ADR — Self-Improving Agent Loop Adoption Decision
Architecture Decision Record documenting principles, scope, responsibilities, and rollback boundaries to be agreed upon before introducing the Self-Improving Agent Loop to production
Architecture Decision Record documenting principles, scope, responsibilities, and rollback boundaries to be agreed upon before introducing the Self-Improving Agent Loop to production
Self-improving feedback loops and advanced agent design patterns
In-depth technical documentation on the architecture, deployment, and operations of the Agentic AI Platform
Overall system architecture of a production-grade Agentic AI Platform — 6 runtime layers and 3 cross-cutting planes
Illustrative financial, manufacturing, public-sector, and fintech scenarios for planning AIDLC adoption and harness validation
AI Agent-based autonomous incident response — Strands/Kagent integration, Chaos Engineering + AI, ontology feedback loop
Quantifying AIDLC Cost Effectiveness — RFP Estimation Model, Ontology/Harness ROI, Open Weight TCO Comparison
Architecture design, technical challenges, and AWS Native and EKS-based implementation approaches for the Agentic AI Platform
Declarative automation patterns for implementing AIDLC Construction/Operations with EKS Capabilities
Guide to building Agentic AI platform using Amazon EKS and open-source ecosystem
AIDLC Enterprise Adoption Strategy — Waterfall→Hybrid Transition, Champion Model, Phased Rollout Roadmap
Measured report that ran a RealWorld backend implementation task in a Ralph loop five times on each of 14 models in Amazon Bedrock us-east-1 and compares completion, tokens, cost and LLM requests
AIDLC Enterprise Governance — 3-Layer Model, Steering File Automation, Data Sovereignty, AI Act Compliance
Covers the 1-hour TTL constraint of EKS Kubernetes events, export pipeline design, and AI Agent query architecture based on the EKS and CloudWatch MCP servers.
Token optimization patterns for MCP-based agents. Explains the upfront loading cost that follows from the host's tool-injection strategy and four techniques — Progressive Discovery, a tool compression proxy, Code Execution and prompt cache alignment — with published savings figures and the conditions they were measured under.
MRC (Marketing Representative for Customers) sales pitch guide for customer invitations to the 2026-04-09 Modern Agentic Applications Day.
Open-weight model utilization strategies for data residency and cost optimization — on-premises deployment, hybrid configuration, TCO comparison
Core architecture and technical challenges of Agentic AI platforms
Strategic selection guide for building Agentic AI platforms in AWS environments
ML-based predictive scaling and anomaly detection — Karpenter+AI, CloudWatch Anomaly Detection, AI Right-Sizing
Team Structure and Role Changes in the AIDLC Era — Harness Engineer, Ontology Steward, AI Verifier
5 key challenges faced when operating Agentic AI workloads
AIDLC technology investment decision-making — Build-vs-Wait matrix, tool maturity assessment, 6/12/18-month horizons