AJAlen Joyinpragmaticstack.in00In Probabilistic Systems, You Watch the Shape of Success2h ago · 18 min read · 🗓️ Last updated June 2026. Field names and stability levels track the still evolving OpenTelemetry GenAI semantic conventions; check them against the official spec on GitHub before adoption. There'sJoin discussion
EIEshan Inamdarineshaninamdar.hashnode.dev00Agentic AI Deep Dive — Evaluation & Production2d ago · 12 min read · Where We Left Off Part 8 was about failure modes — the six ways agents break in production without anyone trying to break them. Infinite loops. Hallucinated tool calls. Silent failures. Context poisonJoin discussion
SDSwapnil Dhimaninswapnildhiman.hashnode.dev10iOS Engineer to AI Engineer3d ago · 8 min read · I'm betting eight months of my life on this plan. In May 2026, I decided to stop being "the iOS engineer who's curious about AI" and become an AI Engineer. I'm giving myself roughly 8 months — from MaJoin discussion
AJAlen Joyinpragmaticstack.in10Reasoning Is Cheap, Side Effects Are Forever5d ago · 15 min read · 🗓️ Last updated: June 2026. Reflecting current tool use patterns and saga based agent architectures. There's a quiet failure mode buried in every agentic system that touches the real world: The agenJoin discussion
POPrecious Obinnainprecious-o.hashnode.dev20How I cached intention, not queries6d ago · 3 min read · While building a project for a client recently, the system runs an LLM pipeline with multiple LLM calls. I ran into 2 obvious problems — latency and high token usage. I needed a way to kill both birdsJoin discussion
MMMarco Mornatiinblog.mornati.net00Your AI Agent Deserves a Tool Harness, Not a Wild WestMay 31 · 14 min read · We started the same way everyone does: give the LLM access to everything and hope it figures it out. Connect the GitHub MCP, the Jira MCP, the internal product API MCP, throw in a database schema or tJoin discussion
PKPrashant Koiralainblog.prashantkoirala.info.np10Vector databases are not always the answerMay 31 · 22 min read · Vector databases became one of the default answers to almost every AI product question. Building a chatbot over your documents? Use a vector database. Building semantic search? Use a vector database. Join discussion
SMScott McMahaninaitransformeronline.hashnode.dev10Multi-Agent AI Systems Are Changing AI DevelopmentMay 27 · 2 min read · AI development is entering a new phase where single-model applications are no longer enough for many real-world use cases. Multi-agent systems are becoming one of the most important architectural pattJoin discussion
SKSunil Kumarinsunil-kumaar.hashnode.dev00How Multi-Agent AI Systems Are Replacing Traditional Dev Teams in 2026May 27 · 6 min read · Introduction Three years ago, GitHub Copilot felt revolutionary. It autocompleted your functions and saved you a few keystrokes. Today, that feels like the Stone Age. In 2026, the shift isn't about beJoin discussion
DBDnyandeo Bharambeinmcpoverrag.hashnode.dev10Why I chose MCP over RAG for live infrastructure auditingMay 26 · 6 min read · I've been working on a project to audit distributed hardware infrastructure — devices spread across multiple sites, each running firmware that needs to stay compliant with a central policy. Pretty staJoin discussion
