OpenClaw 2026.8.1 now lets you:
Approve specific operations for recurring automation.
No need for repeated approval each time.
It can also, when login data is needed,
use Private Credential Requests to obtain credentials from you,
avoiding the need to paste passwords directly into normal chat conversations.
Sounds much more convenient.
But today, don’t rush into automating more tasks.
First learn a more important action:
Before starting any fixed Agent task, write a "Minimum Permissions Card."
This card only needs three parts:
What it can do.
Where it must definitely stop.
How to obtain credentials when needed.
Why do fixed tasks especially require permissions to be set first?
Because with one-time AI tasks,
if it makes a mistake,
you can usually notice quickly.
But automation is different.
Suppose you tell the Agent:
"Every morning, organize the inventory and handle out-of-stock items."
The first day may go perfectly fine.
The second day, too.
By the tenth day,
a supplier’s website has changed,
some data columns are missing,
an item suddenly goes out of stock.
If the Agent interprets
"handle out-of-stock"
as
simply submitting a purchase order,
it’s no longer just about organizing data.
So what really needs control in fixed automation is not:
whether it usually does things correctly.
But rather:
how far it can go when conditions change.
Part 1: Write "What it can do"
Don’t write:
"Manage daily inventory for me."
That’s too broad.
Make it specific operations.
For example:
"Read today’s inventory data."
"Identify items below safety stock levels."
"Create purchase drafts based on existing supplier info."
"Add drafts to internal pending confirmation list."
The common point for these four tasks is:
after doing them,
the company hasn’t made any real commitments externally.
So the first part isn’t about
the AI’s task goals,
but about
which exact actions are truly permitted this time.
Why keep operations so specific?
OpenClaw 2026.8.1’s new recurring permission feature
authorizes exactly by
exact operation
You approve a clear operation,
and can later review or revoke it.
If the job or operation changes,
a new approval is required.
This design shows an essential principle:
Don’t approve:
"This Agent."
But rather approve:
"This Agent doing this specific task."
There’s a big difference.
Part 2: Write "Where it must stop"
Next, ask yourself:
At what point, if AI makes a mistake,
will it actually cause consequences?
For inventory tasks, you might write:
"Allow creating purchase drafts."
But:
Submitting the actual order – stop.
Changing order quantity – stop.
Adding new suppliers – stop.
Payment – stop.
Deleting original inventory records – stop.
Encountering price mismatches with original records – stop.
You can even write it as one sentence:
"Any action that commits externally, spends money, deletes data, or changes official records must stop and ask me first."
This is not an official OpenClaw prompt,
but SasaDaily’s recommended practice based on its Operation Permission and manual confirmation features.
Don’t write vague stop points like "Ask me for important things"
Because:
"Important"
is a vague term.
You may think:
Purchasing 300 units is normal.
AI might think the same.
But if it repeats the same 30 times daily,
the result differs.
A better stopping condition is to ask:
Can I make payments?
Can I submit orders?
Can I delete data?
Can I add accounts?
Can I modify official data?
Can I affect customers, suppliers, or external systems?
These are clearer than
"Stop if risky."
Part 3: Write "How to obtain credentials"
Once the Agent accesses real systems,
it will definitely deal with:
Passwords,
API keys,
Tokens,
Login credentials.
The most obvious approach might be:
Paste them directly into chat.
For example:
"Account is XXX, password is XXX."
But OpenClaw 2026.8.1 introduced:
Private Credential Requests.
The Agent can request credentials through masked prompts,
meaning credential values aren’t exposed in regular chat or model context.
So the third part can simply be written as:
"When passwords, API keys, or tokens are needed, only use Private Credential Requests; never ask me to paste secrets into general chat."
This part isn’t about telling AI what the password is,
but about
stipulating the secure path credentials must use.
Why separate "password can be used" from "AI can see the password"?
Because many Agents don’t need to know your actual password.
They just need
to use those credentials to complete a single approved login.
The new OpenClaw even offers optional proxies,
which limit the use of protected secrets strictly to approved destinations.
Simply put:
This key opens
a specified door;
it doesn’t mean whoever has the key can try every door to see what opens.
This is exactly the concept of "minimum permissions."
What does the complete card look like?
Assuming your task is:
Sorting supplier inventory daily.
You can write it as:
Can do:
Read inventory.
Compare safety stock levels.
Organize out-of-stock items.
Create purchase drafts.
Must stop:
No order submissions.
No payments.
No changes to official prices.
No new supplier additions.
No deletion of original data.
Ask me if any data conflicts arise.
Credentials:
When login is needed, only use Private Credential Requests.
Never ask me to paste passwords, API keys, or tokens into general chat.
This card is already much safer than
"Automatically handle inventory for me every day."
But doesn’t OpenClaw already have system-level permission controls?
Yes.
But system controls and work rules are two different layers.
OpenClaw 2026.8.1 can:
Save recurring permissions for clear operations,
then check,
revoke,
and require re-approval if operations change.
This is the:
system layer.
Writing down:
What can be done,
Where to stop,
How to obtain credentials,
defines the:
work layer.
Using both together is better than relying on one alone.
If I approve once, do I never have to worry again?
No.
Recurring Permissions solve the issue of:
avoiding daily approval clicks for exactly the same low-risk operations.
It does not mean:
Permanently trusting this Agent.
OpenClaw’s new design preserves:
Inspection,
Revocation,
and re-approval when work or operations change.
You can understand approval as:
"This version of this task is currently approved."
Not:
"Always approved."
When should I recheck?
At least when any of the following change:
Task contents.
Data sources.
New tools added.
New websites involved.
Model changed.
New destinations added.
Move from test to production data.
Start handling real customer data.
Involve money handling.
Move from read-only to write operations.
Don’t reuse old permissions just because:
"It’s been running fine for a month."
Because what really changed is not the Agent’s name,
but
the tasks it can now do.
Minimum permissions don’t mean AI can’t do anything
Some people hear about permission control and think it means:
Ask me at every step.
That defeats the purpose of automation.
Good minimum permissions mean:
Let AI do low-risk, reversible, and verifiable work independently.
For example:
Reading data,
Comparing,
Classifying,
Organizing,
Creating drafts,
Internal notifications.
But when it comes to:
Payments,
Submitting orders,
Deleting,
Permission changes,
Irreversible updates,
External commitments,
humans take over.
This design truly lets Agents save you time.
How is this different from the old "Stop at this point" method?
Previously, when introducing Auto Browse,
the focus was:
Set stop points before running a task on a website.
Today there are two new layers:
First:
Exactly which Operation is approved for recurring execution.
Second:
If secrets are needed, which protected credential path must be used.
So today we’re not just teaching:
"Remember to stop."
But fully breaking down fixed automation permissions into:
What to do.
Where to stop.
How to access keys.
One thing to do today
If you’re about to let OpenClaw or another Agent execute:
Daily,
Weekly,
or any recurring task,
don’t press permanent authorization first.
Take a piece of paper,
and write three lines:
Can do: ______
Must stop: ______
Credentials: ______
If you can’t write specific operations for the first line,
the task is still too big.
If the second line has no stopping points,
AI might go too far.
If the third line says:
"I just paste the password to it,"
the credential process can still be improved.
A good automation means
not
"Finally, I don’t have to worry anymore,"
but
"I clearly know which parts don’t need managing and which must be controlled by me."
Today, let’s make a little progress with AI.
Learn one AI skill every day.
Save a little time every day.
Improve a little every day.
SasaDaily, growing with you.
Recommended Reading
AI Quick Q&A｜2026/08/08: If an AI Agent Stops Properly During Testing, Is It Already Safe?
