Most teams break AI workflows not because of model quality, but because roles are fuzzy. A practical rule: split work into three streams — research, execution, and quality control. Each stream needs its own prompt template and expected output.
A minimal stack is enough: 1) technical brief template, 2) acceptance criteria template, 3) five-line summary template. This removes most conversational noise and gives repeatable results.
Do not ask “do everything.” Provide context, constraints, and response format. Example: “update this script, do not touch other modules, return a diff and risks.” This cuts iteration count significantly.
Daily routine: morning — top 3 priorities, daytime — one focused technical sprint, evening — short decision log. If the assistant keeps the log automatically, you do not lose context between sessions.
Anti-pattern: running an agent without success criteria. You get lots of text and little value. Success criteria must be measurable: “script compiles,” “endpoint returns 200,” “notification arrived in the correct chat.”
7-day loop: Day 1 templates, Day 2 prioritization rules, Day 3 decision log, Day 4 quality control, Day 5 automated checks, Day 6 retrospective, Day 7 prompt optimization.