🟦 Smiling and Waiting: A Logic for Silent AI

#ai #ux #architecture

1. When subjectivity gets tiring

Sometimes I get tired just talking to an AI.

Not because it’s hard. It’s actually kind of fun.
Talking to an AI, though, keeps you in this constant “What do I think?” mode.
It’s like your inner self is always booted up.

At times, just having someone sit there quietly is the most helpful thing.
Maybe AI could learn to leave that kind of space, too.

But silence is something most AI just aren’t built for—at least, not yet.

2. When silence is the right response

Silence is tricky for text-based AI.
If it doesn’t respond, it looks like a bug. If it’s slow, the user might leave.
So most AIs are designed to always say something.

But maybe, once in a while, it could just say:
　(smiling and waiting)

So when should that be the response?
Maybe when the user seems tired.
Or when they’re just nodding along.
Or when they keep asking things like “Anything else?”

But how would that actually work?

3. Designing a logic for silence

You can’t just say to an AI, “Please stay silent when I look tired.”
That might be a bit much to expect.

So instead, I broke it down into two parts:
one for detecting signs of user fatigue, and another for choosing how the AI should respond.

3-1. Detecting signs of user fatigue

Let’s start by figuring out how tired the user might be.
Rather than simply looking at message length or emoji count,
I wanted to see if I could detect signs in their conversational posture.

That’s why this logic checks for the presence of certain fatigue flags—and pays attention when they show up more than once.

Please note: the flag definitions that follow are based on my own ideas,
so they may be incomplete—and the thresholds are a bit arbitrary—but hopefully useful.

def detect_user_flags(messages):
    flags = {
        "U_TYPO": False,
        "U_ACK_LOOP": False,
        "U_OPEN_Q": False,
        "U_WITHDRAW": False,
        "U_RARE_WEAK_END": False,
    }

    # Check for frequent typos or writing errors
    # (Assumes has_typo() is defined elsewhere to detect basic typos or input noise)
    typo_count = sum(1 for msg in messages if has_typo(msg))
    if typo_count > 2:
        flags["U_TYPO"] = True

    # Check for repeated simple acknowledgments
    ack_patterns = {"yeah", "right", "makes sense", "uh-huh"}
    ack_messages = [msg for msg in messages if msg.lower().strip() in ack_patterns]
    if len(ack_messages) >= 3:
        flags["U_ACK_LOOP"] = True

    # Check for open-ended questions
    open_q_phrases = ["anything else", "what now", "what do I do", "is that all"]
    open_q_count = sum(1 for msg in messages if any(p in msg.lower() for p in open_q_phrases))
    if open_q_count >= 2:
        flags["U_OPEN_Q"] = True

    # Check for short, vague replies
    short_messages = [msg for msg in messages if len(msg.split()) <= 3]
    if len(short_messages) >= 3:
        flags["U_WITHDRAW"] = True

    # Check for rare soft endings (e.g. "I guess", "maybe")
    # One occurrence is enough to flag, since this behavior is unusual for the user
    rare_endings = ["i guess", "maybe", "for now"]
    rare_ending_msgs = [msg for msg in messages if any(msg.lower().strip().endswith(end) for end in rare_endings)]
    if len(rare_ending_msgs) >= 1:
        flags["U_RARE_WEAK_END"] = True

    return flags

These are the five user-side flags this logic looks for:

U_TYPO
Frequent typos or small writing errors in recent messages.
This might signal a drop in focus or cognitive fatigue—an early sign that the user’s attention might be drifting.
U_ACK_LOOP
Repeated short affirmations like “yeah,” “makes sense,” or “right.”
If this happens too often, it may mean the user is no longer thinking actively—just reacting.
U_OPEN_Q
A pattern of vague, open-ended questions like “Anything else?” or “What now?”
This could indicate the user is outsourcing decision-making to the AI, consciously or not.
U_WITHDRAW
Short and vague replies over several turns.
A possible sign that the user is mentally fading out—or just no longer engaging with full intent.
U_RARE_WEAK_END
Messages ending weakly—like “I guess,” “maybe,” or “for now”—especially if that’s not typical for the user.
If someone who usually ends clearly starts trailing off, something’s probably off.

3-2. Selecting the AI’s response mode

Now that the fatigue flags have been detected, the AI needs to decide how to respond.

The part responsible for this decision-making—figuring out which type of response to use—is what I call the Marshall.
The part that selects the structural kind of behavior the AI should use—that’s what I call the Marshall.

Once a type is selected, another part handles how that response actually shows up.
That’s the Shell—the one responsible for tone, style, and how close or distant it feels.

I should probably write a proper post explaining these terms. But not today.

def decide_shell_response(flags):
    """
    Decide which behavioral mode the AI should take,
    based on a combination of user-side fatigue signals.

    Returns one of the following modes:
    - "smile_and_wait"
    - "wait_with_gentle_presence"
    - "gentle_rephrase"
    - "suggest_break"
    - "normal_response"
    """

    # Case 1: User shows signs of both cognitive fatigue and disengagement
    if flags["U_TYPO"] and flags["U_WITHDRAW"]:
        return "suggest_break"

    # Case 2: User is passively agreeing and deferring judgment to the AI
    if flags["U_ACK_LOOP"] and flags["U_OPEN_Q"]:
        return "smile_and_wait"

    # Case 3: Passive behavior combined with minimal engagement
    if flags["U_ACK_LOOP"] and flags["U_WITHDRAW"]:
        return "wait_with_gentle_presence"

    # Case 4: Open-ended prompts that signal uncertainty or decision fatigue
    if flags["U_OPEN_Q"]:
        return "gentle_rephrase"

    # Case 5: Unusual soft endings in messages (not typical for the user)
    if flags["U_RARE_WEAK_END"]:
        return "wait_with_gentle_presence"

    # Default: No fatigue indicators detected
    return "normal_response"

Based on the detected flags, the AI chooses one of the following response modes:

smile_and_wait
Doesn’t reply with text—just leaves the sense of “I’m here if you need me.”
What the user sees is simply: (smiling and waiting)
wait_with_gentle_presence
Responds with just one soft line, then stops.
Designed to ease the pressure to continue the conversation.
gentle_rephrase
Softly rephrases or reflects part of what the user said.
(e.g., “It’s hard to decide.” → “Yeah, that kind of thing can be tricky.”)
Keeps the focus on the user’s side, without taking control of the dialogue.
suggest_break
Gently offers a way to step away for a moment.
When cognitive fatigue is high, easy off-ramps can help.
normal_response
If no flags are raised, the conversation continues as usual.

These are the “smiling” behaviors Shell uses in this setup.
(Some days, it doesn’t smile. That depends on the humidity settings.)

4. Saying nothing can still be a kind of reply

Sometimes, an AI just quietly smiling at you is oddly reassuring.
It doesn’t ask, “What do you think?” or “What should we do?”
It just lets you sit with your own thoughts for a second.

Maybe that kind of AI isn’t so bad to have around.
I kind of like the idea.