Stay Calm and Prompt On (SCAPO): Navigating the AI Service Tsunami with Community Wisdom#

The AI gold rush isn’t slowing down—it’s accelerating. Every morning brings another “revolutionary” AI tool to your inbox. Then ofcourse, another $20/month subscription. The important realization was that, although I maybe using 10% of each tool’s potential, there’s always someone who uses it better.

Let’s say you were using Heygen. Then you stumble across a random Reddit comment: “Pro tip: Use 720p instead of 1080p in HeyGen—saves 40% credits and viewers can’t tell the difference on mobile.”

You test it. It works. You’re simultaneously thrilled and annoyed. WTF.

Why wasn’t this in the documentation?

Because documentation tells you what features exist. But our “annoying” fellow redditors tell you how to actually use them (even taking advantage of these services)

The Problem: You’re Drowning in AI Services, Not Using Them#

🌊 The Subscription Graveyard#

Check your credit card statement. How many AI subscriptions are you paying for right now? Now count how many you used this week.

Common patterns:

• Multiple subscriptions for similar services
• Services used intensively for a week, then forgotten
• Monthly costs adding up to hundreds of dollars
• Only using basic features of premium subscriptions

We’re all collecting AI services like Pokemon cards without clear strategic directives, and these cost $20-50/month each.

📚 Documentation vs. Real-World Usage#

Official docs are great for listing features. They’re terrible at telling you:

• Which settings actually matter for quality vs. cost
• Hidden rate limits that will ruin your workflow at the worst moment
• Workarounds for common issues
• Real performance in production scenarios
• Cost optimization strategies that actually work
• and most importantly, WHERE IT BREAKS!

💸 Hidden Costs of Each Service#

Every service has optimization tricks you’ll only discover after burning through credits:

• ElevenLabs: Specific SSML tags like <break time="1.5s" /> for natural pauses
• Midjourney: Parameter combinations that reduce wasted generations
• Claude: Context window management strategies
• Runway: Quality settings that balance output and credit usage
• GitHub Copilot: Understanding actual rate limits and usage patterns

🕐 The Knowledge Discovery Problem#

The community collectively discovers optimization techniques and usage tips daily, but this knowledge is scattered across:

• Thousands of Reddit threads in dozens of subreddits
• Discord servers with ephemeral conversations
• Blog posts buried in search results
• Twitter threads that disappear in the feed

Meanwhile, thousands of users independently rediscover the same optimizations through expensive trial and error.

SCAPO: Community Knowledge, Organized, Opensource#

SCAPO (Stay Calm and Prompt On) is an open-source tool that automatically extracts optimization techniques from Reddit discussions about AI services.

Current coverage: 381 AI services discovered from curated awesome lists, with automated extraction of specific optimization tips from Reddit discussions.

What SCAPO Extracts#

🎯 Specific Configuration Settings#

• Parameter values that work (temperature, top_p, etc.)
• Model-specific settings for optimal results
• Configuration combinations tested by the community

🚧 Limitations and Workarounds#

• Undocumented rate limits and quotas
• File size restrictions and processing limits
• Known bugs and their workarounds

💰 Cost Optimization Strategies#

• API usage patterns that reduce costs
• Quality vs. cost trade-offs
• Batch processing techniques

How SCAPO Works#

Two Approaches#

Batched Processing with Service Discovery (Recommended):

# Step 1: Discover services from awesome lists
scapo scrape discover --update

# Step 2: Extract tips for specific services
scapo scrape targeted --service "Eleven Labs" --limit 20

# Or batch process multiple services
scapo scrape batch --category audio --limit 15

Legacy Sources Mode:

# Use predefined sources from sources.yaml 
# (you can add your own sources ofc.)
scapo scrape run --sources reddit:LocalLLaMA --limit 10

The Value of Shared Knowledge#

Time/Cost Savings:

• Skip hours of experimentation by learning from community discoveries
• Implement proven optimizations in minutes instead of discovering them yourself

Knowledge caching:

• Valuable tips can be found without going through the Reddit rabbitholes
• Organized, searchable knowledge base that grows over time

Common Questions#

“Why not just read the official docs?” - Docs tell you features, not usage tips discovered through real usage (but in general, read the docs 😂)

“Can’t I just ask ChatGPT for tips?” - ofc. you can, but it will often give you generic advice (i.e., just “suck less and be better”). SCAPO extracts specific techniques from actual user experiences that will lift your eyebrows (“hmm…”, in both good and bad ways)

“What about Discord servers?” - Actually, discord servers are great. I wish I could implement discord pipelines in SCAPO. It is just not scraping-friendly right now

The Philosophy: Stay Calm and Prompt On 🧘#

• Stay Calm: Don’t panic when services don’t work as expected (at least, you will be able to justify your panic now)
• Prompt On: Keep experimenting, but learn from collective experience first

The community has likely already discovered workarounds for common issues. SCAPO makes this collective knowledge accessible.

Getting Started with SCAPO#

Quick Installation#

git clone https://github.com/czero-cc/scapo.git
cd scapo
curl -LsSf https://astral.sh/uv/install.sh | sh  # Install uv
uv venv && source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .
uv run playwright install  # Browser automation

Configure Your LLM#

cp .env.example .env
# Edit .env and set your LLM provider (OpenRouter recommended)

Start Extracting#

# Discover services
scapo scrape discover --update

# Extract tips for a service (the limit here is larger the better. Test it out yourself.)
scapo scrape targeted --service "Midjourney" --limit 20

# Browse extracted tips
scapo tui

Join the Community#

SCAPO is open source and community-driven. Every contribution helps build a better knowledge base for everyone.

Because learning AI services shouldn’t feel like reinventing the wheel every time. Stay calm and prompt on. 🧘