Anthropic's AI SDLC vs AWS AI-DLC vs Cursor pstack vs my workflow
Anthropic's AI-native SDLC playbook, AWS AI-DLC, Cursor's pstack and my own workflow, compared stage by stage on one real feature, with Claude Code and Kiro.
Forward Deployed Engineer · Indianapolis
I work where software meets the business: the internal tools and last-mile automations that rarely get budget or time, yet quietly compound into serious productivity.




Spec-driven AI engineering, end to end.
Issue status, driven by the staging automation
Anthropic's AI-native SDLC playbook, AWS AI-DLC, Cursor's pstack and my own workflow, compared stage by stage on one real feature, with Claude Code and Kiro.
Every notable Claude feature from Oct 2025 to today, mapped to the products that use it, with current versions, best use cases and a runnable example for each.
A forward deployed engineer sits with the people who have the problem, builds the fix and ships it. What the work is, how it differs, and how to hire one.
Two Kiro Workflows recipes turn my issue to staging to main pipeline into orchestrated agent steps. The runtime validator caught two bugs no JSON parse would.
My experience, skills and current projects in one PDF, in English.
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