ASAditya Sethinadityaseth777.hashnode.dev·4d ago · 26 min readDebugging Silent Model Divergence with Gradient MonitoringYour loss curve looks like a masterpiece of engineering because it plunges beautifully toward zero every single epoch. It is gorgeous. But beneath that smooth line, your model's internal math might be22K
MKMohit Kumarinmohitkumar1.hashnode.dev·Jul 27 · 8 min readI Built a Security Stack for AI Agents — Here's the ArchitectureAuthor: Mohit KumarProject: Bulwark – An open-source security stack for AI agentsGitHub: mk12002/Bulwark This article is part of the Bulwark series, where I explore practical approaches to securing AI00
ASArfaat Shaikhinapexcraftbyarfaat.hashnode.dev·Jul 10 · 9 min readFace Detection Login SystemThis document covers the complete implementation of a biometric face detection login system built inside Oracle APEX 24.2. The system replaces or supplements the standard username/password login with 00
GBGracie Boltonincontain.hashnode.dev·Jun 25 · 6 min readNLP Models Are Becoming the Engine Behind Smarter PlatformsHow natural language processing is quietly reshaping the way people interact with digital products Modern users don't just want software that works. They want platforms that understand them — tools th00
KSKanishka Shashiinnodej.hashnode.dev·Jun 23 · 10 min readModern Database Access: Prisma, Drizzle, and ORMs ExplainedWhere Does Application Data Live After a User Closes the App? Imagine you're using an e-commerce application. You create an account, add products to your cart, place an order, and close the app. The n00
SSangharshainnoob6t5.hashnode.dev·Jun 11 · 4 min readPickle Deserialization RCE via Model Upload EndpointLink: https://www.ratctf.com/challenges/synapse-lab This challenge revolves around a classic but still heavily abused primitive: unsafe Python pickle deserialization exposed through a model upload API00
KMKartik Mehtainwriter.mrmehta.in·Jun 5 · 8 min readAgent = Model + HarnessIf you have ever called an LLM API, you already know the basic shape of it. You send some text, you get some text back, and the connection closes. That is a model. It is good at producing language, bu00
KMKartik Mehtainwriter.mrmehta.in·Jun 5 · 8 min readLetting Agents Run, SafelyPart three of a series on agent harnesses. Part one introduced the model-plus-harness idea, and part two split work across subagents. This piece is about the layer where agents stop just talking and s00
KMKartik Mehtainwriter.mrmehta.in·Jun 5 · 7 min readOne Agent Is Not Always EnoughPart two of a series on agent harnesses. If you have not read part one, it introduces the idea that an agent is a model plus the harness around it. This piece builds on that, so a quick skim first wil00
AAArjun Adhikariinblogs.thearjun.com·Jun 2 · 11 min readHow Temperature, Top‑K, and Top‑P Control LLM Output — A Practical GuideWhen an LLM generates text, it isn't thinking in sentences. It computes a massive list of raw scores (logits) for its entire vocabulary, converts them into a probability distribution, and selects the 00
