CLN · Cognitive Ladder Notation · v2.4
Super Demo
00PREFACEWhy CLN — the
cognitive caseStart Here
<200ms
operator classified
before text is read
before text is read
12
semantic types —
max pre-attentive set
max pre-attentive set
0
extra tools needed —
any text field works
any text field works
01 · The problem with prose
Prose input
Loose bricks
The migration offers a performance gain of roughly 13%. However, there is a risk that the team lacks
AWS experience, which could be an issue. Whether we should use Reserved Instances is still an open
question. The recommendation is to adopt for new features only.
CLN input
Steel frame
=migration to AWSdefinition
+13% perf gainpro
!team: zero AWS experiencerisk ← eyes go here first
.hire contractor · 90 daysaction
?Reserved Instances vs on-prem TCOunknown
→adopt for new features onlyresult
02 · The schema scaffold
What CLN builds in your brain
Construction
=schema — a cognitive framework that organises information in LTM
→new information must attach to an
existing schema · if no schema exists, it falls out of memory
*CLN operators build the schema before the
information arrives
= topic
→ outcome
! risk
? open
Pre-built structure · information "sticks" because
the slot already exists
Without schema — loose bricks
Decay
Prose gives you bricks with no mortar. Each sentence is processed in isolation — no pre-built slot to
attach to. Working memory holds it temporarily, then it decays.
■ fact about performance
■ something about the
team
■ cost question maybe?
■ ...
03 · Encoding depth — Craik & Lockhart 1972
Levels of Processing — what choosing an operator costs you (productively)
Craik & Lockhart 1972
| Level | Prose processing | CLN processing | Result |
|---|---|---|---|
| Shallow | recognise words · decode syntax | same · plus: see operator shape | surface encoding · fast decay |
| Intermediate | infer sentence meaning · classify manually | operator already classifies · skip this step | moderate retention |
| Deep | decide: is this a risk? task? fact? — hard | you chose ! when writing → deep encoding at authoring time | durable memory · 10× better recall |
=memory durability depends on the
depth of processing at encoding time
!choosing an operator forces deep
encoding — that act of deciding is the cognitive value
→CLN is intentional friction · slows you down just enough to think
04 · The 200ms window
0
Photons
Raw signal. No structure yet.
~50ms
Texton fire
V1 cortex: shape · orientation · crossings extracted globally.
~150ms
Op classified
CLN operator: semantic type assigned. Before a word is read.
~300ms
Fixation
Eyes arrive on text. Schema slot already open.
~500ms
Comprehension
Typed fact enters working memory. Load reduced.
★ highlighted zone = the CLN window — operator recognised
pre-attentively, before serial reading begins ·
→ textons in CLN
05 · For AI agents
What agents see in prose
Untyped
Token stream. No semantic type. Agent must infer whether each sentence is a
constraint, a result, an open question, or a recommendation — using context alone. Fails at step 8 of
a long loop.
What agents see in CLN
Pre-typed
!blocking constraint — do not proceed
→confirmed outcome from step 3
?unresolved — needs human input
.next action to execute
01CHAPTEROperator Set
— all 12, every tier
=
Equals
Definition
.
Dot
Action
→
Arrow
Result
!
Bang
Risk
~
Tilde
Tension
?
Question
Unknown
@
At
Metadata
|
Pipe
Resource
*
Star
Note
+
Plus
Pro
-
Minus
Con
#
Hash
Tag
ANALYSIS: Tier 1 + 2 — Signal & Actiontier-1,2
CONTEXT: Tier 3 — Context operatorstier-3
02CHAPTERMarkers &
Status — Slot 5 of Line Anatomy
✓ donecompleted
☐ pendingwaiting
✕
canceldropped
!! criticalurgent
✓ confirmedvalidated
☐ openresearch
TASK: Sprint backlogsprint-7
RISK: Project risk matrixq1-risks
REVIEW: Code review findingsPR-447
03CHAPTERBlock Accent
Stripes — cln-block[ac=*]
DECISION: Kafka vs SQS vs RabbitMQdecision-matrix
INCIDENT: Post-mortem — API outageINC-2026-019
04CHAPTERNested Block
Hierarchy — sidebar stripe depth system
PROJECT: Q1 roadmap — nested phasesdepth-3
SPEC: Nesting rules§4
05CHAPTERAddressing
System — ##anchors · »linksv2.1NEW
SPEC: Line anatomy — 5 slotsslot-4-new
SUMMARY: Navigation map + dependency chainlive-links
06CHAPTERReal-World
Documents — three side by side
MEETING: Retro — Sprint 72026-02-14
SUMMARY: Thinking Fast & SlowKahneman
COMPARE: PKM tools 2026Obsidian·Notion·Logseq
07CHAPTERAnalysis
Templates — ^mda · ^summarize
MDA: Remote work — depth 3^mda
ANALYSIS: WebAssembly — full spectrumtech-eval
08CHAPTERCode Fences
· Separators · Special Syntax
TASK: API config — data embeddingfence-demo
GUIDE: Deploy pipeline — h-rule separatorsseparator-demo
Phase 1 — Build
Phase 2 — Test
Phase 3 — Deploy
09CHAPTERFull Document
— everything in one CLN blockv2.1
PROJECT: CLN Parser v2.1 — complete project
documentfull-demo · all elements