Manus doesn't just generate code — it executes it in a real sandboxed environment, sees the output, debugs errors, and iterates until the code actually works. This closes the loop that every other AI code tool leaves open: the gap between generated code and verified, working code.
You describe what the code should do: inputs, expected outputs, edge cases to handle, and the environment it will run in.
Manus writes the implementation, test files, and any configuration needed in the appropriate language and framework.
The code is run in the sandboxed environment. Manus sees the actual output or error messages — not simulated outputs.
If errors occur, Manus reads the error, diagnoses the issue, makes the fix, and runs again — iterating until the code produces the correct output.
Building an automated ETL process
Build a Python data pipeline that pulls daily sales data from a MySQL database, transforms it (deduplication, null handling, currency conversion), and loads to a Snowflake data warehouse. Include logging, error handling, and a test suite. Verify it runs end-to-end.
Creating a REST API with full test coverage
Build a Node.js REST API for user authentication: register, login, logout, and password reset endpoints. JWT tokens with refresh rotation, rate limiting, input validation, and 100% test coverage via Jest. Deliver the working tested codebase.
Web scraping with error handling
Write a Python script that scrapes product prices from 5 e-commerce URLs daily, detects price changes vs the prior day, and sends a Slack webhook notification with the changes. Run it to verify the scraping and notification logic works.
"Python 3.11, using pandas 2.0 and SQLAlchemy 2.0" ensures Manus writes code compatible with your actual environment rather than defaulting to its latest knowledge.
"Write the test cases before writing the implementation" (TDD approach) often produces cleaner, more reliable code than implementation-first development.
"Include a README with deployment instructions, environment variable requirements, and how to run the tests" makes the deliverable immediately usable by your team.
After receiving working code, ask "test the edge cases: empty input, malformed data, database connection failure, and concurrent requests." This stress-tests the initial implementation.