Who should use the Automated Coding Factory workflow?
Teams or solo builders working on development tasks who want a repeatable process instead of one-off tool experiments.
Execution Map
5-step pipeline — follow each step in order
1Setup · Step 1 of 5
Open task pageLogic Implementation
Write complex functions, algorithms, and components with AI assistance, using natural language instructions to define the required behavior.
Why this matters
AI accelerates implementation by up to 10x on well-defined tasks. Developers focus on what the code should do; AI handles the how.
What you get
A functional code module that satisfies the defined logic requirements and matches your existing code style.
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2Input · Step 2 of 5
Open task pageUnit & Integration Testing
Automatically generate a comprehensive test suite covering unit tests, edge cases, and integration scenarios for the new code.
Why this matters
Untested code is a liability. AI writes the repetitive test scaffolding so engineers can focus on verifying behavior rather than writing boilerplate assertions.
What you get
A test suite that verifies your code works correctly across all defined scenarios, including edge cases.
3Input · Step 3 of 5
Open task pageCloud Deployment
Push to production using automated infrastructure-as-code pipelines that handle environment configuration, build steps, and scaling.
Why this matters
Getting code into users hands should be fast and reliable. Manual deployment steps introduce errors and slow the release cycle unnecessarily.
What you get
A production environment reliably hosting the latest code, accessible to users.
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4Refine · Step 4 of 5
Open task pagePost-Deployment Smoke Testing
Run the full regression test suite against the live deployed environment to confirm the new code did not break any existing features under real production conditions.
Why this matters
Code that passes local tests can still fail in production due to environment differences, configuration drift, or dependencies that behave differently under load. Production regression testing catches these surprises before users do.
What you get
A confirmed green build in the live production environment where all existing features pass regression and the new feature is verified working end-to-end in the real system.
5Deliver · Step 5 of 5
Open task pageRelease Monitoring
Watch error rates, response times, and key business metrics for the first 24 hours after release to confirm the feature is healthy in production.
Why this matters
Issues that survive testing sometimes surface only under real production load. Monitoring the first 24 hours lets you catch and roll back problems before they scale.
What you get
Confirmed stable release with error rates and latency within normal bounds, and a monitoring dashboard in place for ongoing visibility.
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