Quick Answer
For search, voice, and "just tell me what to do".
An effective AI business stack has 4 layers: Input (capturing data/ideas), Intelligence (processing/reasoning), Execution (creating output), and Feedback (analyzing results). Focus on workflows that connect these layers, not just individual tools.
Key Takeaways:
- Tools are optional; systems are mandatory.
- The 4 Layers: Input, Intelligence, Execution, Feedback.
- Workflows matter more than the specific model you use.
- Design pipelines that can run asynchronously.
- Include human-in-the-loop checkpoints for quality.
Playbook
Audit your current tools: categorize them into the 4 layers.
Identify gaps: do you have strong Execution but weak Intelligence?
Create standard prompts for moving data between layers.
Automate handoffs using tools like Zapier or Make where possible.
регулярно review your stack to remove unused 'shiny objects'.
Common Pitfalls
- Spending too much time configuring tools vs. doing work.
- Building fragile automations that break constantly.
- Neglecting the data privacy of your inputs.
- Ignoring the need for a 'Feedback' loop to improve the system.
Metrics to Track
Number of fully automated workflows.
Time saved per workflow.
Reduction in manual data entry.
System uptime/reliability.
FAQ
What is the best AI tool for business?
There isn't one. The best tool is the one that fits your specific workflow layer. ChatGPT/Claude are great Intelligence layers, Midjourney is an Execution layer, etc.
Do I need to know how to code?
Not necessarily. Low-code/no-code platforms allow you to connect these layers visually. However, understanding the *logic* of the flow is crucial.
Related Reading
Next: browse the hub or explore AI Operations.