Framing Lock™

Definition

Framing Lock™ occurs when an early decision about how a situation is described, categorized, or interpreted quietly constrains all subsequent decisions — without the practitioner recognizing that the constraint exists. The first framing that "worked" becomes the operative frame, and alternative framings become progressively harder to access.

How It Develops

Framing Lock typically begins at the point of first AI engagement — the initial prompt, the first accepted output, the first formatted response that gets used without modification. Under time pressure, the practitioner accepts a framing because it serves the immediate purpose. They move on. The framing moves with them.

Each subsequent decision builds on what came before. The documentation that follows matches the initial frame. The assessment references the framing established in the note. The plan reflects the priorities built into the first output. The lock deepens gradually, and by the time it becomes visible, it has already shaped a significant portion of the record.

Where It Shows Up in AI Use

• Initial AI-generated assessments that carry forward into documentation without re-evaluation
• Prompts written under pressure that define the terms of all subsequent AI interaction on a case
• Workflows where the first AI output is treated as the foundational draft rather than one possible starting point
• Collaborative settings where a framing produced by AI is shared with the team and becomes the shared frame by default

Why It's Hard to Detect

Framing Lock is invisible by design. When a frame is working — when documents read well, when the workflow flows, when outputs are accepted — there is nothing that signals constraint. The practitioner is not experiencing difficulty. They are experiencing efficiency. The lock is not felt until someone asks a question the current frame cannot accommodate.

Consequences in Practice

• Case documentation that is internally consistent but doesn't reflect the full complexity of the client's situation
• Assessment processes where significant factors were not considered because the initial frame didn't surface them
• Intervention plans built on an understanding of the situation that was narrowed in the first AI interaction
• Professional records that, reviewed later, show a coherent narrative that obscures what was actually happening

Mitigation Strategies

• Frame check at entry: Before accepting an AI output as the working frame, explicitly ask whether an alternative framing would change what the output says.
• Re-entry prompts: At the start of each new AI session on an existing case, deliberately surface the established frame and evaluate whether it still holds.
• ARP Attune phase: Use the Attune phase to establish your own evaluative position before the AI output is introduced.
• Documentation audit: Periodically review AI-assisted records for internal consistency patterns that may indicate locked framing.

Reflection Questions

1. Looking at your most recent AI-assisted case documentation: what frame is it operating within? Did you choose that frame, or did it arrive with the first output?
2. If you re-engaged with this case from scratch today, would you frame it the same way?
3. Is there information about this person or situation that doesn't fit the current frame? What happened to that information?
4. At what point in your workflow would it be hardest to change the working frame? Is that point already behind you?