Writing Automation in Plain English

TL;DR

Writing automation in plain English means describing what should happen in clear, human language instead of technical logic or scripts. This approach lowers the barrier to automation, improves collaboration, and reduces misunderstandings between business and technical teams. It works best when plain English is translated into structured workflows with clear rules and guardrails.

Why this idea matters now

Automation used to be a technical activity. You needed developers, scripts, and deep system knowledge to make anything run.

That model does not scale well in modern organizations.

Today, the people who best understand processes are often in operations, finance, sales, or support. They know what should happen, but they cannot always express it in code. Writing automation in plain English closes that gap.

It allows teams to describe workflows the same way they explain them to a colleague. That description then becomes the source of truth for automation.

This shift is one of the reasons no-code, low-code, and agentic automation tools are growing so quickly.

What “plain English automation” actually means

Plain English automation does not mean vague instructions like “handle the request.”

It means clear, explicit descriptions such as:

• When a new support ticket arrives, check its category.
• If the issue is billing-related, route it to finance.
• If the amount is above a threshold, request approval.
• After approval, update the system and notify the customer.

These are not technical statements, but they are precise.

Plain English focuses on:

• Triggers
• Conditions
• Actions
• Exceptions
• Outcomes

If a human can follow the steps without guessing, an automation system can usually follow them too.

Plain English vs traditional automation logic

Traditional automation logic is written for machines first and humans second.

It uses:

• If else statements
• Loops
• Variables
• Error codes

Plain English automation flips that priority.

It is written for humans first, then translated into structured execution.

This has several advantages:

• Business users can read and validate the logic
• Edge cases are easier to spot early
• Ownership is clearer
• Documentation is built in

The trade-off is that plain English still needs structure underneath. Language alone is not enough.

Why plain English helps automation succeed

Most automation failures are not technical. They are conceptual.

Teams automate the wrong thing, misunderstand the process, or forget exception paths. Writing automation in plain English surfaces these problems early.

Here is what improves when teams use plain English.

Shared understanding
Everyone sees the same process description. There is less translation loss between business and technical roles.

Faster iteration
Changing a sentence is easier than changing code. This encourages refinement.

Better exception handling
When you write “what happens if this fails” in words, you are forced to think about it.

Stronger governance
Clear language makes it easier to review, approve, and audit automation logic.

Where plain English automation works best

Plain English works especially well for workflows that:

• Span multiple systems
• Involve approvals
• Include human-in-the-loop steps
• Change over time
• Are owned by business teams

Common examples include:

• Lead routing
• Support triage
• Invoice processing
• Refund approvals
• Employee onboarding
• Weekly reporting

In these cases, clarity matters more than micro-optimizations.

Where plain English alone is not enough

Plain English is a design layer, not an execution engine.

It breaks down when:

• Performance tuning is critical
• Logic is extremely complex or mathematical
• Real-time constraints are strict
• Low-level system integration is required

In these cases, plain English should still exist, but it should describe the intent, while technical implementations handle execution details.

Think of plain English as the contract, not the engine.

How plain English connects to AI and agents

AI makes plain English automation more powerful.

Agents can:

• Interpret natural language instructions
• Convert them into structured steps
• Reason about conditions
• Suggest improvements

This is why many teams now start automation design by writing the workflow in plain English, then letting tools or agents help implement it.

However, this also introduces risk.

If plain English instructions are ambiguous, agents may interpret them in unexpected ways. This is why structure and guardrails still matter.

Turning plain English into reliable workflows

To make plain English automation work in production, you need discipline.

A practical approach looks like this.

Step 1. Write the workflow as a narrative
Describe the process start to finish as if explaining it to a new hire.

Step 2. Identify decision points
Mark every place where a choice is made. Write down the rule in simple language.

Step 3. Define exceptions explicitly
For every step, ask “what if this fails or is missing.”

Step 4. Add ownership and approvals
Write who approves what and when.

Step 5. Translate into workflow steps
Only after the language is clear should you map it into tools, bots, or agents.

This keeps automation aligned with reality.

Common mistakes when writing automation in plain English

Teams often make the same mistakes.

Too abstract
Statements like “handle the request” hide complexity. Be specific.

Missing boundaries
If it is not written down, it will be assumed. That leads to errors.

No failure paths
Success is easy to describe. Failure is where systems break.

Overconfidence
Plain English does not remove the need for testing, monitoring, and review.

Treating language as execution
Language defines intent. Systems still need to enforce rules.

Example of plain English automation

Here is a simple before and after.

Before
“Automate invoice handling.”

After
“When a new invoice arrives by email, extract the vendor name, amount, and due date. If any field is missing, flag it for review. If the amount is under 1,000, queue it for automatic entry. If the amount is over 1,000, request approval from finance. After approval, enter the invoice and notify the requester.”

The second version is longer, but it is actionable.

FAQs

What does it mean to write automation in plain English?

It means describing automated workflows using clear, human-readable language that defines triggers, rules, actions, and exceptions.

Is plain English automation the same as no-code?

They are related. Plain English is about how you describe logic. No-code is about how you implement it. Many no-code tools rely on plain English thinking.

Can plain English replace technical automation?

No. It replaces unclear requirements, not execution engines. Technical systems still run the automation.

Does AI make plain English automation safer?

AI makes it easier to convert language into workflows, but safety still depends on clear rules, validation, and monitoring.

Who should write automation in plain English?

The people who understand the process best. Often this is operations, finance, or support, with technical teams reviewing for feasibility.

How detailed should plain English automation be?

Detailed enough that two people would implement it the same way. If interpretation varies, it is not clear enough.

Conclusion

Writing automation in plain English is not about avoiding technical rigor. It is about putting clarity before complexity.

When teams describe processes in language everyone understands, automation becomes easier to build, easier to review, and easier to operate. The systems underneath can be as sophisticated as needed, but the intent remains readable.

In modern automation, plain English is not a shortcut. It is the foundation that keeps workflows aligned with how work actually happens.