Phase 1: KNOW
Contextual Intelligence
Stop looking at tools and start looking at the problem. Understand AI capabilities, limitations, and security requirements for your specific workflow context.
The Goal
Before mentioning "Generative AI," map the specific workflow step-by-step. Where is the bottleneck? Is it ideation, summarization, or coding?
Workflow Contextualization
Map the Workflow
Break down your workflow into discrete steps. Identify where friction occurs, where time is wasted, and where quality suffers.
- Document each step in the current process
- Identify bottlenecks and pain points
- Measure time spent on each step
Identify the Bottleneck
Determine the specific type of AI assistance needed. Different bottlenecks require different AI capabilities.
Data Classification: The Critical Gate
This is the most important decision point. The sensitivity of your data determines which AI tools are viable options. Get this wrong, and you risk security breaches or compliance violations.
Public Data
Safe for open models. Information that is already publicly available or can be shared without security concerns.
Internal/Confidential
Requires enterprise instances with "zero-retention" policies. Data that must remain within your organization's control.
Strictly Private/IP
May require on-premise or private cloud small language models (SLMs). Highest security requirements.
Constraint Mapping
Latency Requirements
How quickly does the user need a response? This determines whether you need real-time processing or can use batch processing.
Accuracy Requirements
Can you tolerate hallucinations, or do you need factual grounding? This determines whether you need RAG (Retrieval-Augmented Generation) or can use pure generative models.