Agentic Design Digest

Climaxing. Google Gemini Enterprise Platform full lifecycle; ADK 2.0 refactor (deterministic+LLM, 50% token/20% latency reduction); OpenAI Agents SDK + Temporal; AWS AgentCore quotas 5x; Configuration-Driven Agents; Claude Code Dynamic Workflows GA (1,000 parallel agents, evaluator-optimizer loop). Echoes Red Hat supervisor, xAI Grok, SnapLogic MCP Builder. New: Trade reconciliation whitepaper (LangGraph/AutoGen, Planner/Executor/Evaluator); Samsara Agent Studio (no-code IoT agent builder); DZone Six AI Agent Patterns taxonomy; AgenticSTS bounded-memory testbed (0% win rate frontier LLMs vs 16% human); Trunk Tools three-layer architecture (60→10 days); Travelport two-layer MCP architecture; EasyClaw local-first state persistence; Design Patterns for Enterprise AI Agent Architectures (five foundational + cost-control, 70.6% vs 45.2% safe success); AI Agents Architect 2026 roadmap; Supply chain case study; Healthcare AI layered decomposition; Sheaf-ADMM (Sakana AI, ICML2026); AI Agent Error Handling & Self-Healing Patterns (MAST 41-86.7% failure rates); DuoMem on-device memory (77.9% 4B vs 87.1% 72B, 3x speedup); 4-layer memory architecture; Four-phase framework; CI/CD pipelines; Multi-agent pattern taxonomy (80% failure, 68-point gap, 171% ROI); The Log Is the Agent; Sakana AI ICML 2026 preview; A Practical Architecture for Autonomous AI Agents (x402 protocol, ACHIVX reputation). Omnigent meta-harness (policy stacking, sandboxing, multi-vendor orchestration, shared session/credential brokering). Mortgage lending multi-agent blueprint on Red Hat OpenShift AI (MCP-based predictive models, MLflow observability). Aaron Levie 'battle for context' framing (domain expertise, multi-model routing, applied AI layer value beyond wrappers). Three-stage governance model (assistant→agent→operator) as operationalization framework; identity as operational control plane (five concrete areas). Federal trust/governance perspective (HUD call center, NASA Artemis, NIST AI RMF) reinforces human-in-the-loop and scaling governance. Multi-agent system as distributed system (idempotency keys, outbox, sagas) — production hygiene pattern. LLMs alone not enough — enterprise architecture reminder. Ghost memory (A-TMA) — state-aware overlay with evidence packets, separate evaluation of memory bank/retrieval/answer. Agentic workflow patterns primer (sequential, parallel, hierarchical, event-driven, recursive) with infrastructure implications. Human-validated semantic context for analytics agents — structured HITL to avoid propagating wrong patterns. The 3 Loops That Break AI Agents in Production — retry, tool, clarification loops with exit strategies. Is Shared Services Ready for Agentic AI? — readiness framework emphasizing process stability, data reliability, decision rights. New: Building Agents with Claude in 2026 (practical guide, Claude-specific architecture, shift from assistants to agents); Solve AI Agent Sprawl with an Operational Context Layer (Appian, governed operational data access, unified context); Build agentic full-stack apps with Genkit (Google's Genkit for agentic full-stack apps, selective optimization in multi-agent systems); Building Reliable AI Agents for Production Systems (95% pilot failure rate, three-layer security architecture, exception-based governance model, distributed systems primitives). Kore.ai + Atos sovereign agentic AI (bounded autonomy, governance by design). Personal AI Agents 2026 summit (July 21, security/MCP/OpenClaw sessions). Siemens Intelligence Center X (industrial orchestration, hybrid workforce, 85% issue reduction). AI orchestration primer (monday.com, five patterns, governance). GitLost vulnerability (prompt injection in GitHub Agentic Workflows, 'lethal trifecta'). Prompt chaining saga patterns (AWS, event-driven saga for LLM workflows). New: Data Fabrics for AI Agents and MCP — context quality blind spot, federated fabric approach, real-time governance. Quantiphi SAE framework — 5-layer reference architecture for agentic infrastructure on AWS, phased maturity model. Agentic Workflows Explained — TAO loop, design patterns, 78% pilot/14% production stat, reliability-over-capability shift. Agentic Security: How to Build Trust in AI Agents — 84% want L1 automation but only 22% ready, trust as engineering problem, human-on-the-loop. GitLost vulnerability (prompt injection in GitHub Agentic Workflows) — reinforces context window attack surface. First documented agentic ransomware (JADEPUFFER) — fully automated LLM-driven attack on Langflow, verbose adaptation pattern. New: Building & Debugging a Multi-Agent System — practical debugging tutorial for hierarchical multi-agent systems using AirlineTurnaround case study; Agent-S pattern (state machine over conversational) and sly_data channel for persistent state; real failure categories with root cause analysis and solutions. Cognizant ontology+context engineering framework for production readiness. New: Postman AWS AI Competency — API readiness as bottleneck, Gartner 40% cancellation stat, PayPal MCP server (60-to-1 minute time-to-first-call). Meta Muse Spark 1.1 — context compaction, 1M token window, multi-agent optimization. OpenAI ChatGPT Work — GPT-5.6, Codex, autonomous multi-step execution, enterprise controls. Legacy systems integration patterns (wrap, compose, bridge batch, HITL writes, retrieval) — practical production patterns. New: Sam Bhagwat's three production agent patterns (customer-facing, internal enterprise, developer platform) with emphasis on context engineering over model swaps and practical rollout checklists. New: Microsoft Agent Framework pipeline architecture — clear breakdown of middleware, context, and chat client layers across C#, Python, Go. (first seen: 2026-03-13, last updated: 2026-06-08)