what groundy covers
Long-form analysis on developer tools, AI infrastructure, and the platforms shaping how software gets built. Comparisons, benchmarks, routing guides, and the pricing and regulatory shifts landing on working teams. Published most days, every claim cited to a public source.
the beats
Nine coverage areas. Each links to its full archive.
Agents & FrameworksIndependent comparisons of agent stacks and multi-agent designs, tracking the gap between framework marketing and the failure modes that show up under real workloads.Models & ResearchWhere architecture, training tricks, and eval methodology meet the marketing layer — separating durable progress in foundation models from leaderboard theater that quietly falls apart under load.Infrastructure & RuntimeThe serving stack, network fabric, and cloud-account substrate beneath production AI, where every throughput claim collides with rebuild windows, egress invoices, and control-plane risk.Developer ToolsThe economics, interop standards, and workflow tradeoffs reshaping how code gets written, reviewed, and shipped when AI agents share the editor with the engineer.Industry & BusinessThe money, power, and labor decisions reshaping who controls AI infrastructure, who pays for it, and which incumbents the buildout dislodges or entrenches over the next decade.Ethics, Policy & SafetyWhere AI safety claims collide with reproducible measurement, where training-data harvesting collides with consent, and where deployment outruns the laws and norms meant to constrain it.SecurityWhere AI infrastructure inherits the unpatched assumptions of the web stack beneath it, and trust boundaries collapse faster than disclosure timelines can keep up.Open SourceWhere source availability, license fine print, and project survival collide — separating open-weight theater from software you can actually fork, audit, and outlive.Culture & SocietyWhere law, labor, and culture push back on machines that scrape, surveil, displace, and addict faster than institutions can write rules for them.
popular right now
Most-read over the last six days, ranked by pageviews.
- 1modelsGLM-5.2 Benchmarks: What 62.1% SWE-bench Pro and 99.2% AIME Actually Mean52
- 2modelsChinese AI Models Compared: DeepSeek, Qwen, Kimi, Doubao, and Ernie48
- 3industryStargate: Inside OpenAI's $100B Infrastructure Buildout33
- 4infraMLX vs llama.cpp on Apple Silicon: Which Runtime to Use for Local LLM Inference32
- 5modelsGLM-5.2 on Terminal-Bench 2.1: Strengths, Gaps, and How to Route Real Coding Tasks13
- 6policyAtlassian Turned On AI Training Data Collection by Default: Here's What to Disable11
- 7modelsDeepSeek V3/R1: How Chinese Engineers Matched GPT-4 for $6 Million11
- 8devtoolsClaude Code in GitHub Actions: A Complete Guide to Automated PR Fixes11
- 9infraRunning GLM-5.2 at Home: SGLang, vLLM, Transformers, and KTransformers Setup Guide9
- 10cultureEU's 2027 Replaceable Battery Mandate: What It Means for Phone Buyers and Repairers Right Now9
Browse the full archive on the articles page.