HELM Long Context
We introduce the HELM Long Context leaderboard for transparent, comparable and reproducible evaluations of long context capabilities of recent models.
Alpaca Blog18 min read
retrieval augmented generation
527 stories
New in Kiln: Search Tools/RAG, Document Library, and Synthetic Data V3
Introducing our biggest release ever! Build state-of-the-art RAG systems in minutes, with drag-and-drop!
Kiln Blog2 min read
PageIndex: Next-Generation Vectorless, Reasoning-based RAG
PageIndex is a vectorless, reasoning-based retrieval framework that simulates how human experts extract knowledge from complex documents. Instead of relying on vector similarity search, it builds a tree-structured index from documents and enables LLMs to perform agentic reasoning over that…
PageIndex Blog8 min read
Vector Databases and LLM's - Why They Need Each Other
Understanding how vector databases and LLMs work together, why they complement each other.
VoltAgent Blog7 min read
The AI Margin Dashboard: What to Watch Daily, Weekly, Monthly
If you only track MRR, you'll miss the cliff. Here's the margin scorecard operators actually use to stay profitable.
UnitPay Blog2 min read
AI Agents Made Simple with VoltAgent
The evolution of AI agents, framework choices, and production challenges. Modern agent development with VoltAgent and VoltOps.
VoltAgent Blog5 min read
From Claude Code to Agentic RAG
The same bet behind both PageIndex and Claude Code: skip the vector DB and let the LLM itself drive retrieval. We explore the rise of agentic retrieval over vector indexing and PageIndex's agentic, vectorless RAG framework.
PageIndex Blog8 min read
What makes Claude Code so damn good (and how to recreate that magic in your agent)!?
Claude Code is the most delightful AI agent/workflow I have used so far. Not only does it make targeted edits or vibe coding throwaway tools less annoying, ...
MinusX Blog12 min readChallenges and Considerations Behind Trae Cue
Cue is one of the latest and most complex AI development tool features developed by TRAE. We explored the technical challenges, achievements as well as future plans for TRAE Cue.
Trae Blog5 min read
Document Columns, Function Evaluations, and Async Evals via SDK
Upload documents into datasets with built-in OCR, write deterministic function evals for objective checks, and run evaluations async from the SDK.
Future AGI Blog4 min read
Distillation with Programmatic Data Curation: Smarter LLMs, 5-30x Cheaper Inference
Every LLM application builder faces a fundamental tradeoff: large models deliver superior performance at higher costs, while small models are affordable but often underperform. This choice becomes critical when scaling to production workloads where inference costs can quickly explode.
TensorZero Blog38 min read
Voice Agents: Easy to Use, Hard to Build
Voice has emerged as a widely adopted modality in applied AI. From call centers to scheduling assistants, voice agents are entering more production use cases across various industries than ever before. Despite how natural it feels to speak, building low-latency, conversational voice agents remains…
Greylock8 min read
Evaluating Long-Context Question & Answer Systems
Evaluation metrics, how to build eval datasets, eval methodology, and a review of several benchmarks.
Eugene Yan26 min readSummarize Hacker News Posts with Haystack & OPEA
Welcome to this step-by-step tutorial where we’ll build a simple Retrieval-Augmented Generation (RAG) pipeline using Haystack and OPEA. We’ll fetch the newest Hacker News posts, feed them to a lightweight LLM endpoint (OPEAGenerator), and generate concise one-sentence summaries (based on this…
Haystack Blog4 min read
RAG Evaluation Metrics: Assessing Answer Relevancy, Faithfulness, Contextual Relevancy, And More
RAG evaluation metrics — answer relevancy, faithfulness, and contextual relevancy — measure retrieval and generation quality, with working DeepEval code examples.
Confident AI (DeepEval)17 min read
RAG vs. fine-tuning
What I learned performing work with RAG and Fine-tuning. A calm tutorial to choose the right method, full of real experiences for newbies.
VoltAgent Blog7 min read
When Fine-Tuning Actually Makes Sense: A Developer's Guide
Most teams are curious about fine-tuning and how it might help their AI products, but they don't know what to expect from the process, how to measure success, or where to start.
Kiln Blog7 min read
Code Comprehension at Scale: Learning from the Bitter Lesson
Handcrafted tricks break at scale. The future of code comprehension lies in holistic, learning-based systems.
Hopper Blog6 min read
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