Algomi Blogs

System design, AI engineering, databases, networking, concurrency and more, written for engineers building real trading and fintech systems — part of the Algomi Suite.

All System Design AI Solutions Architecture & AI Engineering Interview Questions (61)

Browse by topic (29)

AI Engineering (7)Java (7)Distributed Systems (6)Reliability (6)Security (6)AI Agents (5)Caching (5)Concurrency (4)Databases (4)Low-Level Design (4)Messaging (4)Networking (4)Streaming (4)APIs (3)Architecture (3)Consistency (3)Design Patterns (3)Harness Engineering (3)Observability (3)RAG (3)Transactions (3)Agent Memory (2)Capacity Planning (2)Enterprise Architecture (2)Fintech (2)Kafka (2)Machine Coding (2)Storage (2)Tool Use (2)

Part 2 of 2

Algomi Architecture, Part 2: Trading, Insights, Charts, Career, and the AI Guardrails

How a Telegram message becomes a broker order, why recommendations refuse to guess, and how one doorway keeps personal data away from third-party AI models.

Created 2026-09-26 · Updated 2026-10-15 · System Design

Enterprise MCP Gateway: One Front Door for Thousands of AI Agent Tools

Why a company with hundreds of MCP servers needs a gateway, and how a control plane, a data plane, tool-level authorization, progressive discovery and response projection work, using Uber's published MCP Gateway as a case study.

Created 2026-10-04 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering

Multi-Tenant RAG: Retrieving the Right Answer from the Right Customer

How to stop one company's documents leaking into another company's answers: tenant isolation at ingestion, retrieval, context assembly and caching, and how to choose between a shared index, namespaces and dedicated indexes.

Created 2026-10-04 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering

Agent Architecture: Designing AI Systems That Take Actions, Not Just Answers

The agent loop, designing tools the model can actually use correctly, reactive versus planned execution, memory and compaction, multi-agent orchestration, and the guardrails that keep an acting AI safe.

Created 2026-09-18 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering

LLM Serving and Inference Cost: What Actually Determines Latency and Price

Why a demo that works for one user can collapse at scale — prefill vs. decode, the KV cache, continuous batching, PagedAttention, quantization, caching, and a worked cost estimate.

Created 2026-09-18 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering

RAG System Design: How to Ground an AI's Answers in Your Own Data

Why a fluent AI answer can still be wrong — chunking, embeddings, hybrid search and reranking, and when retrieval beats fine-tuning or a bigger context window.

Created 2026-09-18 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering

AI Evals and Observability: How to Check Whether an AI Actually Works

Why a fluent AI answer isn't proof of success — evals, traces, groundedness, graders, and the release checks that catch failures a good average score would hide.

Created 2026-09-16 · Updated 2026-10-15 · AI Solutions Architecture & AI Engineering