Which one are you?
Level 1: Standard Large Language Model (LLM) Prompts
Using Coda AI columns with text prompts to ask the LLM to do something, and getting either a text response, or an image.
More advanced usage; using Coda formulas to inject data into the prompt and extract data from the response.
Level 2: LLM plus Live Web Search
Using Perplexity or Gemini packs to search the web as part of the LLM’s response, for immediate and up-to-date information.
Level 3: Retrieval Augmented Generation (RAG): Upload Your Business Data & Documents
Uploading your company’s own information (data tables, documents, media, etc.) so they are included in the responses and using the AI Assistant Magic pack to execute RAGs.
Level 4: AI Agents & Agentic Workflows
Building AI Agents: autonomous objects (Rows in Tables) that combine business logic with AI prompts and RAG to perform specific business tasks.
Then chaining several AI Agents together into an Agentic Workflow using Action Formulas to automate complicated Standard Operating Procedures (SOP).
Level 5: AI Agentic Workflows with User Interfacing (UI) Apps
Integrating these AI Agentic Workflows into existing Coda Documents which have User Interfaces (Forms or Dialogs) for human interactions.
Level 6: Agentic UI Workflows with Structured AI Languages (SaiL)
Advancing beyond imprecise ‘Prompt Engineering’ trickery to using ‘Structured AI Language’ (SaiL) prompts that are more like Coda formulas with for-each loops and if-then branches.
Business experts can easily define complicated logic and computations, beyond the ability of purely text-based prompting.
Level 7: Expert Systems that Learn from Experience
Building AI Expert Systems that use complicated Rules with ‘fuzzy-logic’, just like human experts, to solve problems autonomously.
These systems learn as they go, and refine the Rules or add new ones based on experience.
If there is any interest, I can post some “How-To” articles to this forum for any of the above.
Max
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I’d love
I’d love any insights your willing to share. In particular, what would interest me most is how you envision Level 7, ie which process you are looking to explore to achieve this agentic self-training.
As always, love following your thoughts and the fact that you share your findings with the community - much appreciated!
Hi Max,
Good summary.
Is this a progression?
Or are some of these level optional/ in parallel?
For example, what is the difference between Expert Systems that Learn from Experience, and RAG enhanced systems? Is L3 data focused while L7 has some additional functionality?
E.g., I hope to get my company to the stage where (some) of their SharePoint data forms the basis for a L3 setup. Do we need to go from L3 to L4, L5 and L6 to get to L7?
P
Always lovely to gain knowledge from you, Max! Would love to know more about L3 +
2 Likes
Add me to the list. I’d love to level up my Coda AI game looking forward to reading your post s.
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same, more info would be great!
I’m curious about levels 4-6. Have you actually made systems like these or is this more of a theoretical post?
I’d love to take a peek at a doc using these kinds of workflows, or watch a video about it.
This is not theoretical at all, but a solid framework.
I have built docs using levels 1 thru 6 for clients.
Level 7 is a work in progress, but looks promising.
It is based on work I did using ‘inference engines’ in LISP many years ago.
Note that I do not refer to AGI anywhere in this taxonomy.
I dont believe it will be available any time soon.
And we have a zillion business automations ready for current AI models right now.
I am on vacation and travelling across Europe a.t.m.
But when I return to my office, I will post examples, and how-to videos here.
Fears that AI is a bubble about to burst, or has (yet again) been over-hyped, are not true in my oppinion.
But getting a solid ROI from AI investments needs a very specific set of skills:
- the ability to design good data structures (ie 3rd normal form DBs)
- the ability to analyse business processes and build automation workflows
- new skills around prompting, RAG engineering, AI agent building, and knowledge graphs
- excellent UX and mobile UI designs that work with AI agents to empower the human in the loop
I believe that Coda provides an extremely versatile and capable platform for exploiting those 4 processes.
And that is why I am going all-in on using Coda AI to achieve the 7 levels of business AI mastery I outlines in the OP.
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I hate natural language prompt-engineering prose-like AI instructions
(Not a popular statement at the moment - but, for me, its like voodoo)
LEVEL 6: Structured AI Language (SaiL) Example
The SaiL prompt is a formula that tells the LLM to do the following;
- store the colors of the rainbow as LIST
- take each color in LIST and do the following
- output the color as a level-3 heading
- output its red and blue components as bullets
- if the green component is zero, say it has no green component
- otherwise show its green component
- then repeat the loop with the next color
The purpose of SaiL is to be able to provide a complex set of instructions in a formula-like manner and NOT to have to try and define the logic in natural language.
Most no-code makers are well able to define logic in this formula-like way.
It is more concise, structured, precise, and understandable, than the long-winded, verbose, imprecise, hard to write, traditional natural-language prompts.
Does anyone agree?
3 Likes
None. None. None, None.None.None.
I totally agree. Artificial structures are more legible than prose in so many cases. Is SaiL a language some AI tools use? Or is it a technique you can use in any AI?
