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AI Productivity Handbook 4: Workflows and Task Coordination

Run multi-step work with AI using fewer handoffs, less manual stitching, and less rework

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All chapters
12
Locale
English
Course type

Learn to break multi-step AI work into stages: what must run in order, what can run side by side, and how to split work, pull the results together, and trace errors back to their source. You practice on realistic cases such as sorting feedback and comparing documents.

Best for

  • You can already brief AI, supply material, and check results, and now want to handle work that takes several steps

Problems solved

  • Once a task splits into steps, the material doesn't connect and a later step uses the wrong input
  • Several AI threads each work alone, and you still stitch the results together yourself
  • One error forces a full restart, so fast generation doesn't save you time overall

Outcomes
  • Order the steps so AI uses the right material at every handoff
  • Split work among AI helpers and pull their results into one complete deliverable
  • Check the key results, find the step that went wrong, and redo only the affected part
  • Add up preparation, checking, and rework time to see whether you actually saved time

Highlights

  • 12 lessons with 26 techniques, including prompts, hands-on demonstrations, and checking methods
  • Claude Code demonstrations of reading files, running programs, and dividing work among AI helpers

All chapters

12 chapters

Lesson 1: Choose a Method for the Task

Choose a sufficient method for a job, combining methods when needed. Explain choices using material, rules, dependencies, and problems found in a trial.

Lesson 2: Clarify What to Do First and What Must Wait

Work backward from a final deliverable to organize intermediate results and a workflow. Explain what comes first, what can proceed separately, what must meet, and conditions for starting or continuing.

Lesson 3: Hand Off Information the Next Step Can Use

Revise a short handoff so the next step can use it, identifying adopted content, evidence, and gaps. The recipient decides whether to continue, process part, or return it.

Lesson 4: Let AI Interpret Content and Programs Apply Rules

Choose methods for text organization and statistics, distinguishing interpretation from rule-based processing. Check results by original ID and locate the stage requiring correction.

Lesson 5: Clarify Needs Before Choosing a Handling Path

Arrange handling according to required material, actions, and permissions. For multiple questions, unclear meaning, or missing material, identify the owner and what is awaited.

Lesson 6: Check Critical Results Before Continuing

Arrange checks of critical results. Use original quality standards and stop conditions to decide whether to continue, fix only affected parts, wait, or return a decision to the owner.

Lesson 7: Divide Subagent Work by Object or Question

Divide tasks and delivery responsibilities among subagents for one result, ensuring necessary questions have owners and results combine under consistent conditions.

Lesson 8: Run Tasks Together with Less Conflict and Waiting

Assign independent tasks nonoverlapping write locations and decide which tool requests can start together. Use complete delivery records to decide how many tasks to run at once and what to adjust.

Lesson 9: Synthesize Results into an Evidence-Based Conclusion

Bring the results together to form an evidence-based judgment. Explain which conditions are satisfied and which unresolved key questions affect the conclusion.

Lesson 10: Adjust Steps and Assignments as Evidence Emerges

Use evidence actually found to decide whether to continue the original steps or adjust actions and assignments. Explain how to preserve the original goal, permission scope, and stop conditions when adjusting.

Lesson 11: Find the Faulty Step and Redo Only Affected Work

Trace inputs and outputs to the origin of an error and test its cause with a small sample. Examine missing information, conflicting conditions, and other cases to determine where the method applies, what to fix, and which downstream results to recheck.

Lesson 12: Test a Workflow on New Material and Compare Effort

Use another set of similar material to decide whether to retain, partially adjust, or simplify the original workflow. Explain the choice using this run's conditions, check scope, and total effort from preparation to delivery.