Deleting RAG from our web agent made it 2.3x faster
We rewrote Skyvern from scratch using Pi as inspiration, making it 2.3x faster and score 90.5% on Odysseys benchmark.
Skyvern Blog6 min read
retrieval augmented generation
518 stories
A New Agentic Experience: JetBrains Air in IDEs – EAP Now Open
Last week, we shared our point of view on where we think agentic development is headed and introduced JetBrains’ answer to it: JetBrains Air, an open system of products for agentic development. Today, we’re launching the Early Access Program for Air in JetBrains IDEs.
JetBrains AI Blog8 min readClaude Code Custom Commands & Skills: Automate Your Workflow
Every dev team has repeatable setup tasks: spinning up a new project, running a deployment checklist, generating a file structure, or typing the same instructions into Claude again and again.
Analytics Vidhya7 min readWhen to Use an LLM Knowledge Graph or a Vector RAG
An LLM knowledge graph and vector RAG ground models differently. See when to use each, how to build a knowledge graph from text, and how to run both smoothly.
n8n Blog6 min readConformal Factuality Control for Multi-Hop Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) can ground large language models in external evidence, but retrieved context does not guarantee that generated claims are factually supported.
arXiv - stat.ML2 min readWhat is Google Gemini?
Google has been in its "Gemini era" for a couple years now, and while the confusing rebrandings have slowed, everything else continues to improve at a rapid pace.
Zapier AI Blog13 min readThe best large language models (LLMs) in 2026
Large language models (LLMs) are what most people think of when they think of AI. They're what you're interacting with in ChatGPT and Claude, they write the code generated by Claude Code and Codex, and they power other AI features like Google's AI answers and Apple Intelligence.
Zapier AI Blog18 min readQuery claims in natural language with Amazon Bedrock Knowledge Bases
This technical how-to builds a conversational claims assistant on Amazon Bedrock Knowledge Bases that answers natural-language questions with citations.
AWS ML Blog14 min readAmazon S3 Vectors introduces metadata pre-filtering for up to 5x higher recall on filtered search
Amazon S3 Vectors now supports pre-filtering, which evaluates metadata filters before running similarity search, returning up to 5x more of the matching vectors when your filter is selective. S3 Vectors also adds a prefix match operator ($startsWith) for filtering on values like paths and URLs.
AWS New (What's New)2 min readYour AI Agent Will Obey Anyone. Guardrails Are How You Stop It.
Your AI Agent Will Obey Anyone. Guardrails Are How You Stop It. A guide to the attacks that break LLMs and AI agents, and the guardrails that stop each one. This guide assumes you know nothing about …
Towards AI9 min readEmbedding Models for Production RAG: From Text to Searchable Vectors
Complete RAG Engineering Series, Part 5 | A practical guide to dense and sparse embeddings, model selection, Matryoshka embeddings…Continue reading on Towards AI »
Towards AI1 min readCohere’s faster query model barely dents retrieval quality in its tests
Cohere released Embed 5 on Wednesday, giving teams the option to index data with Embed 5 Pro and query those The post Cohere’s faster query model barely dents retrieval quality in its tests appeared first on The New Stack.
The New Stack - AI4 min readRAG Tutorial for Beginners: Build a Retrieval Pipeline in Python
RAG stands for retrieval augmented generation. Strip the jargon and it is one idea: the model does not know your documents, so before you ask it a question, you look up the relevant passage yourself and paste it into the prompt. Retrieve, augment, generate. That is the whole trick.
Dev.to AI5 min read# When does an AI agent actually earn its cost? I measured it on 100 questions
Built for the TigerGraph Agentic GraphRAG Hackathon. Repo and dashboard linked at the end. RAG retrieves text. GraphRAG adds structure. Agentic GraphRAG lets a model plan its own investigation. Everyone assumes the third one is better — but by how much, and on which questions?
Dev.to AI5 min readModel Context Protocol Documentation: Spec, Schema, Changelog
Short answer: Model Context Protocol documentation is versioned by date, not by number. Each revision has its own specification pages, a schema published beside them, and a changelog recording what moved since the previous revision.
Dev.to AI18 min readApify vs. Firecrawl: how Firecrawl compares to the Apify Actors built for the same job
Features, pricing, and crawl options side by side, plus a look at Firecrawl's new Alexandria library and when each platform is the better pick.
Apify Blog16 min readBest Open-Source LLM Observability Platform for Production (2026 Comparison)
Your security team says traces can’t leave the building. Your finance team says the observability bill can’t grow with traffic. Your engineering team says they...
Opencontroller by lyzr Blog16 min read🟢 Voyage AI: Resolved — Elevated 5xx errors on rerank and voyage-context-4
No — Voyage AI is operational. Uptime: 99.94%. 4 incidents tracked (30d). Live status, updated every 5 minutes.
AIWatch Blog3 min read
Showing 198 of 518 stories
Load more storiesAiByts Weekly Brief
Get the top AI news and tools straight to your inbox every week.
Weekly · AI news
Join 15,000+ AI enthusiasts