Tag: Architecture Patterns

An engineering analysis of Target's lexical and vector retrieval, attribute controls, weighted interleaving, and the evidence limits behind its reported gains.

A practical look at how Cloudflare Turnstile Spin installs, repairs, or migrates a widget with human approval, while Siteverify, credential isolation, and replay testing close the server-side security loop.

A focused engineering reading of Ouroboros v7.4.4: how durable identity, memory, self-modification, and managed subagents can be connected to SHA256, SBOMs, GitHub build provenance, and smoke receipts before deployment.

A focused engineering reading of RSIAgent's curriculum, actor, verifier, and broad-to-deep exploration loop, with a careful audit of frozen experience, benchmark reporting, and reproducibility limits.

A systems reading of AWS's Unified Knowledge Graph RAG reference stack: how GraphRAG and LightRAG share ingestion, graph, hybrid retrieval, and lineage infrastructure while selecting a query strategy per question.

A practical control boundary for multi-agent workflows: separate AgentCore proposals from deterministic validation, human approval, idempotent execution, and durable audit history in Step Functions.

One diagram shows how CoT and WebGPT merge into ReAct, then connects Gorilla and IPI to the rest of the agent-systems reading path.

One diagram shows how DPR and Lewis RAG connect to the retrieval papers already on this site.

A copyable Agentic platform contract: what the platform provides, what projects must wire (E·P·J·T), seven non-bypass rules, and where the IT 100-question evidence stops.

An architectural deep dive into Cloudflare's proposed Agentic Internet framework, spanning Web Bot Auth, Markdown for Agents, WebMCP browser tool exposure, and x402 micro-payments.

GPU memory topologies, server budgets, 3-phase power, liquid cooling, and a five-stage TCO framework for on-premises Kimi-K3 2.8T MoE deployment. Focuses on datacenter procurement—not the 80× RTX 5090 consumer GPU cluster path.

Hardware topology, why 44 GPUs fall short, build costs, and power estimates for running Kimi-K3 2.8T MoE on an 80× RTX 5090 consumer GPU cluster. Focuses on the consumer-card proof-of-concept—not enterprise datacenter TCO.

Reads the architecture layer of GPT-5.6 technical docs: Frontier Intelligence, intelligence per token, kernels, and harness routing. Architecture—not the Sol price sheet.

A comparison of how open-weight models such as DeepSeek V3, Gemma 3, and Kimi K2 use MLA, MoE, GQA, and sliding-window attention to trade off quality, KV cache, throughput, and deployment complexity.

A practical guide to agents versus workflows, single- and multi-agent architecture, tools and MCP, state and memory, evaluation, security, and the path from PoC to production.

A practical framework for enterprise RAG data pipelines, hybrid search, reranking, GraphRAG, agentic RAG, evaluation, access governance, failure diagnosis, and operations.

A summary of the AWS × HoyaBit session: the four major pain points of Enterprise Agentic AI, the Amazon Bedrock AgentCore (Runtime/Memory/Gateway/Governance) technology stack, and how Taiwan's FSC-compliant exchange pushed their voice-trading Agent and enterprise brain platform into production.

A source-bounded review of Pocketpair's Palworld persistent-world migration, with AWS documentation used to verify GameLift scale tests, Spot behavior, and UDP ping beacons.

A summary of the talk by AWS's Howard and Tomofun (Furbo)'s Ricky, supplemented with the official AWS tech blog: from the vertical integration of Trainium/Inferentia/Graviton/Nitro, to Furbo porting BLIP to Inferentia 2, two-tier Auto Scaling, and AMI cold start optimization, successfully saving 81.6%–83% in AI computing costs.

A summary of the AWS and Super 8 (ORRA) session: the single agent decision loop, three major multi-agent orchestration patterns (Graph/Swarm/Workflow), A2A communication, Amazon Bedrock AgentCore core components, and how ORRA allows business users to build and deploy AI employees in two minutes using Job Descriptions.

A comprehensive summary of the AWS ProServ senior consultant's presentation 'Decompose with Care': How a leading Southeast Asian bank modernized its omni-channel monolithic platform serving 20 million active users to AWS cloud-native microservices with zero downtime. Covers four major challenges, Strangler Fig pattern, 3-Tier Facade, Contract-First / Mock-First approaches, and engineering guardrails in the AI era.

A summary of the salon sharing by AWS Solutions Architect HC and Bito Group Operations Manager Michael: OWASP LLM Top 10 security red lines, runC / gVisor / Kata sandbox comparison, Kubernetes multi-tenant isolation levels, and how BitoClaw builds a compliant, low-cost AI Agent platform using EKS, KEDA Scale-to-Zero, Pod Identity, and Network Policy.

A source-bounded review of low-latency shopping agents and payment guardrails from the Amazon × TapPay session, checked against first-party Alexa for Shopping and AgentCore material.

A source-grounded analysis of how ADK 2.0 separates deterministic routing from LLM reasoning, with production boundaries for workflows, tasks, human approval, and durable state.

Build a testable defense-in-depth architecture around prompt injection, tool authorization, exfiltration, memory and identity, supply chain, and observability boundaries.

What changed in the MCP 2026-07-28 spec versus earlier versions: stateless core, Tasks, Apps, and whether to migrate. The date belongs in the body, not the title.

AI Summit Recap: Enterprise AI Control Plane, 15+ Agents responsibility breakdown, 4-stage runtime workflow for wealth managers, 3-layer security boundaries, LLM-as-a-Judge quality governance, and E·P·J·T reusable capability foundation.

Summary of my Cloud Summit sharing: Three lifelines for financial AI deployment, why PoCs get stuck, the three-tier architecture of Cloud Native AI Runtime, MCP tool governance, Hybrid Search and Agentic RAG, and why accuracy is a workflow property rather than a model feature.

Harness Engineering, in Martin Fowler's terms, means outer control loops around coding agents—feedforward guides plus feedback sensors—so trust is designed control, not a feeling.

An in-depth review of the February 2026 horizontal roundup: an engineer's work splitting into 'building the environment' and 'managing Agents', architecture as guardrails, tools as feedback, AGENTS.md as system records, and the separation of planning and execution.

Based on Anthropic's 'Harness design for long-running application development': Improving the reliability and controllability of long-running tasks through generator-evaluator separation, external evaluation, and QA contracts.

A source-grounded analysis of Anthropic's initializer, progress artifacts, feature inventory, Git checkpoints, and end-to-end verification pattern for work spanning context windows.

An architectural read of Anthropic's Building Effective Agents: workflows, tools, evaluation, and when not to build an agent. This is not the site's complete AI Agent guide.