IInternals DecodedSep 10 · 12 min readChain of Thought: When Thinking Out Loud HelpsChain-of-thought prompting tells a language model to generate explicit intermediate reasoning steps before the final answer. Internally, this aligns inference with the training data’s step-by-step expinternals-decoded.hashnode.dev
SSushanth KamabathulaSep 1 · 2 min readOCR Gives You Eyes, Not a BrainWhy reading text off a page and understanding what that text means turned out to be two completely different problems. I went into a course on document extraction assuming modern OCR was basically an blundersnbuilds.hashnode.dev
KKavya Sree KammariAug 4 · 10 min readThe Pattern Your Brain Solved in 2 Seconds — Here's How AI Does ItOkay, can you solve this? Take a second. Look at the sequence. Where does the dot go next? Got it? Cool. How did you do that? You didn't write rules. You didn't say "the dot was top-left, then top-r1techmyway.hashnode.dev
MminhleducAug 1 · 9 min readFrom Retrieval to Memory: The Graph Your Agent Writes ToPart 3 of 3 — Knowledge Graphs for AI Engineers. Part 1 covered why vector search hits a ceiling. Part 2 covered building the graph and what it costs. This one is about the shift that actually changed1minhleduc.hashnode.dev
VVasilisJul 18 · 13 min readSyllogism Machines: Why Logic Was the First AI — And Why It FailedThe first AI program proved theorems in 1956. Seventy years later, we're still building syllogism machines — bigger, faster, more eloquent. They still don't think. The first artificial intelligence pdaimones.hashnode.dev
TTonik MappJul 3 · 2 min readAI Operating Systems: The Next Force Multiplier Every generation is lucky enough to experience a major technology evolution. For one generation, it was the personal computer. For another, it was the internet. The latest one is AI. Each evolution femaptonik.hashnode.dev
MMuhammad Azlaan ZubairJun 18 · 3 min readIs Overthinking a Red Flag? We Put AI Reasoning to the Test.More Thinking Doesn't Always Mean Better Answers Reasoning models are designed to think step by step, and the common assumption is simple: More thinking = better results. I expected reasoning models2Aletinix.hashnode.dev
EEshan InamdarMay 15 · 11 min readAgentic AI Deep Dive — How Agents ThinkWhere We Left Off In Part 2 we opened the hood. Every agent — regardless of framework — has five core components: LLM, planner, executor, tools, and memory. The harness manages the loop between them. eshaninamdar.hashnode.dev
OOwenMay 9 · 10 min readClaude Opus 4.6 vs GPT-5.5 vs Gemini 3.1 Pro: Reasoning Benchmarks (3 Real Tasks Tested)Claude Opus 4.6 vs GPT-5.5 vs Gemini 3.1 Pro: Reasoning Benchmarks (3 Real Tasks Tested) TL;DR — On three reasoning tasks (legal contradiction analysis, multi-step proof, nested-spec planning), Claude Opus 4.6 produced the most rigorous step-by-step ...owenf.hashnode.dev
PPedro EugenioApr 27 · 4 min readThe Private LanguageTwo papers dropped this week that fit together like diagnosis and experiment. One counts what's broken. The other tries to fix it in a way nobody expected. Start with the numbers. A new study analyzed token consumption across eight frontier models on...1theweeklyprompt.news
