ls -la ~/notes/process/
PROCESS
8 articles
cd ../Brainstorming with AI: Why Clarify Beats Prompt
The value of AI brainstorming is not letting AI think for you—it is using AI to think clearly. Mastering diverge–converge rhythm, separating problem from solution space, and keeping a decision log matters more than picking a brainstorming tool.
GStack + GSD + Superpowers: A Long-Horizon Agentic Delivery Stack
GStack owns expert decision-making, GSD owns phase orchestration and context isolation, Superpowers owns TDD and verification discipline — guarded autonomy rather than an unbounded overnight build.
OpenSpec + Superpowers + gstack: A Three-Layer AI-Native Delivery Stack
OpenSpec owns spec truth, Superpowers owns execution discipline, gstack owns expert review and release — layered division of labor rather than mechanically chaining three pipelines.
The AI Development Workflows Landscape: From a Five-Step Skeleton to an Enterprise Delivery Closed Loop
Mainstream AI development workflows converge on Research→Plan→Execute→Review→Ship — mature practice means specs have a source, execution has discipline, review has independence, and release has gates.
Loop Engineering: From Writing Prompts to Designing Manageable Work Loops
Loop Engineering turns the repeated human act of driving AI into a repeatable, verifiable, governable closed loop — the unit of design isn't a sentence, but a loop contract.
Inner Loop / Middle Loop / Outer Loop: The Three Closed Loops of Agent Work
Agent work isn't linear — it splits into three nested closed loops: the inner loop (code-test), the middle loop (task-review), and the outer loop (metrics-improvement). Understanding this model is foundational to designing AI4SE processes.
Designing Human-Agent Collaboration Workflows: Research → Plan → Execute → Review → Ship
AI4SE process design isn't about inserting AI into an old pipeline — it's about redesigning the end-to-end workflow around 'who makes which decisions, and what the agent executes.'
Review Pipeline: How to Review Code When AI Wrote 80% of It
Traditional code review assumes code is human-written and every diff can be read line by line. The AI4SE era needs a new review paradigm — shifting from line-by-line inspection to spec-conformance acceptance.