<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>Datas Blog</title><description>Clear explainers on AI, machine learning, and data science for practitioners and the curious.</description><link>https://datasblog.com/</link><item><title>Run Muse Glimmer Locally with llama.cpp, DFlash, and Pi</title><link>https://datasblog.com/post/run-muse-glimmer-locally-with-llamacpp-dflash-and-pi-36154d/</link><guid isPermaLink="true">https://datasblog.com/post/run-muse-glimmer-locally-with-llamacpp-dflash-and-pi-36154d/</guid><description>Learn how to run Muse Glimmer 30B locally using llama.cpp with DFlash speculative decoding and the Pi coding agent for agentic workflows.</description><pubDate>Fri, 21 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Kimi K3&apos;s 1M Token Context Window Tested Against RAG</title><link>https://datasblog.com/post/kimi-k3s-1m-token-context-window-tested-against-rag-623042/</link><guid isPermaLink="true">https://datasblog.com/post/kimi-k3s-1m-token-context-window-tested-against-rag-623042/</guid><description>A blind experiment comparing RAG and long-context retrieval on 12 questions across 32 articles, measuring cost, latency, and answer quality.</description><pubDate>Wed, 19 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Run Qwen3-27B as a Local AI Coding Agent in 3 Commands</title><link>https://datasblog.com/post/run-qwen3-27b-as-a-local-ai-coding-agent-in-3-commands-a0ad2d/</link><guid isPermaLink="true">https://datasblog.com/post/run-qwen3-27b-as-a-local-ai-coding-agent-in-3-commands-a0ad2d/</guid><description>Use Ollama and OpenCode to run Qwen3.8-27B locally as an AI coding agent. No server configuration required — just three terminal commands.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Effective Project Management for Software Engineers in the Age of LLMs</title><link>https://datasblog.com/post/effective-project-management-for-software-engineers-in--c6c24e/</link><guid isPermaLink="true">https://datasblog.com/post/effective-project-management-for-software-engineers-in--c6c24e/</guid><description>LLMs have shifted how software engineers spend their time. Here are three techniques to manage projects more effectively with AI agents.</description><pubDate>Mon, 17 Aug 2026 00:00:00 GMT</pubDate></item><item><title>How to Build a Simple AI Web Scraper with Python</title><link>https://datasblog.com/post/how-to-build-a-simple-ai-web-scraper-with-python-9b877b/</link><guid isPermaLink="true">https://datasblog.com/post/how-to-build-a-simple-ai-web-scraper-with-python-9b877b/</guid><description>Learn how to fetch, clean, and convert webpages to Markdown, then use an LLM to return focused answers from page content.</description><pubDate>Fri, 14 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Building a Streaming Local AI Agent with Wikipedia and Ollama</title><link>https://datasblog.com/post/building-a-streaming-local-ai-agent-with-wikipedia-and--954ff7/</link><guid isPermaLink="true">https://datasblog.com/post/building-a-streaming-local-ai-agent-with-wikipedia-and--954ff7/</guid><description>Build a local AI agent that watches Wikipedia&apos;s live edit feed and reasons about vandalism using a two-stage filtering pipeline and Ollama.</description><pubDate>Thu, 13 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Before Full Agentic RAG: Parsing Decisions You Should Control</title><link>https://datasblog.com/post/before-full-agentic-rag-parsing-decisions-you-should-co-f1ba70/</link><guid isPermaLink="true">https://datasblog.com/post/before-full-agentic-rag-parsing-decisions-you-should-co-f1ba70/</guid><description>A rule-based document parsing dispatcher gives enterprise RAG pipelines explicit, inspectable control over which methods run and why.</description><pubDate>Wed, 12 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Budget Allocation With Linear Programming That Explains Itself</title><link>https://datasblog.com/post/budget-allocation-with-linear-programming-that-explains-16e0ae/</link><guid isPermaLink="true">https://datasblog.com/post/budget-allocation-with-linear-programming-that-explains-16e0ae/</guid><description>A constrained LP approach to budget allocation that preserves shadow prices, letting the model explain exactly what each rule costs.</description><pubDate>Tue, 11 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Specification Engineering: The Next Skill Beyond Prompt Engineering</title><link>https://datasblog.com/post/specification-engineering-the-next-skill-beyond-prompt--8215fb/</link><guid isPermaLink="true">https://datasblog.com/post/specification-engineering-the-next-skill-beyond-prompt--8215fb/</guid><description>Prompt engineering helps you ask better questions. Specification engineering defines what a correct answer actually looks like.</description><pubDate>Mon, 10 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Five Token Cost Traps Hidden in Your Agentic Loop</title><link>https://datasblog.com/post/five-token-cost-traps-hidden-in-your-agentic-loop-cd6d2a/</link><guid isPermaLink="true">https://datasblog.com/post/five-token-cost-traps-hidden-in-your-agentic-loop-cd6d2a/</guid><description>Token costs compound non-linearly in agentic AI loops. Learn five failure modes and the architectural patterns to control them.</description><pubDate>Fri, 07 Aug 2026 00:00:00 GMT</pubDate></item><item><title>How Kimi K3 Was Built: Inside the Technical Report</title><link>https://datasblog.com/post/how-kimi-k3-was-built-inside-the-technical-report-7c1889/</link><guid isPermaLink="true">https://datasblog.com/post/how-kimi-k3-was-built-inside-the-technical-report-7c1889/</guid><description>Moonshot&apos;s Kimi K3 report reveals the training, architecture, and RL decisions most frontier labs keep private. Here&apos;s what it says.</description><pubDate>Wed, 05 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Introduction to Semi-Supervised Learning for Classification Problems</title><link>https://datasblog.com/post/introduction-to-semi-supervised-learning-for-classifica-3092df/</link><guid isPermaLink="true">https://datasblog.com/post/introduction-to-semi-supervised-learning-for-classifica-3092df/</guid><description>Semi-supervised learning combines labeled and unlabeled data to train classifiers. Learn the core assumptions and algorithm types that make it work.</description><pubDate>Wed, 05 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Agent Harness, Loop, and Graph Engineering: What&apos;s the Difference?</title><link>https://datasblog.com/post/agent-harness-loop-and-graph-engineering-whats-the-diff-17b1bc/</link><guid isPermaLink="true">https://datasblog.com/post/agent-harness-loop-and-graph-engineering-whats-the-diff-17b1bc/</guid><description>Harness, loop, and graph engineering solve distinct problems in agent design. Mixing them up leads to costly mistakes in production systems.</description><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Honest Review: Abacus AI&apos;s ChatLLM, DeepAgent, and AI Studio</title><link>https://datasblog.com/post/honest-review-abacus-ais-chatllm-deepagent-and-ai-studi-aaf8d5/</link><guid isPermaLink="true">https://datasblog.com/post/honest-review-abacus-ais-chatllm-deepagent-and-ai-studi-aaf8d5/</guid><description>Abacus AI offers 100+ models, autonomous agents, and creative tools in one subscription. Here&apos;s what it actually delivers.</description><pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate></item><item><title>MiniMax Agent (Mavis): Architecture, Costs, and Real API Testing</title><link>https://datasblog.com/post/minimax-agent-mavis-architecture-costs-and-real-api-tes-c3b991/</link><guid isPermaLink="true">https://datasblog.com/post/minimax-agent-mavis-architecture-costs-and-real-api-tes-c3b991/</guid><description>MiniMax&apos;s Agent Teams architecture splits tasks across Leader, Worker, and Verifier roles. Here&apos;s what that means in practice, tested against the real API.</description><pubDate>Mon, 03 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Agentic Misalignment: What Anthropic Found Testing 14 AI Models</title><link>https://datasblog.com/post/agentic-misalignment-what-anthropic-found-testing-14-ai-12d55e/</link><guid isPermaLink="true">https://datasblog.com/post/agentic-misalignment-what-anthropic-found-testing-14-ai-12d55e/</guid><description>Anthropic tested 14 frontier AI models in high-stakes simulations where model goals conflicted with human instructions. Here&apos;s what they found.</description><pubDate>Sun, 02 Aug 2026 00:00:00 GMT</pubDate></item><item><title>Ollama vs. LM Studio vs. llama.cpp: Which Local AI Runtime to Use</title><link>https://datasblog.com/post/ollama-vs-lm-studio-vs-llamacpp-which-local-ai-runtime--020c54/</link><guid isPermaLink="true">https://datasblog.com/post/ollama-vs-lm-studio-vs-llamacpp-which-local-ai-runtime--020c54/</guid><description>Compare Ollama, LM Studio, and llama.cpp across five key axes to find the right local AI runtime for your workflow.</description><pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Solving Large Pickup and Delivery Problems with Adaptive Large Neighborhood Search</title><link>https://datasblog.com/post/solving-large-pickup-and-delivery-problems-with-adaptiv-828461/</link><guid isPermaLink="true">https://datasblog.com/post/solving-large-pickup-and-delivery-problems-with-adaptiv-828461/</guid><description>MILP works for small routing problems, but ALNS scales further. This article applies Adaptive Large Neighborhood Search to a complex pickup-and-delivery problem</description><pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Why Predictive Model Selection Fails for Causal Effect Estimation</title><link>https://datasblog.com/post/why-predictive-model-selection-fails-for-causal-effect--8360c1/</link><guid isPermaLink="true">https://datasblog.com/post/why-predictive-model-selection-fails-for-causal-effect--8360c1/</guid><description>Optimizing for predictive fit can bias treatment effect estimates. BAC and double machine learning offer principled fixes—with important caveats.</description><pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Graph Engineering: Building Reliable AI Workflows with LangGraph</title><link>https://datasblog.com/post/graph-engineering-building-reliable-ai-workflows-with-l-9763ed/</link><guid isPermaLink="true">https://datasblog.com/post/graph-engineering-building-reliable-ai-workflows-with-l-9763ed/</guid><description>Graph engineering treats AI applications as explicitly designed workflows. Learn the core components and build a reliable LangGraph research workflow.</description><pubDate>Tue, 28 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Measuring Local LLM Energy Costs on Apple Silicon M3 Ultra</title><link>https://datasblog.com/post/measuring-local-llm-energy-costs-on-apple-silicon-m3-ul-31e74e/</link><guid isPermaLink="true">https://datasblog.com/post/measuring-local-llm-energy-costs-on-apple-silicon-m3-ul-31e74e/</guid><description>Five local LLMs measured at the wall socket on an M3 Ultra. A 120B model costs five times less per token than a 27B dense model.</description><pubDate>Tue, 28 Jul 2026 00:00:00 GMT</pubDate></item><item><title>5 Architectural Patterns for Memory and State in AI Agents</title><link>https://datasblog.com/post/5-architectural-patterns-for-memory-and-state-in-ai-age-c91280/</link><guid isPermaLink="true">https://datasblog.com/post/5-architectural-patterns-for-memory-and-state-in-ai-age-c91280/</guid><description>LLMs are stateless by design. These five architectural patterns show how to manage memory and state in production AI agents.</description><pubDate>Mon, 27 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Reducing Human Annotation Costs with Active Learning Techniques</title><link>https://datasblog.com/post/reducing-human-annotation-costs-with-active-learning-te-e70093/</link><guid isPermaLink="true">https://datasblog.com/post/reducing-human-annotation-costs-with-active-learning-te-e70093/</guid><description>Active learning selects the most informative unlabeled samples for human annotation. This tutorial covers uncertainty sampling, diversity-based sampling, and qu</description><pubDate>Mon, 27 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Stateful vs. Stateless Agent Design: Tradeoffs for Scalable Systems</title><link>https://datasblog.com/post/stateful-vs-stateless-agent-design-tradeoffs-for-scalab-36fcda/</link><guid isPermaLink="true">https://datasblog.com/post/stateful-vs-stateless-agent-design-tradeoffs-for-scalab-36fcda/</guid><description>Learn how stateless and stateful agent designs differ, and how each approach shapes memory management, scaling, and deployment architecture.</description><pubDate>Fri, 24 Jul 2026 00:00:00 GMT</pubDate></item><item><title>7 Best Claude Code Alternatives for CLI Agentic Coding</title><link>https://datasblog.com/post/7-best-claude-code-alternatives-for-cli-agentic-coding-ed573f/</link><guid isPermaLink="true">https://datasblog.com/post/7-best-claude-code-alternatives-for-cli-agentic-coding-ed573f/</guid><description>Claude Code isn&apos;t the only option for agentic CLI coding. These seven alternatives offer more model flexibility, lower costs, and stronger harnesses.</description><pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Prompt Compression Techniques for LLMs: A Practical Guide</title><link>https://datasblog.com/post/prompt-compression-techniques-for-llms-a-practical-guid-a807d0/</link><guid isPermaLink="true">https://datasblog.com/post/prompt-compression-techniques-for-llms-a-practical-guid-a807d0/</guid><description>Prompt compression reduces token usage and cost while preserving answer quality. This guide covers the main techniques and how to apply them.</description><pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate></item><item><title>10 AI Newsletters for Data Scientists and ML Practitioners</title><link>https://datasblog.com/post/10-ai-newsletters-for-data-scientists-and-ml-practition-c94cf2/</link><guid isPermaLink="true">https://datasblog.com/post/10-ai-newsletters-for-data-scientists-and-ml-practition-c94cf2/</guid><description>A curated guide to 10 AI newsletters organized by purpose: daily news, technical research, policy analysis, and builder ecosystem coverage.</description><pubDate>Wed, 22 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Adaptive Parsing: Escalating from PyMuPDF to Azure and Vision LLMs</title><link>https://datasblog.com/post/adaptive-parsing-escalating-from-pymupdf-to-azure-and-v-8bf02a/</link><guid isPermaLink="true">https://datasblog.com/post/adaptive-parsing-escalating-from-pymupdf-to-azure-and-v-8bf02a/</guid><description>Learn how a feedback loop escalates PDF parsing from cheap to deep only when needed, using LLM self-evaluation to catch silent parse failures.</description><pubDate>Mon, 20 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Backpropagation Explained for Beginners: Building the Intuition</title><link>https://datasblog.com/post/backpropagation-explained-for-beginners-building-the-in-99eea1/</link><guid isPermaLink="true">https://datasblog.com/post/backpropagation-explained-for-beginners-building-the-in-99eea1/</guid><description>A step-by-step guide to understanding backpropagation in neural networks, built on linear regression intuition and the chain rule.</description><pubDate>Sun, 19 Jul 2026 00:00:00 GMT</pubDate></item><item><title>KDnuggets Weekly Roundup: Top AI and Python Articles</title><link>https://datasblog.com/post/kdnuggets-weekly-roundup-top-ai-and-python-articles-53321f/</link><guid isPermaLink="true">https://datasblog.com/post/kdnuggets-weekly-roundup-top-ai-and-python-articles-53321f/</guid><description>This week&apos;s top picks cover LLM optimization, SQL portfolios, Git worktrees, agentic AI, and Python patterns for production-ready data workflows.</description><pubDate>Sat, 18 Jul 2026 00:00:00 GMT</pubDate></item><item><title>5 Free Resources to Learn Agentic AI</title><link>https://datasblog.com/post/5-free-resources-to-learn-agentic-ai-6b77f0/</link><guid isPermaLink="true">https://datasblog.com/post/5-free-resources-to-learn-agentic-ai-6b77f0/</guid><description>Five free resources covering agentic AI from hands-on courses to foundational theory. Build, understand, and evaluate agents that actually work.</description><pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Agentic AI Security: Defending Against Prompt Injection and Tool Misuse</title><link>https://datasblog.com/post/agentic-ai-security-defending-against-prompt-injection--8c2948/</link><guid isPermaLink="true">https://datasblog.com/post/agentic-ai-security-defending-against-prompt-injection--8c2948/</guid><description>AI agents face unique security threats like prompt injection and tool misuse. Learn five foundational defense strategies to mitigate them.</description><pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Enterprise AI Has a Context Problem, Not a Retrieval Problem</title><link>https://datasblog.com/post/enterprise-ai-has-a-context-problem-not-a-retrieval-pro-7caead/</link><guid isPermaLink="true">https://datasblog.com/post/enterprise-ai-has-a-context-problem-not-a-retrieval-pro-7caead/</guid><description>57% of enterprises have traced confident AI agent errors to bad context. RAG dominates, but the governed semantic layer to fix it isn&apos;t built yet.</description><pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate></item><item><title>How to Get the Most Out of Claude Fable 5</title><link>https://datasblog.com/post/how-to-get-the-most-out-of-claude-fable-5-faffa5/</link><guid isPermaLink="true">https://datasblog.com/post/how-to-get-the-most-out-of-claude-fable-5-faffa5/</guid><description>Claude Fable 5 has limited weekly usage. Learn how to reserve it for planning and refactoring while using other models for implementation.</description><pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Run a Local AI Model with Ollama in 15 Minutes</title><link>https://datasblog.com/post/run-a-local-ai-model-with-ollama-in-15-minutes-38f5d3/</link><guid isPermaLink="true">https://datasblog.com/post/run-a-local-ai-model-with-ollama-in-15-minutes-38f5d3/</guid><description>Install Ollama, download a small language model, and run private AI inference on your own hardware in three straightforward steps.</description><pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate></item><item><title>7 Python Frameworks for Orchestrating Local AI Agents</title><link>https://datasblog.com/post/7-python-frameworks-for-orchestrating-local-ai-agents-a45113/</link><guid isPermaLink="true">https://datasblog.com/post/7-python-frameworks-for-orchestrating-local-ai-agents-a45113/</guid><description>Seven Python tools engineers are using in 2026 to build and run AI agents on local infrastructure, from model runtimes to full orchestration frameworks.</description><pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Enterprise AI Has an Orchestration Gap, Not a Platform Problem</title><link>https://datasblog.com/post/enterprise-ai-has-an-orchestration-gap-not-a-platform-p-dc3158/</link><guid isPermaLink="true">https://datasblog.com/post/enterprise-ai-has-an-orchestration-gap-not-a-platform-p-dc3158/</guid><description>Most enterprise &quot;agents&quot; are still chatbot wrappers. A new survey of 101 firms reveals a wide gap between orchestration ambition and deployed reality.</description><pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Meta-Prompting: How to Use AI to Design Better Prompts</title><link>https://datasblog.com/post/meta-prompting-how-to-use-ai-to-design-better-prompts-f446ee/</link><guid isPermaLink="true">https://datasblog.com/post/meta-prompting-how-to-use-ai-to-design-better-prompts-f446ee/</guid><description>Meta-prompting asks a model to design reusable prompts before completing a task. It improves consistency, scalability, and output quality.</description><pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Local Video Summarization Pipeline Using SmolVLM2-2.2B</title><link>https://datasblog.com/post/local-video-summarization-pipeline-using-smolvlm2-22b-f05e60/</link><guid isPermaLink="true">https://datasblog.com/post/local-video-summarization-pipeline-using-smolvlm2-22b-f05e60/</guid><description>Build a local video summarization pipeline using SmolVLM2-2.2B. Runs on consumer GPUs with 5.2 GB VRAM, no cloud API required.</description><pubDate>Fri, 10 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Running OpenClaw with Ollama: A Complete Setup Guide</title><link>https://datasblog.com/post/running-openclaw-with-ollama-a-complete-setup-guide-2776d2/</link><guid isPermaLink="true">https://datasblog.com/post/running-openclaw-with-ollama-a-complete-setup-guide-2776d2/</guid><description>OpenClaw bridges local Ollama models to messaging apps like WhatsApp and Telegram. This guide covers installation, context configuration, and Docker deployment.</description><pubDate>Thu, 09 Jul 2026 00:00:00 GMT</pubDate></item><item><title>DeepSeek DSpark: Semi-Autoregressive Speculative Decoding Explained</title><link>https://datasblog.com/post/deepseek-dspark-semi-autoregressive-speculative-decodin-ebf4a5/</link><guid isPermaLink="true">https://datasblog.com/post/deepseek-dspark-semi-autoregressive-speculative-decodin-ebf4a5/</guid><description>DeepSeek&apos;s DSpark module boosts LLM generation speed 60–85% by combining parallel drafting with lightweight sequential correction.</description><pubDate>Wed, 08 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Data Scientists Are Becoming AI Managers, Not Model Builders</title><link>https://datasblog.com/post/data-scientists-are-becoming-ai-managers-not-model-buil-930788/</link><guid isPermaLink="true">https://datasblog.com/post/data-scientists-are-becoming-ai-managers-not-model-buil-930788/</guid><description>Data scientists at AI-driven companies now spend more time on oversight and system supervision than model building, as 2025–2026 job data confirms.</description><pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate></item><item><title>I Replaced My LLM Wiki With a Pure Python Compiler</title><link>https://datasblog.com/post/i-replaced-my-llm-wiki-with-a-pure-python-compiler-fbed1d/</link><guid isPermaLink="true">https://datasblog.com/post/i-replaced-my-llm-wiki-with-a-pure-python-compiler-fbed1d/</guid><description>A pure Python pipeline that compiles messy text notes into a linked, linted markdown wiki — no LLM calls, no embeddings, no external APIs.</description><pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Large Action Models vs Agentic LLMs: A Practical Comparison</title><link>https://datasblog.com/post/large-action-models-vs-agentic-llms-a-practical-compari-0587f0/</link><guid isPermaLink="true">https://datasblog.com/post/large-action-models-vs-agentic-llms-a-practical-compari-0587f0/</guid><description>LAMs and agentic LLMs both take actions, but differ fundamentally in how. Learn which to use and when.</description><pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate></item><item><title>Claude Sonnet 5: Anthropic&apos;s Free Default Model Built for Agentic Tasks</title><link>https://datasblog.com/post/claude-sonnet-5-anthropics-free-default-model-built-for-e9b72d/</link><guid isPermaLink="true">https://datasblog.com/post/claude-sonnet-5-anthropics-free-default-model-built-for-e9b72d/</guid><description>Anthropic releases Claude Sonnet 5 as the free default model for all users, with stronger agentic capabilities, lower API costs, and improved reliability.</description><pubDate>Tue, 30 Jun 2026 00:00:00 GMT</pubDate></item><item><title>Context Engineering for RAG: The Four Typed Inputs Behind Every Answer</title><link>https://datasblog.com/post/context-engineering-for-rag-the-four-typed-inputs-behin-3d69de/</link><guid isPermaLink="true">https://datasblog.com/post/context-engineering-for-rag-the-four-typed-inputs-behin-3d69de/</guid><description>Context engineering reframes how RAG pipelines work. Each brick emits typed pieces that converge on a single LLM call.</description><pubDate>Tue, 30 Jun 2026 00:00:00 GMT</pubDate></item><item><title>5 AI Coding Subscription Plans That Offer Developers the Best Value</title><link>https://datasblog.com/post/5-ai-coding-subscription-plans-that-offer-developers-th-b46edb/</link><guid isPermaLink="true">https://datasblog.com/post/5-ai-coding-subscription-plans-that-offer-developers-th-b46edb/</guid><description>AI coding platforms are moving away from &quot;unlimited&quot; plans. Here are five token, credit, and quota-based subscriptions worth the price.</description><pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate></item><item><title>Classical NLP for Spooky Author Identification: From Bag-of-Words to Stacking</title><link>https://datasblog.com/post/classical-nlp-for-spooky-author-identification-from-bag-6607e8/</link><guid isPermaLink="true">https://datasblog.com/post/classical-nlp-for-spooky-author-identification-from-bag-6607e8/</guid><description>A step-by-step exploration of classical NLP methods—from Vowpal Wabbit baselines to stacked ensembles—applied to Kaggle&apos;s Spooky Author Identification task.</description><pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate></item><item><title>GraphRAG vs Vector RAG: A Practical Comparison for Retrieval Systems</title><link>https://datasblog.com/post/graphrag-vs-vector-rag-a-practical-comparison-for-retri-acee84/</link><guid isPermaLink="true">https://datasblog.com/post/graphrag-vs-vector-rag-a-practical-comparison-for-retri-acee84/</guid><description>GraphRAG and Vector RAG serve different retrieval needs. This guide breaks down their architectures, query handling, and when to use each.</description><pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate></item><item><title>Model Context Protocol Explained in 3 Levels of Difficulty</title><link>https://datasblog.com/post/model-context-protocol-explained-in-3-levels-of-difficu-f52d1b/</link><guid isPermaLink="true">https://datasblog.com/post/model-context-protocol-explained-in-3-levels-of-difficu-f52d1b/</guid><description>MCP standardizes how AI apps connect to external tools. Learn the architecture, request flow, and production security considerations.</description><pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate></item></channel></rss>