Lens · Alphabet
A to Z
106 titles and 346 aliases in one literal order. An alias points at its page, so a name you half remember still lands.
A
- A Big Little Idea Called Legibility → Rao — A Big Little Idea Called Legibility
- A City Is Not a Tree → Alexander — A City Is Not a Tree
- A Pattern Language → Pattern Language
- a single probe disproves always not never → Falsification Is Asymmetric
- Abadi 2005 CFI → Control-Flow Integrity — Abadi et al.
- Abadi et al. — Control-Flow Integrity → Control-Flow Integrity — Abadi et al.
- abundance creates sameness → AI Commoditizes Expertise
- active confirmation → Human-in-the-Loop by Exception
- After Automation → Dan Shipper — After Automationto read
- Agent Autonomy Spectrum concept
- Agent Memoryauto-ingested concept
- agent wiki → Agent-Maintained Wikiauto-ingested
- Agent-Maintained Wikiauto-ingested concept
- agents as employees → Agents as Employees vs Human-Agent Collaboration
- Agents as Employees vs Human-Agent Collaboration concept
- AI and Employment — Replacement vs Expansion concept
- AI and jobs → AI and Employment — Replacement vs Expansion
- AI Commoditizes Expertise concept
- AI commoditizes the residue of expertise → AI Commoditizes Expertise
- AI Daily Brief → The AI Daily Brief
- AI for Science guest post → Anthropic — Teaching AI to Build Scientific Modelsauto-ingested
- AI for scientific discovery → AI-Accelerated Scienceauto-ingested
- AI for scientific discovery: How researchers use Claude → Anthropic — How Scientists Use Claudeauto-ingested
- AI job loss debate → AI and Employment — Replacement vs Expansion
- AI productivity paradox → Individual vs Organizational AI Gains
- AI share of research time → AI-Accelerated Scienceauto-ingested
- AI slop → Slop
- AI Use Tracks AI Capabilityauto-ingested concept
- AI-Accelerated Scienceauto-ingested concept
- AIDB → The AI Daily Brief
- AIDB — Nine Tips for Getting the Most Out of Codexto read source
- AIDB — The New Jobs AI Will Createto read source
- AIDB — Why Agents Make Every Job a Startupto read source
- AIDB — Why Agents Still Need Humans → The AI Daily Brief — Why Agents Still Need Humans
- Alexander → Christopher Alexander
- Alexander — A City Is Not a Tree source
- Alexander — The Origins of Pattern Theory (OOPSLA 1996) source
- Alexander 1965 → Alexander — A City Is Not a Tree
- Alexander OOPSLA → Alexander — The Origins of Pattern Theory (OOPSLA 1996)
- all models are wrong → Distributions over Best Fits
- allowlist not blocklist → Allowlist over Blocklist
- Allowlist over Blocklist concept
- An Introduction to Cybernetics → Ashby — An Introduction to Cybernetics
- analogical transfer → Surface vs Deep Structure
- Anthropic entity
- Anthropic — How Scientists Use Claudeauto-ingested source
- Anthropic — Investigating Vault Particles with Claudeauto-ingested source
- Anthropic — Progress on Provable Inference for Large Language Modelsauto-ingested source
- Anthropic — Teaching AI to Build Scientific Modelsauto-ingested source
- Anthropic — The Components of Agent Memoryauto-ingested source
- Anthropic agent memory post → Anthropic — The Components of Agent Memoryauto-ingested
- Anthropic provable inference → Anthropic — Progress on Provable Inference for Large Language Modelsauto-ingested
- Anthropic science usage report → Anthropic — How Scientists Use Claudeauto-ingested
- Anthropic vault paper → Anthropic — Investigating Vault Particles with Claudeauto-ingested
- As We May Think → Bush — As We May Thinkto read
- Ashby — An Introduction to Cybernetics source
- Ashby 1956 → Ashby — An Introduction to Cybernetics
- authoritarian high modernism → Legibility
- automate the bulk → Human-in-the-Loop by Exception
- autonomy spectrum → Agent Autonomy Spectrum
B
- backlink index → Navigation vs Search
- blocking → Shrink the Candidate Space
- Blumenfeld — Scaling Karpathy's LLM Wiki (Neo4j) source
- Borges bloat → The Borges Map
- Borges map → The Borges Map
- bottleneck shift → The Bottleneck Shift
- bronze silver gold → Medallion Architecture
- Build It as an Extension concept
- build stuff that doesn't work yet → Leadership, Lab, and Crowd
- build with not against → Build With, Not Against
- Build With, Not Against concept
- Bush — As We May Thinkto read source
C
- candidate generation → Shrink the Candidate Space
- capability-led adoption → AI Use Tracks AI Capabilityauto-ingested
- categorical negative → Falsification Is Asymmetric
- centers → Living Structure
- CFI → Control-Flow Integrity
- CFI paper → Control-Flow Integrity — Abadi et al.
- CFI: Principles, Implementations, and Applications → Control-Flow Integrity — Abadi et al.
- Chad Sanderson data contracts → Sanderson — The Rise of Data Contracts
- ChatGPT → OpenAI
- cheap competence → AI Commoditizes Expertise
- checking AI output → Verification Requires Domain Knowledgeauto-ingested
- Choose the Platform by the Hardest Recurring Part concept
- Chris Alexander → Christopher Alexander
- Christopher Alexander entity
- Claude Code entity
- Claude Cowork → Claude Code
- Claude Coworker → Claude Code
- cliché is low-information → Clichés Carry Less Information
- Clichés Carry Less Information concept
- Codex entity
- Codex Mobile → Codex
- communication ⇄ control → Communication and Control Are Intertwined
- communication and control → Communication and Control Are Intertwined
- Communication and Control Are Intertwined concept
- Components of Agent Memory → Anthropic — The Components of Agent Memoryauto-ingested
- compute constraint → Token Shortage
- compute once → Do It Once, at the Right Place
- compute once at the boundary → Data Contract
- compute placement → Data Gravity
- concede where the other side is better → Build With, Not Against
- control flow integrity → Control-Flow Integrity
- Control-Flow Integrity concept
- Control-Flow Integrity — Abadi et al. source
- control-flow integrity (CFI) → Control-Flow Integrity
- convenient source → System of Record
- critical thinking → Critical Thinking Is Domain-Bound
- Critical Thinking Is Domain-Bound concept
- critical thinking is not a skill → Critical Thinking Is Domain-Bound
- Critical Thinking: Why Is It So Hard to Teach? → Willingham — Critical Thinking, Why Is It So Hard to Teach
- cue vs capability → Metacognitive Strategies
- customer-best over team-relevance → Build With, Not Against
D
- Dan Shipper entity
- Dan Shipper — After Automationto read source
- Dan Willingham → Daniel T. Willingham
- Daniel T. Willingham entity
- Dario Amadei → Dario Amodei
- Dario Amodei entity
- Data & Org Heuristics → Working Heuristics — Data, Matching, Product, Org, Tooling
- Data Contract concept
- data contracts article → Sanderson — The Rise of Data Contracts
- Data Gravity concept
- Data Gravity in the Clouds → McCrory — Data Gravity in the Clouds
- data gravity original post → McCrory — Data Gravity in the Clouds
- Databricks — What is Medallion Architecture source
- Databricks medallion → Databricks — What is Medallion Architecture
- declare the grain → Kimball — Declaring the Grain
- Declaring the Grain → Kimball — Declaring the Grain
- deep structure → Surface vs Deep Structure
- default-deny → Allowlist over Blocklist
- demand for difference → AI Commoditizes Expertise
- derivation at the boundary → Data Contract
- derive once → Do It Once, at the Right Place
- design patterns → Pattern Language
- didn't-happen metric → One Fact Per Grain
- directional links are load-bearing → Scope Hygiene for Tickets and Tooling
- Distributions over Best Fits concept
- do it once → Do It Once, at the Right Place
- do it once at the right place → Do It Once, at the Right Place
- Do It Once, at the Right Place concept
- domain-general thinking skills → Critical Thinking Is Domain-Bound
- don't optimize for the prototype → Choose the Platform by the Hardest Recurring Part
- draw the seam → Build With, Not Against
- dreaming → Dreaming (Offline Memory Consolidation)auto-ingested
- Dreaming (Offline Memory Consolidation)auto-ingested concept
- DRY for data and decisions → Do It Once, at the Right Place
E
- employee agents → Agents as Employees vs Human-Agent Collaboration
- Engineering Heuristics → Working Heuristics — Data, Matching, Product, Org, Tooling
- Ethan Mollick entity
- Every entity
- Every Inc → Every
- Every Media → Every
- exception handling → Human-in-the-Loop by Exception
- extension not new product → Build It as an Extension
F
- Falsification Is Asymmetric concept
- far transfer → Surface vs Deep Structure
- Five Hat Racks → LATCH
- Five Hat Racks → Wurman — Five Hat Racks and LATCH
- five ways to organize information → LATCH
- FlashProve → Anthropic — Progress on Provable Inference for Large Language Modelsauto-ingested
- FlashProve post → Anthropic — Progress on Provable Inference for Large Language Modelsauto-ingested
- Fox Tree → Jean E. Fox Treeto read
- front door foundation → Legibility in the Lens, Not the Land
- Front Door Pattern Language synthesis
- front door patterns → Front Door Pattern Language
- front-door design principles → Legibility in the Lens, Not the Land
- front-door pattern language → Front Door Pattern Language
G
- gains not captured → Individual vs Organizational AI Gains
- generative sequence → Pattern Language
- grain → One Fact Per Grain
- grain discipline → One Fact Per Grain
- graph index → Navigation vs Search
H
- hardest most-recurring part → Choose the Platform by the Hardest Recurring Part
- harness → Agent Autonomy Spectrum
- harnesses → Agent Autonomy Spectrum
- heartbeats → Agent Autonomy Spectrum
- heavy SDLC when → Match Process Weight to Stage and Stakes
- heuristics list → Working Heuristics — Data, Matching, Product, Org, Tooling
- hidden AI use → Secret Cyborgs
- high modernism → Legibility
- high value low ceremony → Match Process Weight to Stage and Stakes
- Hodgkin-Huxley post → Anthropic — Teaching AI to Build Scientific Modelsauto-ingested
- hop vs scan → Navigation vs Search
- How scientists use Claude → Anthropic — How Scientists Use Claudeauto-ingested
- How This Wiki Thinks → Method Reflection
- Human Sandwich → The Human Sandwich
- human-agent collaboration → Agents as Employees vs Human-Agent Collaboration
- Human-in-the-Loop by Exception concept
- human-in-the-loop sandwich → The Human Sandwich
I
- imposed legibility → Legibility
- Inbox inbox
- Individual vs Organizational AI Gains concept
- inference verification → Provable Inferenceauto-ingested
- Infinite Backlog → The Infinite Backlog
- information and originality → Clichés Carry Less Information
- ingestion downstream of export contract → Pipeline Legibility
- Introduction to Cybernetics → Ashby — An Introduction to Cybernetics
- Investigating vault particles with Claude → Anthropic — Investigating Vault Particles with Claudeauto-ingested
J
- James C. Scottto read entity
- Jean E. Fox Treeto read entity
- Jean Fox Tree → Jean E. Fox Treeto read
K
- Karpathy — LLM Wiki Gist source
- Karpathy LLM wiki → Karpathy — LLM Wiki Gist
- Karpathy wiki → Agent-Maintained Wikiauto-ingested
- Karpathy's recipe → Karpathy — LLM Wiki Gist
- ki (knowledge-index) → Blumenfeld — Scaling Karpathy's LLM Wiki (Neo4j)
- Kimball — Declaring the Grain source
- Kimball grain → Kimball — Declaring the Grain
- knowing what to do → The Bottleneck Shift
- knowledge wiki → Agent-Maintained Wikiauto-ingested
L
- L05 vault → Anthropic — Investigating Vault Particles with Claudeauto-ingested
- Lands vs Lives concept
- LATCH concept
- LATCH principle → Wurman — Five Hat Racks and LATCH
- law of requisite variety source → Ashby — An Introduction to Cybernetics
- Leadership Lab and Crowd → Leadership, Lab, and Crowd
- Leadership, Lab, and Crowd concept
- Leadership, Lab, and Crowd → Making AI Work: Leadership, Lab, and Crowd
- Legibility concept
- Legibility in the Lens, Not the Land synthesis
- lens not land → Legibility in the Lens, Not the Land
- lightweight discovery loops → Match Process Weight to Stage and Stakes
- Living Structure concept
- LLM agent memory → Agent Memoryauto-ingested
- LLM wiki → Agent-Maintained Wikiauto-ingested
- LLM wiki recipe → Karpathy — LLM Wiki Gist
- llm-wiki.md → Karpathy — LLM Wiki Gist
M
- Macke Gedon Wahl → Anthropic — Teaching AI to Build Scientific Modelsauto-ingested
- make the manual step productive → Human-in-the-Loop by Exception
- Making AI Work — Leadership, Lab, and Crowd → Making AI Work: Leadership, Lab, and Crowd
- Making AI Work: Leadership, Lab, and Crowd source
- Manus entity
- map as large as the territory → The Borges Map
- match ceremony to stakes → Match Process Weight to Stage and Stakes
- Match Process Weight to Stage and Stakes concept
- maxims about how to think → Metacognitive Strategies
- McCrory — Data Gravity in the Clouds source
- McCrory 2010 → McCrory — Data Gravity in the Clouds
- medallion → Medallion Architecture
- Medallion Architecture entity
- medallion architecture docs → Databricks — What is Medallion Architecture
- Memex → Bush — As We May Thinkto read
- memory as prediction → Agent Memoryauto-ingested
- memory consolidation → Dreaming (Offline Memory Consolidation)auto-ingested
- memory hierarchy → Agent Memoryauto-ingested
- memory notes → Agent Memoryauto-ingested
- Meta → Method Reflection
- metacognition → Metacognitive Strategies
- Metacognitive Strategies concept
- Method Reflection overview
- method tensions → Method Reflection
- model the negative case → One Fact Per Grain
- model uncertainty → Distributions over Best Fits
- model-space search → Distributions over Best Fits
- Mollick → Ethan Mollick
- move compute to the data → Data Gravity
- move the small thing → Data Gravity
- multi-hop architecture → Medallion Architecture
N
- name projects after the outcome → Scope Hygiene for Tickets and Tooling
- name tables for direction → Pipeline Legibility
- name the data flow → Pipeline Legibility
- name what you keep → Allowlist over Blocklist
- Nathaniel Whittemore → NLW (Nathaniel Whittemore)
- navigable structure → Navigation vs Search
- Navigation vs Search concept
- Neo4j LLM wiki post → Blumenfeld — Scaling Karpathy's LLM Wiki (Neo4j)
- nine tips for Codex → AIDB — Nine Tips for Getting the Most Out of Codexto read
- Nine Tips for Getting the Most Out of Codex → AIDB — Nine Tips for Getting the Most Out of Codexto read
- NLW → NLW (Nathaniel Whittemore)
- NLW (Nathaniel Whittemore) entity
- non-identifiability → Distributions over Best Fits
- Norbert Wiener entity
- not a land-grab → Build With, Not Against
- not a new thing to learn → Build It as an Extension
O
- offline consolidation → Dreaming (Offline Memory Consolidation)auto-ingested
- On Exactitude in Science → The Borges Map
- One Fact Per Grain concept
- One Useful Thing entity
- One Useful Thing newsletter → One Useful Thing
- oneusefulthing → One Useful Thing
- OOPSLA 1996 keynote → Alexander — The Origins of Pattern Theory (OOPSLA 1996)
- OpenAI entity
- OpenAI Codex → Codex
- OpenClaw entity
- Organizational AI Benchmarks → Leadership, Lab, and Crowd
- originality as information → Clichés Carry Less Information
- overlap → Tree vs Semilattice
- oversight requires expertise → Verification Requires Domain Knowledgeauto-ingested
- Overview overview
P
- Pattern Language concept
- pattern languages → Pattern Language
- pay it once → Do It Once, at the Right Place
- people use AI where it works → AI Use Tracks AI Capabilityauto-ingested
- persist human decisions → Human-in-the-Loop by Exception
- personal agents → Personal vs Team Agents
- Personal vs Team Agents concept
- physical base table vs modeling layer → Lands vs Lives
- physical bottleneck → AI-Accelerated Scienceauto-ingested
- PI → Provable Inferenceauto-ingested
- piecemeal growth → Living Structure
- Pipeline Legibility concept
- place capability where the mental model is → Build It as an Extension
- placement and judgment → Placement and Judgment Over Raw Execution
- Placement and Judgment Over Raw Execution synthesis
- placement over execution → Placement and Judgment Over Raw Execution
- planned and actual → One Fact Per Grain
- platform selection → Choose the Platform by the Hardest Recurring Part
- priest of communication → The Human Use of Human Beings — Wiener (excerpt)
- process tailoring → Match Process Weight to Stage and Stakes
- process weight → Match Process Weight to Stage and Stakes
- Progress on provable inference for large language models → Anthropic — Progress on Provable Inference for Large Language Modelsauto-ingested
- proof of inference → Provable Inferenceauto-ingested
- Provable Inferenceauto-ingested concept
R
- Rao — A Big Little Idea Called Legibility source
- Rao legibility → Rao — A Big Little Idea Called Legibility
- readable lineage → Pipeline Legibility
- replacement vs expansion → AI and Employment — Replacement vs Expansion
- replay → Dreaming (Offline Memory Consolidation)auto-ingested
- report the distribution, not the best fit → Distributions over Best Fits
- research acceleration → AI-Accelerated Scienceauto-ingested
- reuse the nearest proven mechanism → Build It as an Extension
- reverse index → Navigation vs Search
- Ribbon Farm → Venkatesh Rao
- Ribbonfarm → Venkatesh Rao
- Ribbonfarm legibility → Rao — A Big Little Idea Called Legibility
- Richard Saul Wurmanto read entity
- right-sizing process → Match Process Weight to Stage and Stakes
- RSW → Richard Saul Wurmanto read
S
- salience → Agent Memoryauto-ingested
- sample across the spectrum → Falsification Is Asymmetric
- Sanderson — The Rise of Data Contracts source
- SBI → Distributions over Best Fits
- Scaling Karpathy's LLM wiki → Blumenfeld — Scaling Karpathy's LLM Wiki (Neo4j)
- scarcity when execution is cheap → What's Scarce When Execution Is Cheap
- scope hygiene → Scope Hygiene for Tickets and Tooling
- Scope Hygiene for Tickets and Tooling concept
- Scott → James C. Scottto read
- Secret Cyborgs concept
- Seeing Like a State → James C. Scottto read
- Seeing Like a State → Legibility
- semi-synchronicity → Agent Autonomy Spectrum
- semi-synchronous → Agent Autonomy Spectrum
- semilattice → Tree vs Semilattice
- shadow AI → Secret Cyborgs
- shared agents → Personal vs Team Agents
- Shipper → Dan Shipper
- Shrink the Candidate Space concept
- simulation-based inference → Distributions over Best Fits
- single point of derivation → Do It Once, at the Right Place
- sleep-time compute → Dreaming (Offline Memory Consolidation)auto-ingested
- Slop concept
- SOR → System of Record
- SOT → System of Record
- source of truth → System of Record
- speaking things into existence → Vibe Coding
- split orthogonal scope → Scope Hygiene for Tickets and Tooling
- structure you can navigate → Navigation vs Search
- structure-preserving transformations → Living Structure
- surface structure → Surface vs Deep Structure
- Surface vs Deep Structure concept
- System of Record concept
T
- Teaching AI to build scientific models → Anthropic — Teaching AI to Build Scientific Modelsauto-ingested
- team agents → Personal vs Team Agents
- test the category claim → Falsification Is Asymmetric
- the AI adoption gap → Individual vs Organizational AI Gains
- The AI Daily Brief entity
- The AI Daily Brief — Why Agents Still Need Humans source
- The Borges Map concept
- The Bottleneck Shift concept
- The components of agent memory → Anthropic — The Components of Agent Memoryauto-ingested
- The Crowd → Leadership, Lab, and Crowd
- the delegation paradox → Verification Requires Domain Knowledgeauto-ingested
- the front door's six patterns → Front Door Pattern Language
- the human premium → AIDB — The New Jobs AI Will Createto read
- The Human Sandwich concept
- The Human Use of Human Beings → The Human Use of Human Beings — Wiener (excerpt)
- The Human Use of Human Beings — Wiener (excerpt) source
- The Infinite Backlog concept
- The Lab → Leadership, Lab, and Crowd
- the moves that recur → Placement and Judgment Over Raw Execution
- The Nature of Order → Living Structure
- The New Jobs AI Will Create → AIDB — The New Jobs AI Will Createto read
- The Origins of Pattern Theory → Alexander — The Origins of Pattern Theory (OOPSLA 1996)
- the right overlap → Tree vs Semilattice
- The Rise of Data Contracts → Sanderson — The Rise of Data Contracts
- the value migration thesis → What's Scarce When Execution Is Cheap
- theoretical AI capability → AI Use Tracks AI Capabilityauto-ingested
- thinking is intertwined with knowledge → Critical Thinking Is Domain-Bound
- thinking maxims → Metacognitive Strategies
- three recurring moves → Placement and Judgment Over Raw Execution
- ticket hygiene → Scope Hygiene for Tickets and Tooling
- Token Shortage concept
- token shortage era → Token Shortage
- tool scope → Scope Hygiene for Tickets and Tooling
- tooling hygiene → Scope Hygiene for Tickets and Tooling
- transfer of learning → Surface vs Deep Structure
- tree structure → Tree vs Semilattice
- Tree vs Semilattice concept
- trust readable lineage → Pipeline Legibility
- trust the verifier, not the prover → Provable Inferenceauto-ingested
- turf friction is an unowned boundary → Build With, Not Against
- two modes of working with agents → Agents as Employees vs Human-Agent Collaboration
U
- unfolding wholeness → Living Structure
- unit agents → Personal vs Team Agents
- unreliable join key → Shrink the Candidate Space
- use ratio → AI Use Tracks AI Capabilityauto-ingested
V
- value vs ceremony 2x2 → Match Process Weight to Stage and Stakes
- Vannevar Bush Memex → Bush — As We May Thinkto read
- vault particles → Anthropic — Investigating Vault Particles with Claudeauto-ingested
- Venkat Rao → Venkatesh Rao
- Venkatesh Rao entity
- verifiable inference → Provable Inferenceauto-ingested
- verification gap → Verification Requires Domain Knowledgeauto-ingested
- Verification Requires Domain Knowledgeauto-ingested concept
- vibe benchmarking → Leadership, Lab, and Crowd
- Vibe Coding concept
- vibe-coded → Vibe Coding
- vibework → Vibe Coding
- view-only medallion → Medallion Architecture
W
- what failed is the insight → Distributions over Best Fits
- What is Medallion Architecture → Databricks — What is Medallion Architecture
- what to build → The Bottleneck Shift
- What's Scarce When Execution Is Cheap synthesis
- where data lands → Lands vs Lives
- where data lives → Lands vs Lives
- whitelist over blacklist → Allowlist over Blocklist
- wholeness → Living Structure
- Why Agents Make Every Job a Startup → AIDB — Why Agents Make Every Job a Startupto read
- Why Agents Still Need Humans → The AI Daily Brief — Why Agents Still Need Humans
- Why your knowledge base needs a graph → Blumenfeld — Scaling Karpathy's LLM Wiki (Neo4j)
- Wiener → Norbert Wiener
- Wiener on cliché → Clichés Carry Less Information
- Wiener on cliché and information → The Human Use of Human Beings — Wiener (excerpt)
- wiki as memory representation → Agent-Maintained Wikiauto-ingested
- wiki bloat → The Borges Map
- Wiki Method → Method Reflection
- will AI replace jobs → AI and Employment — Replacement vs Expansion
- Willingham → Daniel T. Willingham
- Willingham — Critical Thinking, Why Is It So Hard to Teach source
- Willingham 2007 → Willingham — Critical Thinking, Why Is It So Hard to Teach
- Willingham 2008 → Willingham — Critical Thinking, Why Is It So Hard to Teach
- Willingham critical thinking → Willingham — Critical Thinking, Why Is It So Hard to Teach
- Working Heuristics → Working Heuristics — Data, Matching, Product, Org, Tooling
- Working Heuristics — Data, Matching, Product, Org, Tooling source
- Wurman → Richard Saul Wurmanto read
- Wurman — Five Hat Racks and LATCH source
- Wurman LATCH → Wurman — Five Hat Racks and LATCH
- Wurman's Law → LATCH
Y
- you can only check what you know → Verification Requires Domain Knowledgeauto-ingested
Z
- zkML → Provable Inferenceauto-ingested
- zkSNARK inference → Provable Inferenceauto-ingested