Build practical AI systems with less guesswork
Implementation-ready workflow kits, evaluation templates, retrieval patterns, and operating playbooks for builders and small teams.
# A reviewable AI workflow1. define the job and failure modes2. prepare representative test cases3. compare outputs against a rubric4. require human approval for decisions5. log revisions and known limitations→ ship the process, not just the prompt
From prompt to accountable process
A practical curriculum for designing, testing and documenting AI-assisted work
Task design
Turn a vague automation idea into a bounded job with inputs, outputs and review criteria.
WORKSHEETSPrompt systems
Build reusable instructions with context boundaries, examples and clear fallback behaviour.
PATTERNSKnowledge retrieval
Map sources, freshness rules and citations before introducing retrieval into a workflow.
RAG BASICSStructured outputs
Design schemas and validation steps before connecting a model to downstream actions.
SCHEMASWorkflow orchestration
Split complex work into observable stages with retry limits and approval gates.
MULTI-STEPEvaluation
Create test sets, scoring rubrics and regression checks that make changes discussable.
EVALSChoose your learning track
One-off digital kits with clear scope and transparent contents.
Prompt Evaluation Lab
Measure prompt changes before they reach users
Retrieval System Starter
A clear starting point for grounded AI answers
AI Workflow Builder
Turn a fragile demo into an accountable workflow
Guardrail & Review Playbook
Make AI-assisted features easier to review and operate
Agent Operations Console
See what an AI workflow did and where it failed
Small-Team AI Stack
A complete operating kit for one focused AI use case
Make the workflow inspectable
The implementation workbook covers scope, data boundaries, test cases, review ownership and a practical launch checklist.
# Example acceptance criteriaaccuracy: supported by sourceformat: valid against schemasafety: no sensitive outputreview: named human owner
Ready to design a better AI workflow?
Start with one bounded use case and a reviewable test set.
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