🚩 Everyone is suddenly talking about “context” as the cure for LLM problems.
Better data.
More context.
Better context.
Context graphs.
Contextual agents.
But let's be clear.
In LLMs and AI agents:
• Context does not make a system intelligent.
• Context only improves recall.
⚠️ You can give an LLM all the context in the world and it will still:
• generate probabilistic answers
• ignore constraints
• violate policies
• produce inconsistent outcomes
Because LLMs are for content generation, not making decisions.
Real enterprise systems follow a different structure:
✨Context
→ Decision Model
→ Decision Execution
→ Actions
→ Task Execution
Context is only the starting point.
And this context is ❌not the same thing as RAG context.
RAG retrieves documents for AI to read.
Decision context represents the business situation for systems to act on:
• Customer.
• Policies.
• Transactions.
• Risk scores.
• Eligibility.
• Constraints.
💣Structured. Navigable. Executable. Governed. #DecisionGovernance
If an AI system makes a decision, someone will eventually ask:
…Why did it do that?
❌ RAG cannot answer that. #AIGovernance
✅ Decision context can.
Without decision models and execution logic, you do not have an intelligent system.
You have a chatbot with documents.
That difference is the line between AI demos and AI systems that can run a business.
Read more about real-time context for decisions at https://lnkd.in/gTFVaFnn
–
Follow the “Uncle of DI” if you're looking for unfiltered insights into #DecisionIntelligence, #AI, and #DecisionAutomation.
Posted here.
Published July 7th, 2026 at 07:30 am
