May 31, 2026

Can Knowledge and Know-How Survive After People Leave?

When a person leaves an organization or can no longer explain their experience, how much of the knowledge and know-how they built over a long time remains?

Reports, papers, books, patents, design documents, and code may remain.

But deliverables alone make it difficult to fully understand the thinking process that led to those results.

Why was this problem deemed important
What options were compared
What was attempted and why did it fail
What exceptions and risks were discovered
What were the criteria for the final decision
What practical know-how was not written in the documents

What disappears when a person leaves is not simple information.

It is the context of interpreting information, making judgments, and actually solving problems.

The question 5BY aims to address in the long term lies here.

Can a person's knowledge and know-how be understood and continued even after they leave?

Deliverables Remain, but the Process of Judgment Disappears

Organizations retain countless deliverables.

Proposals, meeting minutes, source code, design files, contracts, research data, and operations manuals are stored.

But in actual work, judgments not recorded in documents are extremely important.

For example, it is hard to fully understand from code alone why a feature was built in its current structure.

What failures occurred in the previous approach
Why was a seemingly simpler method not used
Which customer requirements were prioritized
What risk led to excluding a specific feature
What conditions were right at the time but need to be reviewed now

This information often remains in the memory and conversations of the person in charge.

When the person in charge leaves or the team is disbanded, deliverables may remain but the background of judgments can disappear.

Why Documentation Alone Cannot Preserve All Know-How

Documentation is important.

However, organizing every thinking process and practical experience into documents requires significant time and effort.

In busy work situations, only final results and usage methods tend to be recorded, while intermediate judgments are easily omitted.

Also, people often do not recognize the know-how they naturally possess as separate knowledge.

The first point to check when a failure occurs
How to identify actual requirements from a customer's expressions
Why certain figures are not trusted
Misunderstandings that repeatedly occur during collaboration
Informal conditions to check before official procedures
Sequences naturally followed to avoid failure

This kind of knowledge is better revealed when asked to explain or when actually solving a problem.

So knowledge preservation requires not only finished documents but also the flow of how people think, explain, and judge.

AI Conversations Naturally Retain Thinking Processes

When people converse with ChatGPT, Claude, Gemini, Copilot, Perplexity, DeepSeek, Mistral, and Grok, they do not simply exchange questions and answers.

Users explain problems, add conditions, revise answers, and compare multiple options.

As conversations grow longer, the following traces are naturally left.

Criteria the user considers important
Risks repeatedly checked
Accepted proposals and rejected proposals
Points where judgments changed
How problems are divided
How explanations are understood and restructured
The process of deciding the next task

AI conversations are not finished knowledge documents.

But they can become important material from which thinking processes and judgment criteria can be discovered.

Storing All AI Conversation Raw Text Is Not the Answer

For knowledge preservation, all conversation raw text could be stored indefinitely.

But as records increase, they can become harder to understand again.

Unimportant conversations and key judgments mix together.
Records of the same question repeated multiple times pile up.
Old judgments and recent decisions become indistinguishable.
Personal information and sensitive content may be unnecessarily retained.
You have to re-read long raw text to find the knowledge you need.

5BY does not make long-term storage of all raw text its central goal.

Instead, it aims to leave thought reference points and relationships worth returning to.

What matters is not preserving every sentence, but enabling future users to answer the following questions.

What was being solved
What facts were confirmed
What was decided
What was the reason for that decision
Why were certain options excluded
What problems remain unsolved

The Knowledge Coordinates 5BY Speaks Of

In 5BY, a coordinate does not mean a simple sentence or file location.

It means a reference point from which you can rediscover what problem the user was pondering at a specific point and in what context they made judgments.

A good coordinate requires the following elements.

The purpose of the problem
The background and conditions at the time
Confirmed facts
The chosen direction
Principles to maintain
Excluded options and their reasons
The point to continue next

When this information is connected, future users can understand not just the results but the context in which those results were created.

Anchor Is a Reference Point for Preserving Important Judgments

Anchor is a feature that leaves a flow the user deemed worth reusing in an AI conversation as a reference point.

For example, the following moments can become Anchors.

The moment of finalizing a project's core principle
The moment of proving the actual cause of a recurring failure
The moment of choosing one final direction among multiple options
The moment of newly understanding an important customer requirement
The moment of setting a condition that must be upheld in subsequent work

When such reference points remain, later on you do not have to guess the background of judgments from deliverables alone.

Saved Preserves Conversations Worth Revisiting

Not all important knowledge exists only as a single long flow.

A specific question and answer alone can become important practical know-how.

Saved serves the role of the user personally selecting and preserving conversations they judge worth revisiting.

For example.

A diagnostic method that was decisive in resolving a failure
A key expression used when explaining to customers
An answer that most accurately explained a complex concept
Conditions to repeatedly check in subsequent work
Warnings to avoid mistaken judgments

If Anchor is a reference point for the overall flow, Saved is a conversation within it that is specially worth revisiting.

Graph View Shows the Relationships Between Knowledge

A person's know-how does not exist as a single independent document.

One judgment influences another project, past failures lead to new criteria, and similar principles repeat across different conversations.

Graph View helps explore these flows through the relationships between Anchors and Packs.

The user should be able to examine the following connections.

Which problems started from the same principle
How one failure experience influenced subsequent decisions
What judgment criteria are repeated across different projects
When a specific know-how was first formed
Where an old idea connects to a new problem

Knowledge does not simply accumulate; it gains greater meaning as it connects.

Individual Knowledge Preservation and Organizational Knowledge Preservation Are Different

Individuals can keep records to re-understand their past thoughts and apply them to next judgments.

Organizations must preserve knowledge so that work can continue even after a person leaves.

What is especially important in organizations is the following knowledge.

Operational experience not in official documents
Response sequences for recurring failures
Criteria for interpreting customers and markets
Background of major decisions
Failed attempts and reasons they should not be retried
Practical know-how concentrated in a specific person

When this information is not preserved, new personnel must repeat past failures or investigate already-solved problems from scratch.

5BY's long-term knowledge preservation direction starts with recording individual thoughts, but it can connect to the problem of organizations continuing the context of judgments.

Knowledge Preservation Requires Control and Consent

People's thoughts and conversations may contain sensitive information.

So knowledge preservation cannot be solved by storing more alone.

The following principles are important.

The user must personally choose what to preserve.
Unnecessary raw text should not be stored in its entirety.
Personal information and sensitive conversations must be distinguished.
Organizations must not automatically own individuals' conversations.
The scope of sharing and purpose of use must be clear.
Authority for deletion and access control must be guaranteed.

Collecting all of a person's conversations under the guise of preserving their knowledge is not the direction 5BY pursues.

5BY aims for a structure where the user preserves thought coordinates they deem important and can control the scope in which those coordinates are used.

Knowledge Is Not Copied As-Is but Reinterpreted

Past judgments are not always right for the future.

As environments change and technology advances, past decisions may need to be revised.

The purpose of knowledge preservation is not to make future users follow past conclusions as-is.

It is to help future users understand the following.

What information was available at the time
What constraints existed
Why that decision was considered rational
What conditions have changed now

With this context, future users can respect past know-how while re-judging for new situations.

What Must Continue After People Leave

People eventually leave projects and organizations.

Roles may change, retirement may come, or a moment may arrive when they can no longer explain their experience.

What must remain then is not deliverables alone.

How they viewed problems
Criteria for distinguishing what was important
Lessons learned from failure
Principles repeatedly upheld
Warnings they wanted to pass on to others
Ideas they could not complete
Points the next person should continue from

When these flows remain, knowledge is not just material but becomes the next person's starting point.

5BY's Long-Term Question

5BY currently starts with the problem of rediscovering and continuing the flow of thought that users formed in AI conversations.

It leaves important reference points with Anchor, selects conversations to revisit with Saved, connects context to new conversations with Handoff, and explores the relationships between thoughts and knowledge with Graph View.

These features ultimately lead to one long-term question.

Can the thoughts and know-how a person has built over a long time be understood and continued by others even after that person leaves?

5BY is not trying to create records that replace people.

It aims to create coordinates where you can encounter again what deliberations and judgments lay behind the deliverables a person left.

People may leave.

But the important thoughts and know-how they left do not necessarily have to disappear with them.