Designing autonomous AI agents: tool integration, multi-agent architecture, permission design, and dividing work between agents and people.
Discover how to design AI integration architecture across manufacturing, procurement, and logistics data silos—and solve the data quality issues blocking ROI for 89% of companies.
Learn patterns & implementation steps for multi-tenant cache design that securely shares prompt context across tenants, significantly reducing inference costs.
Use AI not to cut hours, but to amplify output. Data-backed strategies for lean teams—from startups to elite enterprise units—on maximizing AI leverage for peak productivity.
Learn how Non-Human Identity (NHI) management defines *who* AI agents act as. Covers why human IAM falls short, credential issuance, short-lived tokens, revocation, least privilege, and audit logging.
Evaluating AI agents requires validating tool calls and execution trajectories, not just final outputs. Learn golden set design, trajectory scoring, regression detection, and CI integration.
Eliminate the biggest barrier to production-ready autonomous agents: lack of governance. Step-by-step guide to preventing agent drift and designing accountability.
Most AI agent failures stem from data, not models. Learn how to run a data readiness audit—evaluating quality, accessibility, and structure of internal data.
Learn how "token traps" cause billing spikes in high-frequency agent loops, and how to prevent cost explosions with budget caps, throttling, and smart loop design.
Explore how "thinking time" causes response delays in multi-step reasoning agents, and compare latency budget allocation strategies and implementation patterns based on task complexity.
Learn design patterns and implementation steps for circuit breakers and kill switches that automatically detect runaway costs and hallucinations for immediate shutdown.
Detect shadow AI (ChatGPT, Gemini) used without approval, and learn the audit process covering risk assessment, policy development, and PDPA compliance.
Learn how to design coordinated multi-agent systems. Covers role allocation, communication design, and error handling with concrete architecture diagrams.
