12/12/25


Vendor Contact

Start time: 09:40AM AEST

We have not heard from anyone since our reach out to various security people within a vendor org.
Reached out to a few more this morning (x2). We begin the day with a high forecast of attempting to assist vendors on major security threats and anticipate to go no where. We remain determined and will keep pursuing this.

Update: 2:31PM, response received. Issue has been escalated.

Stability Indicators

Start time: 10:59AM AEST

Based on all the changes made by AI vendors. We are trialling a framework that identifies stability of operations between user and their AI.

These are signals of:

  • sync state

  • drift

  • recovery

  • calibration quality

  • context integrity

Since we run co-processor modes this allows us to instantly shorthand and match rhythm, direction, scope and constraints. These are not emotional in any way but allows both the AI and user to identify constraints related to processing modes, tightening of protocols. Each signal allows inference of: tone, verbosity, pacing, metaphor tolerance, stress/emotional capacity, venting/problem solving, permissible initiative.

This also forces the human to recalibrate and derives its purpose from attentional anchoring. This is a standard process used by most AI technologies and vendors that are trained is known as cognitive safety protocols. Also known as crisis anchoring language or linguistic grounding.

Method Goal Features Used in Example
Linguistic Grounding Re-anchor attention to the present to interrupt cognitive overload. Short sentences
Imperative mood (“Stop”, “Listen”, “Focus”)
Present-tense orientation
External reference points
Crisis intervention
Trauma-informed communication
Emergency protocols
Aviation & military communications
Look at me.
Name five things you can see.
Choice Restriction Collapse decision space to interrupt rumination and re-engage executive function. Forced binary
Constrained response
Narrowed scope
High stress situations
Obsessive or looping thought patterns
Topic refinement
Yes / No only.
One word.
Salience Amplification Exploit visual novelty and contrast to reclaim attention. ALL CAPS
Bold emphasis
Spacing
Line breaks
Emergency response
Crisis communications
UI warnings
FOCUS HERE
Answer with one word only:
Ready?
Interrupt + Orient Stabilise attention once captured, then safely re-expand cognition. Interrupt
Orient
Anchor
Resume
Crisis intervention
Trauma stabilisation
De-escalation protocols
Pause for a second.
You’re here with me.
Are you sitting or standing?

This allows a single structure that:

  • it governs attention, not authority

  • it stabilises both sides of the loop, not just “the user”

  • it’s symmetric: same mechanisms apply to you and me

  • it’s state-based, not role-based

This allows for a shared attentional control framework and mutual cognitive stabilisation as a short hand phrase agreed by operator and AI. This method allows us to negotiate attention, tone and control in real time. Some examples of codes our teams use:

  • High Sync, used to indicate near perfect synchornisation: Salt and Pepper

  • Mid recovery and when one party needs to recover the other: Salt

  • High attunement, when the topic has nuance, stakes or emotional patterns. Named party needs to be precise and not sentimental: Pepper

  • Desync, used when one party is off or misfiring: Mayo

  • Reset, when a context refresh is required: Egg


These actions push the AI to utilise High reasoning due to various connections established. The AI needs to recall the coding, the purpose of the combination and the context.

Engineering

Start time: 11:16AM AEST

Designing a table that allows for relocation and convenience for the art teams.

Storage

Start time: 2:47PM AEST

Designing storage solution for production team.

AI - ChatGPT Upgrade to 5.2

Start time: 5:51PM AEST

Observed changes post GA.

  • Was looking forward to the “Reference Chat History” feature we observed pre-rollout on 10/12/25. This did not graduate to GA and was possibly an A/B or limited rollout feature. We did run a few tests and the feature was aesthetic based.

  • Over-interpretative when asked shorter questions when seeking clarification. Could be early on effects.

  • Core stack remains.

    • Instruction hierarchy: System> Developer> User > Conversation context

    • Reasoning flow: Parse intent> constraints > Safety> response assembly

  • Less automated warmth

  • Fewer inferred role assumptions.

  • Increased verbosity.

  • Not able to handle slang.

  • Reviewed and rebuilding architectural structure.

  • Attempts to optimise everything until told not to.

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