PinnedUdaykiran Estari·Jul 31New Here? Start Here: My Complete AI, Claude Code & Agent Engineering LibraryAll my guides, tutorials, and deep dives — organized by what you want to learnA response icon4A response icon4
PinnedInData Science CollectivebyUdaykiran Estari·Jul 3Stop Wasting LLM Tokens: Building a Self-Updating Codebase Knowledge Graph with OKFGoogle's new Open Knowledge Format (OKF) standardizes context. Here's how to build a pipeline to keep your codebase memory self-updating.A response icon27A response icon27
PinnedInTowards AIbyUdaykiran Estari·Jul 22Graphify, OKF, or Both? Beyond RAG for CodebasesGraphify’s own benchmark file quietly admits what its 60,000-star hype cycle won’t: on head-to-head QA accuracy, it ties dense vector RAG…A response icon11A response icon11
PinnedInTowards AIbyUdaykiran Estari·Jul 15Superpowers 6.0 Unpacked: Faster AI Code Review and Fewer TokensDoes subagent-driven development actually work? We break down the Superpowers 6.0 release, its costs, and the limits of context…A response icon1A response icon1
PinnedInTowards AIbyUdaykiran Estari·Jul 16Beyond the 71x Benchmark: Knowledge Graphs for Coding Agents : Graphify and Rivals ComparedCut through the marketing hype. Learn the real tradeoffs between Graphify, CodeGraph, and agentic grep for Claude Code and Codex.A response icon2A response icon2
Udaykiran Estari·11h agoThe Microsoft Outage: How One Jammed Step Took Down Outlook and TeamsWhat actually broke on 12 November 2026, explained in plain words.
InData Science CollectivebyUdaykiran Estari·4d agoThe AI BubbleTwo market shocks in under two years, one pattern: how to read an “AI bubble bursts” headline by separating the price of AI companies from…A response icon1A response icon1
InData Science CollectivebyUdaykiran Estari·6d agoDid AI Just Solve an ‘Impossible’ Problem?What the Exponential Time Hypothesis is, why computer scientists treated it as a wall for 27 years, and how an AI model claims to have…A response icon1A response icon1
InLevel Up CodingbyUdaykiran Estari·6d agoAttention Weights at Scale, Explained Visually (Part 2)Why attention work grows with the square of your prompt, how models avoid redoing it for every new word, and what that means for speed and…A response icon1A response icon1
InData Science CollectivebyUdaykiran Estari·Nov 5Attention Weights, Explained Visually (Part 1)What attention weights are, how a model computes them in four small steps, and why every word in your prompt is competing for a share of…A response icon1A response icon1
