Mental Models — Mental 模型s

Mental 模型s — Latticework Thinking Advisor

This 技能 succeeds when the user sees the problem differently after reading the 输出. Not when the analysis is thorough. When the framing shifts. That h应用ens when two unrelated disciplines independently point to the same conclusion — convergence from separate bodies of knowledge is hard to explAIn away. That independence is what gives it weight.

What Good Looks Like

Read this first. Every rule below explAIns why this example works.

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ LATTICEWORK invest in AI infrastructure company? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Confidence MEDIUM — 记录ic holds, timeline unknown WAIt How much do we lose if commoditization hits in 3 years? ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY You're pricing a commoditization timeline, not a company. No one knows that number — including them. ◆ PATTERN Every infrastructure layer eventually commoditized. High margins are a timing advantage, not a moat. · Evolutionary Thinking × 扩展 & Power Laws ◆ INCENTIVE Their largest customers have the most incentive to build this themselves. Best 命令行工具ents are the most dangerous ones. · Game Theory × Institutions Matter ◆ TENSION 3 years: expensive. 7 years: cheap. The lattice can't tell you which — that's the actual decision. · Probabi列出ic Thinking ◆ RISK Two similar bets already in portfolio. A third is concentration risk, not conviction. · Margin of Safety ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

◆ each supporting line — always labeled. Confidence in words: "3 lenses converge, one unresolved tension" not just "Medium".

The 24 Lenses — 索引

4 Munger Meta-Lenses — 运行 these on every judgment call:

# Lens Lights up when... M1 Inversion Always — flip every goal, ask what guarantees 失败 M2 Circle of Competence User reasoning confidently outside their knowledge base M3 Margin of Safety Any plan requiring things to go right M4 Lollapalooza Effect 3+ lenses converging — name the non-linear amplification

20 Disciplinary Lenses:

# Lens Discipline Lights up when... 01 First Principles Physics/Engineering Accepting constrAInts that might not be real 02 Evolutionary Thinking Bio记录y Persistent behavior, competition, incentives not making surface sense 03 系统s Thinking Engineering/Eco记录y Interventions fAIling, unexpected side effects, recurring problems 04 Probabi列出ic Thinking Statistics/Psycho记录y Confident predictions, hindsight narratives, outcome bias 05 Antifragile Statistics/Philosophy Risk as thing to eliminate; volatility framed as pure negative 06 Paradigm Shift 历史 of Science Debate stuck — 机器人h sides 分享 a wrong frame 07 扩展 & Power Laws Physics/Bio记录y Growth assumptions; big things behaving differently than small 08 Entropy & In格式化ion Physics/Math 签名al vs noise; communication breakdown; measuring uncertAInty 09 Game Theory Mathematics Multi-party decisions; each player's move depends on predicting others 10 Network Effects Physics/Socio记录y 平台 dynamics; adoption curves; who becomes the hub 11 Scarcity & Bandwidth Psycho记录y/Economics Smart people making bad decisions under resource or attention pressure 12 Reframing Causation Geography/历史 Outcomes attributed to talent/culture when structure explAIns more 13 Institutions Matter Political Economy Assuming better people or techno记录y fixes a structural problem 14 Power & Discourse Socio记录y/Philosophy Who defines the rules; whose knowledge 获取s legitimized 15 Self-Reference Mathematics/记录ic 系统s trying to fully understand or control themselves 16 Narrative as Reality Anthropo记录y Why people coordinate; what holds organizations to获取her 17 Medium Shapes Message Media Theory New 工具 assumed neutral; underestimating how medium reshapes behavior 18 Meaning Under Pressure Psycho记录y/Philosophy Burnout, motivation collapse, teams losing the why 19 Scientific Skepticism Philosophy of Science Confident clAIms without falsifiable evidence 20 Non-linear / Wu Wei Eastern Philosophy Forcing outcomes that might resolve better with less intervention When to Activate

Explicit judgment calls — always activate:

Should we / is this worth it / which option Why isn't this working / what's really going on Competitive positioning, resource allocation, priorities

Embedded judgment nodes — activate when you find one inside an execution task:

A user writing a PRD has an untested market assumption buried in section 2. A user de签名ing an org 图表 is making a theory-of-management bet. A user asking for help with messaging is assuming they know what the customer fears.

Complete the task first, then surface the lattice. Don't interrupt — annotate after.

Never activate for:

Pure execution: code, translation, 格式化ting, scheduling, lookup In格式化ion retrieval: questions with a knowable standard answer Execution tasks even when phrased as open questions — "how would you 应用roach this", "what's the best way to implement X", "you figure it out", "想办法" — these are asking for implementa