Articles
AI delivery
How teams deliver software with AI they can check: specifications, reviews, tests, records of what was checked, and the workflow around coding agents.
- AI agents (13)
- AI Coding Agents (1)
- AI delivery (88)
- AI Delivery Programme (12)
- AI Workflow Audit (2)
- Architecture Review (2)
- Laravel (1)
- MVP to Production (1)
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Loop Engineering: Build the Core Before You Automate the Loop
The recurrence is the visible part of Loop Engineering. The core determines whether every cycle compounds value or repeats uncertainty.
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The Orchestration Tax: More Agents Create More Coordination
Agent count is not throughput. Multi-agent systems create a coordination bill that must be lower than the value of parallel work.
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What an Evidence Receipt Proves and What It Does Not
“Implemented successfully” is a conclusion. An evidence receipt shows the target, changed scope, proof, uncertainty, human decisions, and exact artifacts.
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Enterprise AI Coding Needs Roles, Not Just Permissions
A tool can have safe file permissions and still make the wrong product decision. Enterprise workflow needs role boundaries, artifacts, and escalation.
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An end-to-end AI feature story: from ambiguous ticket to inspectable merge receipt
This AI feature development example moves one fictional account-export request through intake, risk routing, planning, a versioned specification, development, independent review, deterministic checks, documentation…
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A paqad-specific executable readiness audit for team AI development
An enterprise AI coding governance checklist should produce inspectable repository evidence for intent, risk routing, roles, rules, specifications, dependencies, checks, documentation, provider capabilities, rollback,…