Spec-driven, production-ready
code generation

Spec-driven, production-ready
code generation

Codeplain is an AI-powered code generation service that produces production-ready software from specifications written in Plain language.

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Specification in Plain

intercom-client.plain

{% include "python-console-app-template.plain" %}

***Definitions:***

- The App interacts with Intercom API (The API).

- The List of Users is the list of Intercom API users.

***Non-Functional Requirements:***

- The resource [intercom-openapi.json](https://github.com/Codeplain-ai/intercom-openapi.json) describes The API.

***Test Requirements:***

- The Conformance Tests should use the real server of The API - do not use mock server.

- The resource [intercom-credentials.json](../credentials/intercom-credentials.json) contains credentials that can be used for testing.

***Functional Requirements:***

- The App should take credentials json as the only positional argument.

- Authenticate with The API.

- Fetch The List of Users from The API.

- Print The List of Users to the console.

Generated Python code

intercom-client.py

def main(args=None):

try:

logger = setup_logging()

logger.info("Application started")

args = parse_arguments(args)

credentials = load_credentials(args.credentials_file, logger)

logger.info("Credentials loaded successfully")

session = authenticate_with_intercom(

credentials['access_token'], logger

)

logger.info("Authentication successful")

users = fetch_intercom_users(session, logger)

print("\nIntercom Users:")

for user in users:

print(f"Name: {user.get('name', 'N/A')}, Email: {user.get('email', 'N/A')}\n")

except Exception as e:

logger.error(f"An error occurred: {e}", exc_info=True)

Explore the SaaS connector repo on GitHub

SaaS connector

Task manager

Specification in Plain

intercom-client.plain

{% include "python-console-app-template.plain" %}

***Definitions:***

- The App interacts with Intercom API (The API).

- The List of Users is the list of Intercom API users.

***Non-Functional Requirements:***

- The resource [intercom-openapi.json](https://github.com/Codeplain-ai/intercom-openapi.json) describes The API.

***Test Requirements:***

- The Conformance Tests should use the real server of The API - do not use mock server.

- The resource [intercom-credentials.json](../credentials/intercom-credentials.json) contains credentials that can be used for testing.

***Functional Requirements:***

- The App should take credentials json as the only positional argument.

- Authenticate with The API.

- Fetch The List of Users from The API.

- Print The List of Users to the console.

Generated Python code

intercom-client.py

def main(args=None):

try:

logger = setup_logging()

logger.info("Application started")

args = parse_arguments(args)

credentials = load_credentials(args.credentials_file, logger)

logger.info("Credentials loaded successfully")

session = authenticate_with_intercom(

credentials['access_token'], logger

)

logger.info("Authentication successful")

users = fetch_intercom_users(session, logger)

print("\nIntercom Users:")

for user in users:

print(f"Name: {user.get('name', 'N/A')}, Email: {user.get('email', 'N/A')}\n")

except Exception as e:

logger.error(f"An error occurred: {e}", exc_info=True)

Explore the SaaS connector repo on GitHub

SaaS connector

Task manager

Specification in Plain

intercom-client.plain

{% include "python-console-app-template.plain" %}

***Definitions:***

- The App interacts with Intercom API (The API).

- The List of Users is the list of Intercom API users.

***Non-Functional Requirements:***

- The resource [intercom-openapi.json](https://github.com/Codeplain-ai/intercom-openapi.json) describes The API.

***Test Requirements:***

- The Conformance Tests should use the real server of The API - do not use mock server.

- The resource [intercom-credentials.json](../credentials/intercom-credentials.json) contains credentials that can be used for testing.

***Functional Requirements:***

- The App should take credentials json as the only positional argument.

- Authenticate with The API.

- Fetch The List of Users from The API.

- Print The List of Users to the console.

Generated Python code

intercom-client.py

def main(args=None):

try:

logger = setup_logging()

logger.info("Application started")

args = parse_arguments(args)

credentials = load_credentials(args.credentials_file, logger)

logger.info("Credentials loaded successfully")

session = authenticate_with_intercom(

credentials['access_token'], logger

)

logger.info("Authentication successful")

users = fetch_intercom_users(session, logger)

print("\nIntercom Users:")

for user in users:

print(f"Name: {user.get('name', 'N/A')}, Email: {user.get('email', 'N/A')}\n")

except Exception as e:

logger.error(f"An error occurred: {e}", exc_info=True)

Explore the SaaS connector repo on GitHub

SaaS connector

Task manager

Review the specification, not the code

Review the specification, not the code

With Plain, your specifications become the new source code. Codeplain turns structured English into production-ready software with full test coverage—no code review required.

Automatically tested.
Maintainable by design.

Automatically tested.
Maintainable by design.

Automatically tested.
Maintainable by design.

Every Plain spec includes testing requirements. Codeplain auto-generates unit and conformance tests and executes them within your infrastructure.

Collaborative AI-powered software development

Collaborative AI-powered software development

AI assists every step of the development process, enabling engineers to work together more effectively through shared specifications, automated workflows, and consistent code generation.

Specs are the new source code

Specs are the new source code

Codeplain turns structured specifications into fully tested, production-ready software—eliminating the need to read or review generated code.

A language built for AI code generation

Plain is a structured English specification language purpose-built for AI-powered code generation. It abstracts implementation details to make generated software reliable, testable, and easy to maintain.

Ready to join the future of software development?

Ready to join the future of software development?

Ready to join the future of software development?

We’re partnering with forward-thinking engineering teams that want to build faster, safer, and more predictably with AI.