Your application starts the work
A request arrives from a business application, a user interface or an integration. It identifies the job, supplies the brief and selects the relevant workflow.
A reusable architecture for organizing context, coordinating AI work and reviewing the result. Available with source, so your team can understand the system it builds on.
Business rules, approved information and a clear definition of done.
A factory is a reusable way to do a type of work. A strategy defines how that work should run. Context supplies the relevant instructions and information. A job carries a particular request through the selected stages.
Factory Line brings those pieces onto a common execution architecture. The same underlying mechanics can support different workflows, while the knowledge about each task lives in configurable records.
That separation matters when your business changes. You can improve instructions, swap an integration or introduce another workflow without treating every change as a new system.
Each layer has a clear purpose. The diagrams show the design pattern; the exact stages and tools depend on the workflow.
A request arrives from a business application, a user interface or an integration. It identifies the job, supplies the brief and selects the relevant workflow.
Company standards, task-specific guidance and relevant project information are assembled for this job. Required information must be present; unrelated context stays out.
Defined stages call the appropriate tools through integration adapters. Job records preserve execution details, output artifacts and the information needed to understand what happened.
A completed tool call is not the same as an acceptable result. Scorecards and review gates evaluate the output and identify when a person must approve, request changes or stop the work.
Measure the gap against the agreed objective, investigate the cause, improve the configuration or implementation and validate the change before it becomes the new baseline.
Your business knowledge deserves a more durable home than somebody's chat history.
The requirements that should stay consistent across work.
The method, constraints and relevant specialist knowledge.
The specific request, inputs and review notes.
Selected layers combine into the job context. Keeping reusable knowledge separate from individual job information makes the system easier to review and maintain.
Define the objective, measure the gap and validate the change. The aim is a more capable system over time, with evidence behind each step.
Set the workflow scope and quality criteria. Compare the observed result with the intended outcome and record where the gap appears.
Examine context, instructions, integration behavior and implementation. Improve the reusable system so the next job benefits from what was learned.
Run representative work, review the outputs and accept the change only when it meets the agreed criteria. Keep a record of the decision.
A controlled improvement mechanism. Factory Line supports configurable improvement workflows. Their activation, scope and human approvals are implementation decisions; this is not a claim of unattended improvement or Six Sigma certification.
The optional $2,500 training and source package combines architecture, factories with source and AI workflow learning. It gives technical teams a foundation to inspect and extend.
DWY adds coaching and direct implementation help. DFY adds responsibility for the core operational foundation. We can also work with the tools and architecture you already have when those better fit your requirements.
Looking for a course, help with a difficult problem, or someone to build a solution? Tell us where you are and what you'd like to do next.