattened, and multi-column layouts scramble reading order. This guide breaks the workflow into four stages—extract text, preserve structure, chunk and index, then answer questions—and explains the pitfalls and tool choices at each step.
While context windows have expanded from thousands to millions of tokens, the ability to 'hold' more data does not guarantee it is used effectively. This article clarifies three real-world failure modes of long-context models: ignoring information in the middle of a sequence, reduced accuracy due to distracting content, and soaring costs and latency. It also outlines when to leverage long contexts versus when Retrieval-Augmented Generation (RAG) is the better choice.
Recall ensures nothing is missed; reranking ensures the right order. This article clarifies the fundamental differences between Cross-Encoder reranking and vector retrieval, explains when adding a reranker is worthwhile, guides model selection, and provides a ready-to-use two-stage retrieval configuration.
A comparison of Perplexity, ChatGPT Search, Gemini, and You.com across citation quality, freshness, understanding of complex questions, and the Chinese-language search experience.
Compare ElevenLabs, OpenAI TTS, Azure Speech, and Fish Audio on voice naturalness, cloning quality, latency, pricing, and API usability.
Document splitting is the most cost-effective yet often overlooked step in RAG. This article compares four strategies—fixed-length, recursive, structured, and semantic chunking—and evaluates their performance across different chunk sizes, offering a ready-to-use default configuration and an optimization workflow.
When RAG gives incorrect or off-target answers, the model usually is not the problem—the retrieval pipeline is. This guide identifies 10 common engineering causes across ingestion, retrieval, and generation, with practical fixes and ways to validate each one.
Vector search understands meaning but struggles with model numbers and identifiers. BM25 matches exact words but misses paraphrases. Hybrid search runs both and combines the results. This guide explains their tradeoffs, reciprocal rank fusion, and which approach fits each use case.
A hands-on comparison of Sora, Runway, Kling, Pika, and Hailuo across image quality, motion consistency, control, cost, and commercial workflows to help video creators choose the right tool.
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