RRajshreeinrjshree.hashnode.dev·7h ago · 26 min readAI Agents Don't Need More Intelligence. They Need Better Architecture.Author: RAJश्री | Software Engineer & Full Stack Developer |AI Researcher | Founder, Shree Labs Introduction: The Intelligence Trap There is a common assumption in the current AI industry: If we mak00
RRYNAUTinrynaut.hashnode.dev·6d ago · 5 min readGoogle’s Own SRE Book Explains Why Your Incident-Response AI Should Never Touch the PagerAt 3 AM, an alerting system isn’t a dashboard — it’s the one thing standing between a degraded service and an unattended outage. So it’s no surprise that incident response looks like an obviously good01L
RRYNAUTinrynaut.hashnode.dev·Aug 9 · 6 min readNetflix Solved Adaptive Rate Limiting With TCP Congestion Control. Not With a Model.Rate limiting looks like exactly the kind of decision that should belong to a model. A static limit — some fixed number of concurrent requests — is genuinely bad, and bad in a specific way: it needs c00
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 24 · 3 min readWhere your MCP server runs is a production decisionA local MCP server starts as a script on one laptop. Someone finds it useful. Six weeks later four people depend on it, it holds a long-lived database credential, and nobody has ever looked at a log. 40
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 23 · 2 min readWhat the MCP protocol actually standardisesMost teams meet MCP as a config block they paste into an app. It works immediately, and that tends to be the end of the thinking. Then someone asks who owns the connector, and the room goes quiet. MCP00
SMScott McMahaninaitransformeronline.hashnode.dev·Jul 22 · 4 min readWhy AI Orchestration MattersModern AI systems rarely rely on a single model or application. Businesses increasingly combine language models, AI agents, databases, APIs, retrieval systems, automation platforms, and human approval00
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 20 · 3 min readDay 60: From model demos to mission-ready AI systemsSixty days ago this series started with one claim: AI is a system, not a model. Here is the map that claim produces, and the question each layer has to answer before it is production-ready. Layer T00
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 19 · 3 min readDay 59: Why production AI is coordinated infrastructureInventory what a production AI system actually runs, and the model turns out to be one component among a dozen. Model routing, so the right model handles each task and fallbacks exist when one is degr00
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 19 · 3 min readDay 58: Why governance belongs in the architectureRun this test on any AI system you have in production: ask who owns it. A name, not a team, a person who answers when it misbehaves. If the room goes quiet, that system has an architecture gap. It jus00
VKVamsi Krishnainblog.vamsiannamreddy.com·Jul 15 · 3 min readDay 53: Why handoffs need contractsAudit a failed multi-agent run and the defect is rarely inside an agent. It is between them — at a handoff, where context the sender held never reached the receiver, which then did something perfectly01A
