Structured Review Workflow: How to Transform "Experience" into "Replicable Algorithms"

Many people, when conducting reviews at the end of a project or every Friday, are accustomed to writing diary-style summaries: "Things went well this week, but there were some communication issues. Need to strengthen this next week."

This type of review is inefficient. Because it records "feelings" rather than "logic." Feelings cannot be replicated, but logic can.

To achieve genuine growth, you need to upgrade your review process from "keeping a diary" to "writing algorithms"—deconstructing a successful experience or a painful failure into a set of if-then execution instructions.

Core Logic: From "Descriptive Summary" to "Algorithmic Extraction"

A descriptive summary focuses on What (what happened); algorithmic extraction focuses on Why & How (what was the trigger condition $\rightarrow$ what action was taken $\rightarrow$ what result was achieved).

1. Identify "Key Decision Points"

During the review, do not focus on the overall process. Instead, look for those moments that determined success or failure.
- Bad Example: "The client communication was successful." (Descriptive)
- Good Example: "In the third minute after the client raised budget concerns, I did not immediately explain the price. Instead, I first asked about their specific concerns regarding delivery quality." (Decision Point)

2. Construct the "Experience Algorithm"

Transform the decision point above into a simple logical formula:
[Scenario/Trigger Condition] + [Key Action] $\rightarrow$ [Expected Result]

Case Study: Handling High-Pressure Requirement Conflicts
- Trigger Condition: When the Product Manager and Tech Lead have serious disagreements on feature priorities and reach a stalemate.
- Key Action: Stop discussing specific solutions $\rightarrow$ Elevate the discussion dimension to "Business Goals/KPIs" $\rightarrow$ Require both parties to list the contribution value of their respective proposals to the KPIs.
- Expected Result: Transform emotional arguments into data-driven decisions, quickly reaching consensus.

Execution Checklist: The Four-Step Structured Review Method

Force yourself to fill out the following table during each review:

Dimension	Content	Requirements
Event Retrospective	What happened?	Limited to objective facts; prohibited from using words like "felt" or "probably"
Variable Analysis	Which action led to the result?	If action A were replaced by action B, would the result change? (Counterfactual reasoning)
Algorithm Extraction	If [Condition] Then [Action]	Write it as an operational guide that can be directly handed to a new hire
System Update	Which list should this algorithm be added to?	Update your SOPs, Checklists, or personal knowledge base

Gotchas & Notes

$\times$ Do Not Try to Review Everything

If you try to review every little thing, you will fall into "analysis paralysis." Only review two types of events:
1. Major Successes: You unexpectedly completed a task with high efficiency $\rightarrow$ Extract the success pattern.
2. Painful Failures: You made a basic error that caused delays $\rightarrow$ Build a defense mechanism (to prevent recurrence).

$\times$ Do Not Mistake "Reflection" for "Review"

Reflection is a psychological activity (I feel I should have...), whereas a review is an engineering activity (Next time I encounter situation X, I must execute Y). If no specific If-Then instruction is produced, the review is ineffective.

$\checkmark$ Conduct Regular "Algorithm Audits"

Every month, review the experience algorithms you have extracted. Some algorithms may have been effective at the time but may become obsolete as the environment changes. Delete outdated instructions and optimize existing paths.

Conclusion: The Highest Form of Learning Is Building Your Own SOP

The difference between a top-tier professional and an average person lies in this: Average people rely on temporary inspiration when facing problems each time; professionals possess a highly structured library of personal SOPs that have undergone countless iterations.

Do not let your experience weather into vague memories over time. Alchemize them into a set of precise execution algorithms. 🦊