So, some are starting with Obsidian. My Obsidian-Deck, part of the Cyberdeck Nexus System, is a way more advances version of that Second Brian idea.
They are connecting and online AI with a local Obsidian installation creating that way more Notes for the note structuring software Obsidian.
Then they stare at a view nodes having a Graph. They fall short of that Second Brain, to be honest.
Obsidian is software, that is not fully free of charge by the way and making profit while using it in an enterprise should lead you here at some point, to structure nodes and display that in a graph. Each note is represented by a node and clicking on it will show you the keyword creating the connections to other nodes and the note file itself.
The idea is that a user looks at the connections of one node, being one note, and than reasons about that node and the surrounding nodes. It is a bit like playing Sherlock Homes with your notes, thereby your thoughts, and it does make sense to note down a lot of what goes on in your brain thinking carefully about the keywords. In my Obsidian-Deck made for large sets of note files a LLM does that for you and notes can be Clustered at which point the Graphing Tool of Obsidian turned secondary, having been a great beginning.
So, using Doc Google to find a logic chain:
Scored Leather (Observation) - Scraping Mud (Context) - Careless Action (Inference) -
Clumsy Servant (Character).
as Sherlock Homes would, a CFO of a Financial Corporation would reasoning over his Obsidian:
"It is a capital mistake to theorize before one has data, yet the data in your Obsidian graph speaks with quite a singular voice. Observe this node, 'Q3 Margin Compression'—a clumsy servant to your balance sheet, is it not?
You see, but you do not observe.
I followed the digital trail to 'Raw Materials,' noting the heavy weight of the connection. A lesser mind might blame the 'Global Market,' that convenient scapegoat for every financial mystery. But by eliminating the impossible, we find a curious link to the 'Green Initiative' node.
The deduction is elementary: you have traded your margins for a conscience. You opted for 'Low-Carbon Aluminum' at a fifteen-percent premium, yet failed to adjust your 'Pricing Model' to compensate. The 'clumsy servant' did not steal your profits; he simply spent them on a virtue you forgot to invoice.
The case is closed. The solution lies not in the markets, but in the recalculation of your contracts."
Now read this chat in full length I had with the Google AI to understand what Obsidian is actually made for, and my Obsidian Deck puts to the extreme:
To think like Holmes, you must move from observation to deduction by stripping away the impossible. Here is a logic chain of keywords to guide that process:
Observation: Notice the trifles; the dust on a sleeve or the wear on a watch [1].
Data: Gather every raw fact before theorizing to avoid twisting facts to suit theories [3].
Inference: Connect the "seen" to the "unseen"—the muddy shoe implies the specific path
Exclusion: Systematically eliminate every explanation that contradicts the evidence [4].
Probability: Weigh the likelihood of the remaining scenarios against human nature and
Deduction: Accept whatever remains, however improbable, as the truth [4].
Verification: Test the conclusion against a new set of facts to ensure it holds [3].
Would you like to apply this chain to a specific mystery or a real-life puzzle you’re currently facing?
AI responses may include mistakes. Learn more
For a CFO navigating a complex knowledge graph in Obsidian, the logic chain shifts from physical clues to structural patterns.
Anchor: Select the core node; identify the primary symptom or "crime scene" (e.g.,
Breadcrumbs: Follow the backlinks; see which departments or projects are feeding into
Cross-Reference: Toggle the Graph View to find "bridge nodes"—entities that connect
Anomaly Detection: Look for "orphaned" nodes; data points that should be connected to
Synthesis: Group the clusters; recognize that three separate "issue" nodes all point back
Root Cause: The Holmesian moment—eliminating "market trends" because the data
Mapping: Create a new Canvas or "Map of Content" to visualize the final deduction for
Should we build a specific folder structure or a tagging system to help you surface these connections more quickly?
AI responses may include mistakes. Learn more
The Scenario: Investigating a Gross Margin Drop
You notice a red flag in your monthly report: Gross Margin is down 4% despite steady sales. You open Obsidian, find the [[Q3 Gross Margin]] node, and begin the logic chain:
Select the Anchor Node:
Node: [[Q3 Gross Margin]]
Observation: The node is heavily linked to [[COGS - Cost of Goods Sold]]. You open the
Follow the Primary Connection:
Node: [[COGS - Cost of Goods Sold]]
Observation: You see a thick connection (multiple mentions) to [[Raw Material -
Deduction: The issue isn't labor or overhead; it's a specific supply chain input.
Trace the External Influence:
Node: [[Raw Material - Aluminum]]
Observation: This node has a backlink to a meeting note: [[Meeting: Vendor Review -
Deduction: There was a price hike discussed three months ago that wasn't fully
Identify the "Bridge" Anomaly:
Node: [[Meeting: Vendor Review - AlumiCorp]]
Observation: You notice a surprising connection to [[Project: Green Initiative]].
Inference: Why are the Green Initiative and the aluminum price linked? You follow the
Uncover the Hidden Correlation:
Node: [[Project: Green Initiative]]
Observation: A note inside this project reveals a decision to switch to "low-carbon
Deduction: The margin drop isn't a "market" problem; it's the financial fallout of a
Formulate the Action (The Holmesian Conclusion):
Conclusion: The "impossible" (sudden market inflation) is eliminated. The "improbable"
Action: Create a new node [[Decision: Q4 Pricing Adjustment]] and link it back to the
Would you like to see how to use Dataview queries to automatically list all nodes that share these specific financial tags?
AI responses may include mistakes. Learn more
You see, but you do not observe.
I followed the digital trail to 'Raw Materials,' noting the heavy weight of the connection. A lesser mind might blame the 'Global Market,' that convenient scapegoat for every financial mystery. But by eliminating the impossible, we find a curious link to the 'Green Initiative' node.
The deduction is elementary: you have traded your margins for a conscience. You opted for 'Low-Carbon Aluminum' at a fifteen-percent premium, yet failed to adjust your 'Pricing Model' to compensate. The 'clumsy servant' did not steal your profits; he simply spent them on a virtue you forgot to invoice.
The case is closed. The solution lies not in the markets, but in the recalculation of your contracts."
Shall we now codify this logic into a Template so you may catch the next 'clumsy servant' before the quarter ends?
