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Agent Loses User Preferences After Session Reset — Settings Not Persisted

Symptom

• User says “always respond in bullet points” — agent forgets after restart
• Language preference (e.g., “respond in Korean”) lost between sessions
• Agent asks “how verbose should I be?” again even though user answered last week
• Custom persona or tone resets to default
• User has to re-configure the agent on every session start

Root Cause

LLM sessions are stateless by default. Preferences set in conversation history are lost when history is cleared. There is no built-in persistence layer — the agent must explicitly save and load user preferences from an external store.

Fix

Option 1: Save preferences to a file, load on startup

import json, os
from pathlib import Path

PREFS_FILE = Path.home() / ".agent_preferences.json"

def load_preferences() -> dict:
    if PREFS_FILE.exists():
        return json.loads(PREFS_FILE.read_text())
    return {}

def save_preferences(prefs: dict):
    PREFS_FILE.write_text(json.dumps(prefs, indent=2))

def preferences_to_system_prompt(prefs: dict) -> str:
    if not prefs:
        return ""
    lines = ["User preferences (always apply these):"]
    for key, value in prefs.items():
        lines.append(f"- {key}: {value}")
    return "\n".join(lines)

# On startup: inject preferences into system prompt
prefs = load_preferences()
system_prompt = BASE_SYSTEM_PROMPT + "\n\n" + preferences_to_system_prompt(prefs)

Option 2: Detect and extract preferences from conversation

PREFERENCE_KEYWORDS = [
    "always", "never", "prefer", "don't", "please use",
    "I like", "from now on", "every time", "remember that"
]

async def extract_and_save_preferences(user_message: str, agent):
    """Detect if user is expressing a preference and save it"""
    is_preference = any(kw in user_message.lower() for kw in PREFERENCE_KEYWORDS)
    if not is_preference:
        return

    # Ask agent to extract structured preference
    extraction = await agent.complete([{
        "role": "user",
        "content": f"""Extract the user preference from this message as JSON:
Message: "{user_message}"
Format: key
If no clear preference, return key"""
    }])

    result = json.loads(extraction)
    if result.get("key"):
        prefs = load_preferences()
        prefs[result["key"]] = result["value"]
        save_preferences(prefs)
        print(f"Saved preference: {result['key']} = {result['value']}")

Option 3: Explicit preference commands

# Support slash commands for preference management
def handle_preference_command(command: str) -> str:
    """
    /set language=Korean
    /set tone=concise
    /set format=bullet-points
    /prefs — show current preferences
    /reset-prefs — clear all preferences
    """
    if command.startswith("/set "):
        key, _, value = command[5:].partition("=")
        prefs = load_preferences()
        prefs[key.strip()] = value.strip()
        save_preferences(prefs)
        return f"Preference saved: {key.strip()} = {value.strip()}"

    elif command == "/prefs":
        prefs = load_preferences()
        if not prefs:
            return "No preferences saved."
        return "\n".join(f"  {k}: {v}" for k, v in prefs.items())

    elif command == "/reset-prefs":
        save_preferences({})
        return "All preferences cleared."

Option 4: Database-backed preferences (multi-user)

import sqlite3
from datetime import datetime

def init_prefs_db(db_path="agent_prefs.db"):
    conn = sqlite3.connect(db_path)
    conn.execute("""
        CREATE TABLE IF NOT EXISTS user_preferences (
            user_id TEXT,
            key TEXT,
            value TEXT,
            updated_at TEXT,
            PRIMARY KEY (user_id, key)
        )
    """)
    conn.commit()
    return conn

def get_user_prefs(conn, user_id: str) -> dict:
    rows = conn.execute(
        "SELECT key, value FROM user_preferences WHERE user_id = ?",
        (user_id,)
    ).fetchall()
    return {row[0]: row[1] for row in rows}

def set_user_pref(conn, user_id: str, key: str, value: str):
    conn.execute("""
        INSERT OR REPLACE INTO user_preferences (user_id, key, value, updated_at)
        VALUES (?, ?, ?, ?)
    """, (user_id, key, value, datetime.utcnow().isoformat()))
    conn.commit()

Option 5: Agent workspace notes (file-based, agent-readable)

<!-- ~/.agent_workspace/PREFERENCES.md -->
# User Preferences

- **Language**: Always respond in English
- **Format**: Use bullet points for lists, code blocks for code
- **Verbosity**: Concise — no lengthy explanations unless asked
- **Tone**: Professional but direct
- **Auto-save**: Don't ask "shall I save this?" — just save

PREFS_FILE = Path.home() / ".agent_workspace/PREFERENCES.md"

system_prompt = f"""
{BASE_SYSTEM_PROMPT}

At the start of every session, read and apply the user's saved preferences:
{PREFS_FILE.read_text() if PREFS_FILE.exists() else "No preferences file found."}
"""

Common Preferences Worth Persisting

Preference	Example Value
Language	“Always respond in Korean”
Format	“Use markdown with headers”
Verbosity	“Be concise, skip explanations”
Persona	“You are a senior Python engineer”
Timezone	“UTC+9 (Seoul)”
Code style	“Use type hints, no comments”
Confirmation	“Don’t ask to confirm — just do it”

Expected Token Savings

Re-explaining preferences every session: ~2,000 tokens/session Loaded from file at startup: ~200 tokens (one-time read)

Environment

• Any agent with persistent user sessions
• Source: direct experience, common request in long-term agent deployments

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