#ai
17 articles
Model Context Protocol (MCP) and Tool-Use Infrastructure
How MCP lets any LLM host discover and call any tool server — collapsing N×M integrations to N+M, with the security, reliability, and token math that matters.
Design an LLM Observability Platform
Design an LLM observability platform: distributed tracing for multi-step LLM apps capturing every prompt, token count, and cost to debug failed agent runs.
Design an LLM Gateway (AI Gateway & Model Router)
Design an LLM gateway: one proxy in front of every model provider, with automatic failover, semantic caching, per-team budgets, and SSE streaming under 50 ms.
Design an LLM Fine-Tuning Platform
Design an LLM fine-tuning platform: dataset ingestion, LoRA/QLoRA/DPO training, fault-tolerant GPU scheduling, eval gating, and multi-LoRA serving.
Design an LLM Evaluation Platform
Design an LLM evaluation platform: offline eval with LLM-as-judge, CI regression gating, online production sampling, and human annotation at 450M evals/month.
Design a GraphRAG System (Knowledge-Graph-Augmented Retrieval)
When vector RAG fails on multi-hop and corpus-wide questions, build a GraphRAG knowledge graph: entity extraction, Leiden communities, map-reduce global search.
Design a Feature Store
Serve identical feature values to model training and online inference, eliminating training-serving skew at sub-10ms latency and millions of reads per second.
Design an Intelligent Document Processing Pipeline
Design a pipeline that turns millions of messy PDFs into validated structured JSON: OCR, LLM extraction, confidence routing, and build-vs-buy cost math.
Design a Customer-Support AI Assistant
Design a production customer-support AI that deflects 40–60% of tickets with RAG, real-action tools, guardrails, and human handoff — hallucination under 2%.
Design a Realtime Voice AI Agent
Design a realtime voice AI agent for PSTN and WebRTC calls with sub-800ms voice-to-voice latency: cascade STT-LLM-TTS pipeline, turn detection, barge-in.
Design an AI Guardrails & Safety System
Design an AI guardrails system that wraps every LLM call — blocking prompt injections, redacting PII, and catching toxic output — inside a 200 ms budget.
Design an AI Coding Assistant (Copilot / Cursor)
Design an AI coding assistant: sub-200ms ghost-text completions plus an autonomous multi-file agent — the two-product architecture behind Copilot and Cursor.
The ML / GenAI System Design Interview Framework
A 7-step, 45-minute framework for the ML and GenAI system design interview — from metric mapping and the feedback loop to the RAG-vs-fine-tune decision tree.
Design a Vector Database / Semantic Search Service
Index 1 billion 768-dimensional vectors and answer top-k similarity queries in under 20 ms — the ANN indexing, sharding, and filtering architecture behind Pinecone, Weaviate, and pgvector.
Design a RAG (Retrieval-Augmented Generation) Pipeline
Design a RAG pipeline that grounds an LLM in 10M documents with sub-2-second, cited answers: ingestion, hybrid retrieval, reranking, generation, and eval.
Design an LLM Inference & Serving System
Serve token generation for a 70B-parameter model at scale — where KV cache, not FLOPs, caps concurrency and continuous batching is what separates good GPU utilization from terrible utilization.
Design an AI Agent Platform
Design an AI agent platform: durable checkpointed runs, idempotent tool calls, tiered memory, and per-tenant safety guardrails around an unreliable LLM core.