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22 guides~2.0 hrs totalupdated Jul 6, 2026

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Designing AI-Native Applications: The Architecture Series

AI-native applications break classic architecture instincts. This 8-part series maps the decisions that matter: context, memory, orchestration, governance.

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BeginnerCDNs and Object Storage: Store at the Origin, Serve at the Edge (2026)CDNs and object storage explained in 2026 — object storage as the origin for large files, CDNs as the edge cache near users, how they work together, and what they store in AI systems.5 min BeginnerRate Limiting Explained: Token Bucket, Leaky Bucket, and When Each Wins (2026)Rate limiting explained in 2026 — fixed window, sliding window, token bucket, and leaky bucket, which algorithm to default to, and why LLM traffic is limited by tokens rather than requests.5 min BeginnerHorizontal vs Vertical Scaling: Scale Up Until You Can't (2026)Horizontal vs vertical scaling in 2026 — scale up (a bigger box) versus scale out (more boxes), the hardware ceiling, why horizontal needs statelessness, and the diagonal middle ground.5 min BeginnerCAP Theorem Explained: It Was Never 'Pick Two' (2026)CAP theorem explained in 2026 — why 'pick two of three' is wrong, the real consistency-vs-availability choice during a partition, PACELC, and what it means for AI systems.5 min BeginnerEvent-Driven Architecture: Trading Control for Decoupling (2026)Event-driven architecture explained in 2026 — events vs commands, choreography vs orchestration, and the real trade-off: you gain decoupling and lose the single view of what happens next.5 min BeginnerAPI Gateway Explained: It's Not a Load Balancer (2026)API gateway explained in 2026 — what it actually does (auth, rate limiting, routing, aggregation), why it's not a load balancer, and where the new AI gateway fits.4 min BeginnerSQL vs NoSQL: It's About Access Patterns, Not Scale (2026)SQL vs NoSQL in 2026 — why the real choice is about access patterns and correctness, not scale; the four NoSQL types; and why most systems end up using both.5 min BeginnerLoad Balancers Explained: Health Checks Do the Real Work (2026)Load balancers explained in 2026 — L4 vs L7, the algorithms, and why health checks (not even distribution) are the part that actually keeps you online.5 min BeginnerSystem Design Building Blocks: A Decision Map, Not a Parts List (2026)System design building blocks explained as a decision map — the five questions that pick your components (architecture style, cache, message broker, database, load balancer) and how each block earns its place.6 min BeginnerCaching Strategies: Why Invalidation Is the Hard Part (2026)Caching strategies in 2026 — the patterns (cache-aside, write-through, write-behind), eviction policies, and why cache invalidation, not adding a cache, is the genuinely hard part.7 min BeginnerKafka vs RabbitMQ: A Log vs a Queue, Not Fast vs Slow (2026)Kafka vs RabbitMQ in 2026 — why it's a log versus a queue (not fast versus slow), the differences that matter, and when each one (or both) is the right call.7 min BeginnerMonolith vs Microservices: It's About Team Size, Not Traffic (2026)Monolith vs microservices in 2026 — the differences that matter, why team size (not traffic) decides it, and when to start with a modular monolith.7 min AI Gateway Design: One Front Door for Every Model (2026)AI gateway design: one front door for every LLM call — routing, fallback, caching, cost control, and guardrails. What belongs in one, and when you need it.8 min IntermediateAgent Mesh vs Supervisor: What Holds Up in ProductionAgent mesh vs supervisor: why 2026 production data favors bounded supervisor coordination over open agent meshes, and when a controlled mesh still earns its keep.6 min IntermediateAgent Orchestration Patterns: A 2026 GuideAgent orchestration patterns: supervisor, hierarchical, sequential, parallel, swarm — which wins in 2026, what it costs, and when one agent is enough.5 min IntermediateAI Control Plane Architecture: A 2026 GuideAI control plane architecture: the governance layer over your agents — identity, policy, observability, cost, and audit — and when you actually need one.5 min IntermediateHuman-in-the-Loop Architecture: A 2026 GuideHuman-in-the-loop architecture for AI agents: approval gates, interrupt and resume, calibrated autonomy, the approval-fatigue trap, and where to put the human.5 min IntermediateLong-Running AI Workflows: A 2026 GuideLong-running AI workflows: why request/response breaks, how durable execution resumes instead of restarting, idempotency, and when to skip it.5 min IntermediateAI Agent Memory Architecture: A 2026 GuideAI agent memory for architects: the three long-term types, the write-recall-forget lifecycle, where it breaks, and when an agent needs no memory at all.6 min IntermediateAI Agents vs Microservices: An Architect's Guide (2026)AI agents vs microservices: the six differences that matter — determinism, state, contracts, retries, testing, cost — and when an agent is the wrong tool.6 min IntermediateContext Engineering Architecture: A 2026 GuideContext engineering for architects: treat the context window as RAM on a token budget — what fills it, where it breaks, and when a plain prompt wins.5 min

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