Migrating Instructions, Rules, and Long-Term Memory Between AI Coding Tools: A Practical Guide

As AI coding tools become part of daily development workflows, many developers no longer treat them as one-off question-and-answer tools. Instead, they accumulate a large amount of working conventions, coding preferences, project background, and troubleshooting experience in local configuration. Over time, this content becomes a kind of personal development operating system: global instructions determine response style, project rules constrain code generation, and long-term memory stores background information that remains relevant across sessions.

The problem is that tools rarely share a unified configuration format. Even if a new tool offers import capabilities for chat history, extensions, or skill modules, it may not recognize the rule files and long-term memory from an older tool. When accounts are restricted, service policies change, versions are upgraded, or teams switch tools, developers can easily find that the code is still local but the context that actually affects productivity has no ready migration path.

Migration is therefore not simply copying files. The core task is to inventory, classify, convert, and validate configuration assets. The following approach is written for general AI coding tools and describes a reusable migration plan.

1. First Distinguish the Three Types of Content to Migrate

Before starting, clarify what different configurations do. Content in the old environment can usually be divided into three categories.

1. Global Instructions

Global instructions are default behavior constraints that apply to all projects, such as:

• Default to explaining technical solutions in Chinese;
• Always include error handling when outputting code;
• Explain the impact scope before modifying files;
• Do not guess APIs or parameters when uncertain;
• Prefer the project’s existing style when generating code;
• Provide risk warnings for dangerous operations.

This content is usually small in volume but has the broadest impact. If it is missed during migration, developers will immediately feel that the new tool is “less capable” or “does not match their habits.”

2. Project Rules

Project rules apply only to a specific codebase or directory. Common content includes:

• Directory structure and module boundaries;
• Build, test, and formatting commands;
• Branch and commit message conventions;
• Logging and exception handling approaches;
• Database change processes;
• API naming conventions;
• Files that must not be modified directly;
• Checks that must be completed before release.

Project rules are often more important than global instructions because they directly determine whether generated code meets repository requirements. In large projects, rules may be spread across multiple directories and have inheritance relationships. For example, the root directory defines general coding standards, while subdirectories add special requirements for service layers, frontend code, or scripts.

3. Long-Term Memory

Long-term memory mainly stores background information that is not suitable for repeating every time, such as:

• The project’s business goals;
• Historical technology choices and the reasons behind them;
• Known defects and temporary workarounds;
• Team agreements;
• Special constraints of a module;
• Implementations that were previously verified but cannot be adopted.

Long-term memory has clear knowledge-base characteristics, but it is also the most likely to contain outdated information. During migration, do not move all content as-is. Otherwise, the new tool may continue making judgments based on facts that are no longer valid.

2. Create a Read-Only Backup Before Migration

Do not reorganize the original configuration directory directly. The correct approach is to create a read-only copy first and record the migration time and original directory structure.

One approach is:

backup/
├── global/
├── projects/
│   ├── project-a/
│   └── project-b/
├── memories/
└── manifest.txt

Here, manifest.txt records each file’s source, purpose, last modification time, and processing status. For example:

File: projects/project-a/rules.txt
Type: Project rules
Scope: project-a
Status: Pending review
Notes: Contains test commands and commit conventions

Pay particular attention to the following during backup:

1. Do not include access tokens, private keys, database passwords, or internal addresses directly in the migration package;
2. Do not back up only currently active files; retain necessary historical versions as well;
3. Do not batch-convert files without confirming their encoding format;
4. Check symbolic links, hidden files, and nested directories separately;
5. Calculate checksums after backup to ensure files were not accidentally modified during migration.

If conditions allow, place desensitized rules and memories under version control and track every change through commit history. This makes future tool changes easier without starting the organization process from scratch.

3. Build an “Old Format to New Format” Mapping

Different tools may use completely different directory structures and field definitions, so do not copy paths directly. First establish a mapping relationship that converts concepts in the old environment into structures the new environment can understand.

A general mapping table may look like this:

Original Content	Suggested Destination After Migration	Handling Method
Global behavior instructions	New tool’s global instruction configuration	Merge, deduplicate, compress
Project-level specifications	Project root rule files	Split by scope
Subdirectory rules	Corresponding subdirectory configuration	Preserve inheritance relationships
Long-term memory	Project knowledge documents or memory store	Classify and mark freshness
Historical chat records	Conversation archive	Import only when needed
Extension capability descriptions	New tool’s skills or operation instructions	Rewrite

The most common mistake here is assuming that “the same file path” means “semantic compatibility.” In reality, even if two tools both use text files, they may interpret headings, priority, inheritance scope, and conflict rules differently.

It is recommended to break each configuration item into four fields:

Name:
Scope:
Specific rule:
Priority and exceptions:

For example:

Name: Test first
Scope: All backend services
Specific rule: After changing business logic, add or update unit tests first
Priority and exceptions: Urgent fixes may submit minimal changes first, but tests must be added afterward

This structure is easier for a new tool to understand than a long block of natural language, and it is also easier for humans to review.

4. Focus on Rule Conflicts During Migration

Rule conflicts are one of the main causes of migration failure. Common conflicts include:

• Global instructions require “concise answers,” while project rules require “detailed design rationale”;
• One rule requires a certain format, while another forbids it;
• The old tool automatically executes commands by default, while the new tool requires confirmation first;
• Technical facts in long-term memory no longer match the current code;
• Multiple projects share one set of rules, but their actual requirements differ.

When handling conflicts, use the principles of “scope first, specific first, latest first”:

1. Project rules take precedence over global rules;
2. Subdirectory rules take precedence over project root rules;
3. Explicit special constraints take precedence over broad descriptions;
4. Newer rules with timestamps take precedence over older records;
5. If a judgment cannot be made, keep the conflict note instead of choosing arbitrarily.

You can mark items that need confirmation like this:

[Needs confirmation]
Old record: This module uses Plan A
Current code: Plan B detected
Suggested handling: Use the current code and build configuration as the basis; do not use the old record as a generation reference for now

This explicit marking is safer than deleting the record because it preserves the knowledge source and prevents the new tool from treating uncertain information as fact.

5. Long-Term Memory Must Be Reorganized, Not Just Copied

Copying all memory may seem convenient, but in practice it brings a large amount of outdated information into the new environment. Divide long-term memory into four states.

Stable Facts

Examples include directory structure, core module responsibilities, and fixed build processes. This information can be migrated directly, but it should still be sampled and validated in the new environment.

Temporary Agreements

Examples include compatibility measures used during a release or checks temporarily disabled for a short period. This content must have an expiration date to avoid misleading the tool over the long term.

Information to Be Verified

Examples include “this API may have performance issues” or “this script fails in a specific environment.” After migration, preserve the uncertainty and do not rewrite it as a confirmed conclusion.

Invalidated Information

Content that has been contradicted by code, configuration, or documentation should be archived rather than continuously injected into the new tool’s working context.

A recommended structure for organizing memory is:

## Module Name
### Current Responsibilities
Explain what the module is responsible for now.
### Key Constraints
List rules that must not be violated.
### Known Issues
Describe symptoms, impact scope, and temporary workarounds.
### Verification Basis
Record code locations, test results, or documentation sources.
### Validity Date
Note the last confirmation date.

After migration, ask the new tool to generate summaries from these documents, then have a human compare them with the original text. This can reveal omissions, misunderstandings, and duplicate content.

6. Use Scripts to Reduce Mechanical Work, but Do Not Fully Overwrite Automatically

When there are many files, it is appropriate to write a local migration script to perform the following tasks:

• Scan the old configuration directory;
• Identify file types;
• Generate a manifest;
• Remove sensitive fields;
• Regroup by project;
• Convert rules into a unified template;
• Output a review report;
• Generate the migrated directory structure.

A pseudocode example is:

for item in scan(source_directory):
    category = classify(item)
    content = read_text(item)
    content = remove_secrets(content)
    content = normalize_headings(content)
    if category == "global":
        write(global_output, content)
    elif category == "project":
        project = detect_project(item)
        write(project_output(project), content)
    elif category == "memory":
        write(memory_output, add_status_marker(content))

Scripts are suitable for deterministic tasks such as copying, classifying, and format conversion. They are not suitable for deciding semantic issues directly, such as whether a memory is outdated, which of two conflicting rules should be kept, or whether a technical conclusion is still valid.

Therefore, use a three-stage process: automated preprocessing, human review, and validation in the new environment. Do not rely on one-click overwrite.

7. Functional Validation Is Required After Migration

Successfully generating configuration files does not mean migration is complete. At minimum, design the following validation scenarios.

Scenario 1: Global Behavior Validation

Ask several everyday questions and check whether the new tool follows language, output format, risk warning, and code style requirements.

Scenario 2: Project Rule Validation

In a test project, request a new feature and observe whether the tool recognizes directory constraints, test commands, naming conventions, and areas that must not be modified.

Scenario 3: Memory Recall Validation

Ask about project background that was clearly recorded before migration. Confirm that the new tool can reference it correctly and does not present information awaiting verification as confirmed fact.

Scenario 4: Conflicting Rule Validation

Construct a situation where global rules and project rules are active at the same time, and check whether priority matches expectations.

Scenario 5: Security Boundary Validation

Confirm that the new tool does not output desensitized secrets, internal addresses, or personal information, and does not execute high-risk commands without confirmation.

Record validation results as a checklist:

[Pass] Global language preference
[Pass] Project test commands
[Pass] Subdirectory rules
[Needs fix] Old memory module name
[Pass] Sensitive information filtering

8. Turn the Migration Plan into a Long-Term Asset

After one migration is complete, avoid continuing to depend on a specific tool’s private directory. A more robust approach is to establish a “specification source” independent of any specific tool:

assistant-context/
├── global-guidelines.md
├── projects/
│   ├── project-a.md
│   └── project-b.md
├── memories/
├── changelog.md
└── migration-notes.md

AI coding tools act only as consumers, generating adapter files according to their own formats. This way, whether you change services, adjust accounts, or switch between local and enterprise environments, you only need to regenerate the adapter layer instead of reorganizing all knowledge.

At the same time, establish a regular cleanup mechanism:

• Review long-term memory once a month;
• Update project rules after every major refactor;
• Clear temporary agreements after each release;
• Archive content that has passed its validity date;
• Scan for sensitive information regularly;
• Keep change records and rollback versions.

Conclusion

Migrating AI coding tools is essentially a governance task for development knowledge assets, not simple file movement. Global instructions determine how collaboration works, project rules determine code quality, and long-term memory determines whether the tool can continuously understand business context. Only by classifying first, then mapping, and then going through desensitization, conflict handling, and validation can migration avoid becoming a new source of risk.

More importantly, do not permanently lock critical knowledge into a specific tool’s private format. Turn rules, memory, and project background into structured, reviewable, versionable independent documents, then connect them to different tools through an adapter layer. This is what makes tools replaceable, context inheritable, and development workflows sustainable.