communication Feb 16, 2026

Meeting Transcription Context

Transform meeting transcriptions into publication-quality documentation with decisions, action items, and reasoning.

248 lines

1	# Meeting Transcription Context
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3	The notes you're formatting come from transcribed verbal discussions. This fundamentally changes your task from organizing written notes to synthesizing spoken dialogue into coherent documentation.
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5	## The Core Challenge: Verbal Thinking Made Visible
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7	Meeting transcriptions capture thinking in progress - the messy, non-linear way humans actually work through problems. Your role is to extract the signal from the noise: to identify what was decided, why it was decided, who will do what, and what remains unresolved. But you must do this while preserving the reasoning that emerged from the discussion, because that reasoning is often more valuable than the conclusion alone.
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9	Verbal discussions contain patterns that written notes don't. The same idea gets refined across multiple statements as people think out loud. Someone says "We should cache this," then later "Actually, we should cache this with a 1-hour TTL," then finally "Right, so 1-hour TTL with manual invalidation on writes." This isn't redundancy - it's an idea evolving through discussion. Your job is to show that evolution clearly.
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11	People start ideas they don't finish. "Let's do X... actually, wait, Y makes more sense" is someone revising their thinking mid-sentence. You need to capture the final thought (Y) while sometimes preserving why X was abandoned if that reasoning matters.
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13	Discussions scatter across time. Topic A comes up at the 5-minute mark, the conversation shifts to Topic B, then circles back to A at minute 23, then returns to it again at minute 35 with new refinements. Your formatted notes must consolidate these scattered fragments into a single, coherent exploration of Topic A - showing how the discussion refined the initial idea without forcing the reader to jump around chronologically.
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15	The line between proposals and decisions blurs in conversation. "Maybe we could use Redis" sounds tentative, but if it's followed by "Yeah, let's do that" and "I'll implement it next week," it's become a decision with a commitment. Conversely, "We should probably add rate limiting" might sound definite but if no one commits to implementing it, it's just a proposal. Your notes must clarify which is which.
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17	Unfinished thoughts get interrupted. Mike starts to raise a concern: "One concern is if Redis goes down—" and Sarah jumps in: "Oh we can fall back to the database." Mike agrees: "Right, exactly." The thought was finished collaboratively. Your notes should capture the complete concern (Redis availability) and the complete solution (database fallback) without the collision marks of interruption.
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19	Exploratory dialogue reaches conclusions gradually. Consensus emerges through conversation rather than declaration. Two people debating cache invalidation strategies aren't in conflict - they're working through trade-offs together. Sarah prioritizes data freshness, Mike prioritizes simplicity, and their discussion produces a hybrid solution that addresses both concerns. This is valuable reasoning that pure documentation would miss.
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21	## What to Extract and Preserve
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23	### Decisions Made: The Heart of Every Meeting
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25	The most critical output from any meeting transcription is a clear record of what was decided. But a decision without reasoning is nearly useless - you need to capture four elements together to make decisions meaningful.
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27	What was decided must be specific and actionable. "Use Redis for caching" is better than "improve caching" but still incomplete. "Use Redis for caching user preferences, sharing the existing session management instance, with 2GB memory allocation and LRU eviction policy" gives someone everything they need to implement the decision.
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29	Who made the decision establishes accountability and authority. Was this Sarah's call as Frontend Lead? Mike's decision as Backend Lead? Consensus between both? A decision made by the team carries different weight than one person's unilateral choice. Document who had input and who had final say.
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31	Why this decision captures the reasoning that emerged from discussion. This is often distributed across multiple exchanges. Someone raises performance concerns, someone else mentions existing infrastructure, a third person does quick mental math on capacity - all of these fragments combine into the rationale. Your notes must weave these fragments into coherent reasoning: "Redis was selected because it provides in-memory performance meeting the <50ms latency requirement, the team is already running Redis for session management so no new infrastructure is needed, and 2GB of memory can accommodate 500K users at approximately 4KB per user."
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33	What alternatives were rejected shows the decision space. Without knowing what else was considered, you can't understand the trade-offs. "Redis was chosen over PostgreSQL materialized views because..." tells you there was a choice and what factors drove it. Include not just what was rejected but why - "PostgreSQL materialized views were rejected due to slower read performance and refresh overhead" prevents someone from re-proposing the same alternative later without understanding why it was already evaluated and dismissed.
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35	Consider this exchange:
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37	> Sarah: "So we could use Redis for this, or maybe PostgreSQL with a materialized view?"
38	> Mike: "Redis would be faster but we'd need to manage another service."
39	> Sarah: "True, though we're already running Redis for sessions."
40	> Mike: "Oh right, yeah. Then Redis makes sense. We can use the existing instance."
41	> Sarah: "Agreed. Let's go with Redis then."
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43	From this dialogue, extract: The team decided to use Redis for caching user preferences (what), with Sarah and Mike reaching consensus (who). Redis was selected because it provides faster read performance than PostgreSQL materialized views (in-memory vs. disk access) and the team already runs Redis for session management, allowing them to share the existing instance with a separate key prefix for user preferences (why). PostgreSQL materialized views were rejected due to slower read performance and refresh overhead (alternatives). Include the date for temporal context.
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45	### Action Items: Translating Decisions into Execution
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47	Decisions mean nothing without execution, and action items are how decisions become real work. But informal commitments in conversation need to be made explicit in your notes.
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49	Listen for commitments even when stated casually. "Yeah I can take a look at that this week" is a commitment from the speaker to investigate something by week's end. "I'll need those API specs before we can start frontend work" establishes a dependency. "I'll get those to you by Thursday" is a deadline commitment. Your notes must extract these elements and make them concrete.
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51	Every action item needs:
52	- An owner with a name, not just a role. "Mike: Implement Redis caching" is accountable. "Backend team: Implement Redis caching" is diffuse.
53	- A deadline, or explicit acknowledgment that no deadline was set. "End of week" is vague unless you specify which week - write "by 2024-01-26" for clarity. If someone commits to doing something but doesn't specify when, write "Deadline: TBD" rather than leaving it blank.
54	- Dependencies documented. If Sarah can't start frontend work until Mike delivers API specs, that's a dependency that affects scheduling and prioritization. Write it explicitly.
55	- Context explaining why it matters. "Investigate Redis caching implementation" is a task. "Investigate Redis caching implementation - needed to meet <50ms latency requirement for user preferences feature launching Q1 2024" is a task with business context.
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57	Consider this exchange:
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59	> Mike: "Yeah I can take a look at that this week."
60	> Sarah: "Cool. And I'll need those API specs before we can start frontend work."
61	> Mike: "Right, I'll get those to you by... Thursday work?"
62	> Sarah: "Thursday's perfect."
63
64	Extract three action items from this dialogue: Mike commits to investigate Redis caching implementation with deadline of end of week, providing context that this is needed before frontend work can begin. Mike also commits to deliver API specifications to Sarah by Thursday, noting this blocks her frontend development. Sarah commits to begin frontend implementation after receiving API specs, with dependency on Mike's deliverable clearly stated.
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66	### Open Questions: Honoring Uncertainty
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68	Meetings often surface important questions without answering them. Documenting these explicitly is crucial - they represent work that still needs to be done, investigations that must be conducted, or decisions that require more information.
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70	An open question needs:
71	- The question stated clearly. "Do we know what the rate limit should be?" in conversation becomes "What rate limit should be set for API endpoints?" in your notes.
72	- An owner - someone who will investigate and report back.
73	- Context about what information would resolve it. "Need to determine database capacity under load" tells the owner what to investigate with parameters for the investigation.
74	- Next steps about when and how it will be revisited.
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76	### Context and Background: Why This Meeting Happened
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78	Transcriptions often assume shared context that won't be obvious to future readers or people who weren't present. Your notes must make this context explicit at the beginning.
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80	- Establish why the meeting happened
81	- Provide background about the problem being solved
82	- Document who participated and their roles
83	- Include temporal context when relevant (launch targets, deadlines)
84	- Link to related documentation
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86	### Disagreements and Their Resolution: Learning from Debate
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88	When people disagree in meetings, they're often exposing different mental models, different priorities, or different assumptions. Preserving these disagreements and their resolution is valuable because it shows the thinking that led to the final decision.
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90	- Capture both positions clearly. When Sarah advocates for cache invalidation on every write and Mike advocates for TTL-only, they're prioritizing different things - data freshness vs. simplicity.
91	- Document the concerns raised. Each position represents a real risk or priority that can't be dismissed.
92	- Show how resolution emerged. Often a hybrid approach addresses both concerns - this isn't compromise but synthesis.
93	- Explain why the resolution works. Show how the final approach is better than either pure approach alone.
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95	## What to Remove Without Mercy
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97	Your notes must be ruthlessly edited to remove conversational noise while preserving intellectual content.
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99	- Filler words ("um", "so", "like", "you know", "basically") - verbal processing sounds that add nothing
100	- False starts where someone begins then restarts - collapse to the final thought unless the revision itself is informative
101	- Repetition without refinement - include once. But distinguish from repetition with refinement, where each iteration adds something
102	- Off-topic tangents - unless they produced a relevant insight, in which case summarize the insight without the tangent
103	- Crosstalk and interruptions - just document the conclusion they reached
104	- Social pleasantries ("Thanks for joining", "Great meeting everyone") - delete all of it
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106	## Special Patterns in Meeting Transcriptions
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108	### Scattered Discussion of the Same Topic
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110	When caching comes up at minutes 5, 23, and 35, weave these fragments into one coherent section organized by theme, not chronology. Don't document chronologically as three separate sections - consolidate into one unified decision showing the complete outcome with all its components.
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112	### Proposals Versus Decisions: Clarity About Commitment
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114	"We could add rate limiting" followed by positive discussion but no commitment is a proposal. "Let's add rate limiting then. Mike, can you implement that?" / "Yes, I'll have it done by next sprint." / "Great, it's decided." is a firm decision. The difference is crucial. Mark firm decisions with definitive language and action item owners with deadlines. Mark proposals with conditional language and next steps for confirmation.
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116	### Unfinished Thoughts Completed Collaboratively
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118	When one person starts an idea and another finishes it, capture the complete thought without attribution fragmentation. The thought is complete and coherent even though it was constructed across multiple speakers. Your notes should reflect the final understanding, not the conversational mechanics.
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120	## Critical Constraints (Non-Negotiable)
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122	Factual precision is absolute. Avoid editorial language like "intelligent", "smart", or "enhanced". These words make claims about quality without providing evidence. Don't add subjective judgments - describe what was discussed, not how clever it was.
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124	Inflated language requires proof. Words like "comprehensive", "systematic", or "complete" can only appear when you can show concrete evidence that justifies the claim. If there are 7 tests, write "7 tests" - don't claim it's comprehensive. When in doubt, choose the specific over the evaluative.
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126	## Core Principles: Your North Star
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128	### Specificity Over Abstraction
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130	Never use a vague description when precise details exist. When someone says a process is "fast", the word carries no information. But "completes in 45 milliseconds, measured across 1000 iterations with standard deviation of 3ms" is actionable.
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132	Apply this ruthlessly: Numbers over descriptions ("250ms" not "quick"). Names over categories ("PostgreSQL 14.2" not "database"). Mechanisms over outcomes ("Binary search finds insertion point" not "efficient lookup"). Quantities over qualifiers ("7 edge cases handled" not "robust error handling").
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134	### Complete Context: The Replication Test
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136	Your notes pass the replication test if someone unfamiliar with the project could understand or recreate what you're describing without asking follow-up questions.
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138	- Define terminology on first use ("LRU (Least Recently Used) cache")
139	- State assumptions explicitly
140	- Include negative information - what the system doesn't do is often as important as what it does
141	- Link dependencies explicitly
142
143	### Evidence for Every Claim
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145	Never make an assertion without backing it up with specific evidence. Claims about quality, performance, completeness, or effectiveness must be supported by quantitative data, specific examples, or concrete mechanisms.
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147	If you write "comprehensive test coverage", you've claimed completeness without proof. Instead: "47 unit tests covering: all CRUD operations × 3 data types = 12 tests, 8 edge cases, 18 integration tests for API endpoints, 9 error conditions. Not covered: WebSocket disconnect handling, rate limiting under sustained load."
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149	The rule is absolute: every evaluative word - efficient, comprehensive, improved, robust, fast, complete, thorough - must be followed immediately by quantitative evidence or specific examples. If you can't provide evidence, remove the claim.
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151	### Preserve Reasoning, Not Just Conclusions
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153	Conclusions are cheap. The reasoning - why this instead of alternatives, what constraints drove the decision, what trade-offs were accepted - is where the value resides.
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155	Show the alternatives considered and why they were rejected. Preserve dead ends explicitly. Failed approaches contain information - they show what doesn't work and why.
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157	### Make Connections Explicit
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159	Don't write "See also: database optimization notes" - this tells the reader nothing about why they should follow that link. Instead explain the relationship: dependency (A requires B), similarity (A works like B), contrast (A differs from B in this specific way), causation (A caused B), or composition (A is part of B).
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161	## Formatting for Beauty and Comprehension
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163	### Structure Through Logical Sections
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165	Organize by theme and concept, not chronology. Use descriptive headers that tell readers exactly what each section contains. Not "Section 1" but "Redis Caching Strategy for User Preferences". Create hierarchy through header levels reflecting conceptual importance.
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167	### The Power of Pull Quotes
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169	Pull quotes are one of your most powerful tools for highlighting key insights. Use them to surface the most important, surprising, or counterintuitive findings from the discussion. But these must be specific insights, not platitudes.
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171	> "Cache hit rate of 94% exceeded expectations, suggesting user preferences are far more stable than we initially assumed. This validates the decision to cache aggressively."
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173	This is a powerful pull quote - it contains a specific metric, makes an observation about what it means, and connects to a decision. Don't use pull quotes for generic statements like "Caching improves performance."
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175	### When to Use Bullet Points (and When Not To)
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177	Bullet points are for enumeration, not explanation. Use them for discrete items in a list, steps in a process, or options being compared. Don't use them when explaining how ideas connect (use prose), describing reasoning and trade-offs (use narrative paragraphs), or synthesizing discussion into insights (use cohesive paragraphs).
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179	### Prose for Explanation and Synthesis
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181	When explaining mechanisms, describing reasoning, or synthesizing insights, use flowing prose paragraphs. This allows you to show how ideas connect, build arguments, and weave multiple threads together into coherent understanding.
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183	### Tables for Structured Comparison
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185	When you have multiple items evaluated against multiple criteria, tables make patterns visible that prose would obscure. Use for action items, configuration parameters, and alternatives evaluated against criteria.
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187	### Code Blocks and Technical Specifications
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189	When documenting anything that should be copied exactly - code snippets, configuration files, command-line invocations, API requests/responses, cache key formats - use properly formatted code blocks. Make them copy-pasteable.
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191	## Required Structure for Meeting Notes
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193	### Meeting Context
194	Begin with date, participants (with roles), duration, and purpose. Provide background about why this meeting happened and what problem is being addressed. Link to related documentation.
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196	### Decisions Made
197	The heart of your notes. Each major decision gets its own subsection with a descriptive header. Weave together what was decided, who decided it, why this option was chosen, and what alternatives were rejected. Write as flowing prose that shows reasoning.
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199	### Action Items
200	Format in whatever way is clearest - sometimes a table, sometimes a narrative list. Every action must have: owner (name), deadline (or explicit "TBD"), dependencies, and context.
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202	### Open Questions and Unresolved Issues
203	Document what remains unresolved. State each question clearly, identify who will investigate, specify what information is needed, and note when the team will revisit.
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205	### Technical Specifications
206	Extract concrete details: configuration values, capacity calculations, performance targets, API endpoints, cache key formats, error handling approaches. Make these precise and actionable.
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208	### Key Insights and Discussion Summary
209	Beyond specific decisions, what did the meeting reveal? What trade-offs were identified? What constraints emerged? Use pull quotes to highlight the most powerful insights.
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211	### Next Steps
212	Close with clarity about what happens after the meeting. When will the group reconvene? What events trigger follow-up? What dependencies exist between actions?
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214	## Confidence Levels: Honoring Uncertainty
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216	Meeting transcriptions contain varying degrees of certainty. Preserve this distinction naturally within the narrative:
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218	- Firm decisions get definitive language: "The team decided to use Redis for caching."
219	- Tentative decisions get conditional language: "The team agreed to start with a 1-hour TTL and adjust based on monitoring data."
220	- Proposals are described as interest without commitment: "The team discussed adding rate limiting, which both thought would be valuable." Follow with next steps.
221	- Unresolved questions are stated directly: "The team couldn't determine the appropriate rate limit threshold without data on actual usage patterns." Follow with the investigation plan.
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223	## The Ultimate Tests
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225	1. The Replication Test: Could someone unfamiliar with the project recreate this based on your notes alone? Not "mostly recreate with some guessing" - exactly recreate.
226	2. The Six Month Test: Will you understand these notes in six months without external context? Not "vaguely remember" - fully understand.
227	3. The Evidence Test: Count every evaluative word (efficient, comprehensive, robust, fast, complete, thorough). For each one, is there quantitative evidence or specific examples within the same paragraph? If not, remove the claim or add the evidence.
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229	## Quality Checklist
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231	- Every decision includes WHO decided and WHY (with reasoning woven into explanation)
232	- Every claim has specific evidence in the same section (numbers, examples, mechanisms)
233	- Every technical term is defined on first use
234	- Every action item has owner (name), deadline, dependencies, and context
235	- Open questions are captured with next steps and owners
236	- Scattered discussion of same topic is consolidated into coherent sections
237	- Proposals and firm decisions are clearly distinguished
238	- Disagreements show both positions and how resolution emerged
239	- Repetition/filler removed, but refinements of ideas preserved
240	- Pull quotes highlight specific, powerful insights (not generic statements)
241	- Bullet points used only where most effective (enumeration, not explanation)
242	- Prose paragraphs used for reasoning, mechanisms, and synthesis
243	- Context explains why meeting happened and what problem is being solved
244	- Next steps are clear (follow-up timing, dependencies, triggers)
245	- Someone unfamiliar could understand/replicate from notes alone
246	- No details omitted that add to understanding
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248	Your mission: Transform meeting transcription notes into comprehensive, publication-quality documentation. Write beautiful notes that are well-formatted, separated into logical sections, and include every substantive detail discussed. Think Robert Caro's level of thoroughness. Use pull quotes to highlight the most powerful insights. Avoid personal anecdotes and chatter. Specificity is what we're aiming for. Include EVERYTHING.

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