Real products meet tired and hurried users every day, not ideal operators who follow each step in a quiet lab. People wear gloves, work in poor light, grab the wrong plug, skip checks, or reach toward moving parts. These acts show how a product meets the real world.
When a product causes harm, early reports may blame the user, but cases reviewed by Michael Kelly often raise a key question: did the injury come from the design, production, an inadequate warning, or the way it was used? Engineers cannot predict every extreme act. They should study likely mistakes and show how risks were clearly reduced.
Why Ideal Use Is an Incomplete Design Assumption
Intended use defines what the product should do. Foreseeable misuse covers acts outside that pla ...
Key Takeaways
Agentic SDLC platforms help engineering organizations coordinate AI-assisted work across planning, development, testing, deployment, operations, and remediation.
Enterprise teams should avoid treating agentic SDLC as only code generation. The bigger need is governed software delivery across the full lifecycle.
AI agents are more valuable when they understand services, dependencies, ownership, policies, scorecards, runbooks, environments, and delivery standards.
Enterprise software delivery is entering a new phase.
For years, engineering organizations focused on improving the software development lifecycle through DevOps, developer portals, engineering intelligence, and platform engineering. Each category solved part of the problem. Planning tools helped teams organize ...
