Notion and Coda AI Overload: Give Me Data, Not AI

Notion (303 upvotes) and Coda users are frustrated by AI features they never asked for: auto-summarizing pages, suggesting content, adding AI buttons everywhere. What power users actually want is structured data access, API-first workflows, and no AI middleman for basic operations like querying a database or filtering rows. The data-first approach to productivity tooling means giving users raw programmatic access, not wrapping everything in an AI layer.

The complaint pattern

The Reddit threads follow a consistent pattern. Users say: "I just want to query my data." "Stop adding AI to everything." "Give me a better API instead of another chatbot." "I pay for a database tool, not an AI assistant." The frustration is not with AI broadly but with AI inserted between the user and their data when they did not ask for it. The added latency, unpredictability, and cost of AI features reduce trust in tools that should be deterministic.

What users actually want

• Programmatic access to their data without rate limits that punish automation
• Structured query capabilities: filter, sort, aggregate without a chat interface
• Webhook triggers on data changes for custom automation
• Export in standard formats (JSON, CSV) without manual clicking
• API endpoints that are stable and documented, not deprecated every quarter

The data-first alternative

Instead of an AI layer deciding what you probably want, a data-first approach gives you direct access. You write the query, you get the results, deterministically, every time. This is what APIs provide. When you need intelligence on top of that data (trend analysis, competitive research, market signals), you choose when and how to apply it.

import requests, os

# Data-first approach: query what you need, get exactly that
H = {"x-api-key": os.environ["SCAVIO_API_KEY"]}

def get_market_data(query: str) -> dict:
    """Direct data access. No AI middleman. Deterministic results."""
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers=H,
        json={"platform": "google", "query": query},
        timeout=10)
    return resp.json()

# You decide what to do with the data
# No AI summarizing it before you see it
# No AI deciding which fields to show you
# No AI adding latency to a simple data fetch
results = get_market_data("crm software pricing 2026")
organic = results.get("organic", [])
paa = results.get("paa", [])

# You analyze it how you want
prices_mentioned = [r for r in organic if "$" in r.get("snippet", "")]

Building workflows without AI overhead

# Example: Daily competitive monitoring - no AI needed for data collection
import json
from datetime import datetime

def daily_competitor_check(competitors: list[str], keywords: list[str]) -> dict:
    """Pure data collection. Apply intelligence later, if you want."""
    report = {"date": datetime.now().strftime("%Y-%m-%d"), "data": []}

    for kw in keywords:
        result = get_market_data(kw)
        organic = result.get("organic", [])

        # Simple deterministic check: who ranks where?
        for comp in competitors:
            positions = [
                i + 1 for i, r in enumerate(organic)
                if comp in r.get("link", "")
            ]
            report["data"].append({
                "keyword": kw,
                "competitor": comp,
                "positions": positions
            })

    return report

# Output: structured JSON you can pipe to any tool
# Notion, Coda, spreadsheet, dashboard, Slack - your choice

The cost of unwanted AI

Every AI feature added to Notion or Coda costs: $10/month extra for Notion AI, added latency on every page load, unpredictable behavior (AI summaries change even when content does not), and cognitive load from dismissing AI suggestions. Users paying $8-15/month for a productivity tool do not want to pay an additional $10/month for features that slow them down. They want the core product to work reliably and give them API access to automate around it.

The builder mindset

The users complaining loudest on Reddit are builders: they have their own automation, their own dashboards, their own workflows. They chose Notion or Coda as a flexible data layer, not as an opinionated AI assistant. For these users, the right answer is API-first tools that provide raw data access at predictable cost. Search APIs, database APIs, webhook systems. Let the user decide when AI adds value to their specific workflow, rather than injecting it everywhere by default.

Practical alternative stack

Replace the AI-bloated productivity tool with: a simple database (Postgres, Supabase, or even SQLite), a search API for market intelligence at $30/month, a Slack bot or CLI for quick queries, and a weekly cron job for automated reports. Total cost: similar or lower. Total control: complete. No AI between you and your data unless you explicitly add it.