Decode Your Insurance Policy: 1 — Set Up the Project
Scope the assistant as a research aid not a lawyer/adjuster; quote-the-clause and verify-the-statute discipline from the first move
Chapter X
Cards marked with a teaser are in the Vault. Unlock everything — $97, one time.
Scope the assistant as a research aid not a lawyer/adjuster; quote-the-clause and verify-the-statute discipline from the first move
Plain-English coverage summary, every claim-relevant clause quoted with why-it-matters, terms in your favor not yet mentioned
State-specific total-loss thresholds, ACV calculation, appraisal-invocation, each with statute named and a verify-it flag
Sourced timeline, gaps/contradictions flagged, missing evidence and what each piece would prove
Side-by-side net outcome of each settlement path with line-by-line math; ends with questions to pressure-test the offer
Factual, calm, firm written response grounded only in your documents; short email + formal long version with attachment lists
Role-play a trained adjuster pushing back, then drop character and coach where you were weak and what to say
decision scorecard (Data Tables)
Prompt 2. The Decision Scorecard (Data Tables feature) Generate this as a Data Table from the Studio panel. The value sits in the side-by-side comparison rather than in prose. Build a Decision Scorecard for the opportunities surfaced by the Income Opportunity Map on [TARGET COMPANY]. My constraints. Time budget: [HOURS PER WEEK]. Revenue target: [$]. Skills: [LIST]. Investment posture: [LONG-TERM / SHORT-TERM / NOT INVESTING]. Current sentiment: [CNN FEAR/GREED LEVEL]. Default scope: every opportunity from the Map. To narrow: [OPERATOR ONLY / INVESTOR ONLY / ONE QUADRANT]. Columns: - Opportunity - Trigger - Impact (1 to 5) - Effort (1 to 5) - Operator Quadrant (Quick Win / Strategic Play / Slow Burn / Money Pit) - Investor Read (Buy / Watch / Avoid / N/A) - Sentiment Adjustment (one sentence on how the current Fear or Greed reading sharpens or softens the call) - Earliest Action For each row, defend the Quadrant and Investor Read in one sentence using a source citation. Use only opportunities surfaced by the Map. Mark Investor Read N/A for operator-only signals and explain.
action playbook (Reports)
map income opportunities (Reports)
intelligence brief (Audio Overview)
shareable map (Infographic)
gather primary sources in one pass
map income sources + payer concentration
stress-test liquidity
trace who ultimately pays you
classify your tasks by expertise
hedge on the capital side
audit your demand footprint
design a second income stream
test your disintermediation risk
translate policy into money impact
autopsy the budget for leaks
connect costs across silos
map stakeholders to money risk
argue against your financial assumptions
audit meetings for wasted money
invest around the Nvidia/AI-demand story
capitalize on Claude-as-desktop-agent
capitalize on agentic phones
position around AI cybersecurity
barbell investment strategy on AI capex
evaluate a deal across financing structures
Prompt 2: The Deal Evaluator with Financing Structure Comparison Architecture: B (Structuralist) | Format: XML This prompt builds a complete financial model across multiple financing structures, because the same property can be a bad deal at conventional terms and a strong deal with alternative financing. Most investors never run this comparison. <context> I'm evaluating a specific investment property. Here are the details: Property address or description: [ADDRESS / DESCRIPTION] Listing price: $[AMOUNT] Property type: [SFH / DUPLEX / TRIPLEX / FOURPLEX / CONDO] Bedrooms/Bathrooms: [X/Y] Square footage: [NUMBER] Year built: [YEAR] Current condition: [TURNKEY / LIGHT REHAB / MAJOR RENOVATION] Estimated monthly rent (per unit if multi): $[AMOUNT] HOA or condo fees (if applicable): $[AMOUNT/month] Property tax (annual): $[AMOUNT] Insurance estimate (annual): $[AMOUNT] Renovation budget (if applicable): $[AMOUNT] </context> <task> Build a complete investment analysis across FOUR financing scenarios: SCENARIO A: Conventional 30-year fixed at 6.3%, 20% down SCENARIO B: Conventional with rate buydown to 5.5%, 20% down (estimate buydown cost as 2% of loan amount) SCENARIO C: DSCR loan at 7.0%, 25% down (qualify on property income, not personal income) SCENARIO D: All-cash purchase For EACH scenario, calculate: - Total cash required at closing (down payment + closing costs + buydown cost if applicable + renovation budget) - Monthly cash flow (gross rent minus ALL expenses) - Cash-on-cash return (annual net cash flow / total cash invested) - Cap rate (NOI / purchase price) - Break-even occupancy rate - 5-year equity position (principal paydown + 2% annual appreciation) - Debt service coverage ratio (for financed scenarios) Then produce a FINANCING VERDICT that identifies which structure produces the best risk-adjusted return for this specific property. </task> <constraints> - Use realistic expense ratios: Vacancy: 5-8% (use 8% for single-tenant SFH, 5% for multi-unit) Maintenance: 10% of gross rent (12% if property is pre-1980) Property management: 10% of gross rent EVEN IF self-managing (this reflects true economic cost and keeps analysis honest) CapEx reserves: 5% of gross rent - Flag every assumption you make - Do NOT present an optimistic-only scenario - Include a "What Could Go Wrong" section with three property-specific risks (not generic risks) - If any scenario shows negative cash flow, flag it immediately </constraints> <output_format> ## Investment Memo: [Property Description] ### Property Snapshot [Key details in compact format] ### Expense Model [Line-item breakdown with percentages and dollar amounts] ### Scenario A: Conventional Fixed [Full analysis] ### Scenario B: Rate Buydown [Full analysis, including whether buydown cost is recovered within the hold period] ### Scenario C: DSCR Loan [Full analysis, noting qualification advantages and rate premium] ### Scenario D: All-Cash [Full analysis] ### Financing Verdict [Which structure wins and why. If the answer depends on the investor's situation, specify the decision criteria.] ### What Could Go Wrong 1. [Property-specific risk with financial impact estimate] 2. [Property-specific risk with financial impact estimate] 3. [Property-specific risk with financial impact estimate] ### Final Recommendation [GO / CONDITIONAL GO / PASS] The single most important factor: [One sentence] </output_format> Why this works: The four-scenario structure reveals how sensitive the deal is to financing terms. Many investors eliminate strong properties because they only modeled one loan structure. The DSCR loan option matters especially for investors whose personal debt-to-income ratio makes conventional qualification difficult. The mandatory self-management cost prevents the most common investor delusion. Counters: Anchoring bias. By modeling four financing structures, the prompt disconnects “can I afford the monthly payment” from “does this investment produce returns worth the risk.”
macro + neighborhood investment intel
run a comparable market analysis
architect exit strategies
find how the deal breaks
find your differentiation angle
Prompt 1: Market position finder - identify your differentiation angle THE PURPOSE : Every real estate agent newsletter covers market stats and new listings. You need a positioning hook that makes readers subscribe specifically for your perspective. This prompt analyzes your market, expertise, and client base to find the unique angle that turns casual readers into people who won’t miss an issue. It eliminates the “why would anyone read my newsletter” paralysis by extracting the specific knowledge only you can provide about your territory. Copy and customize this prompt: I’m a real estate [AGENT/BROKER] in [CITY/NEIGHBORHOOD] launching a Substack newsletter to generate leads through expertise positioning. I need to find my unique market angle. My context: - Primary market: [SPECIFIC NEIGHBORHOODS OR BUYER SEGMENTS] - Years of experience: [NUMBER] - Client types I work with most: [FIRST-TIME BUYERS/MOVE-UP FAMILIES/INVESTORS/DOWNSIZERS] - Geographic knowledge advantage: [WHAT I KNOW ABOUT THE AREA THAT OTHERS MISS] - Questions clients always ask me: [LIST 3-5 RECURRING QUESTIONS] Analyze this information and create 5 potential newsletter positioning angles: For each angle, provide: 1. Positioning statement (one sentence: “The [NEIGHBORHOOD] newsletter that...”) 2. Content pillars (3 recurring themes I’d cover) 3. Reader avatar (who this attracts specifically) 4. Differentiation factor (why this beats generic market updates) 5. Search opportunity (what terms people would use to find this) Rank these angles by: - Sustainable content generation (can I write this weekly for a year?) - Authority demonstration (does this showcase my unique expertise?) - Lead quality potential (does this attract serious buyers/sellers?) - Competition level (how many others are doing this exact thing?) Select the top angle and explain why it creates the strongest positioning for lead generation.
hyper-local SEO content
Prompt 5: Neighborhood authority framework - own geographic search traffic THE PURPOSE : When someone searches “moving to [your neighborhood]” or “what to know about [school district],” you want your newsletter ranking first. This prompt creates hyper-local content strategies that capture geographic search traffic and position you as the neighborhood expert. You’re building SEO authority through depth, not breadth. One well-documented neighborhood beats shallow coverage of ten areas. This converts search traffic into subscribers who are already interested in your exact territory. Copy and customize this prompt: I need to dominate local search for [NEIGHBORHOOD(S) I SERVE] by creating hyper-local Substack content that establishes me as the territorial expert. My target neighborhoods: [LIST 1-3 SPECIFIC AREAS] My typical buyer questions about these areas: [LIST 3-5 QUESTIONS] Create my neighborhood authority content strategy: GEOGRAPHIC CONTENT PILLARS: For each target neighborhood, design 5 content categories that capture different search intents: 1. Moving/Relocation content (”moving to [neighborhood]”) 2. Lifestyle/Community content (”what it’s like to live in [neighborhood]”) 3. Education content (”[neighborhood] schools” or “school districts”) 4. Economic content (”home prices in [neighborhood]”) 5. Hidden knowledge content (”what locals know about [neighborhood]”) SIGNATURE NEIGHBORHOOD SERIES: Create 3 recurring series I can own: - Series name and description - Episode topics (at least 10 topics per series) - Search terms this captures - Why buyers value this information - How this positions me as the neighborhood insider SEARCH-OPTIMIZED CONTENT FRAMEWORKS: For each content pillar, provide: - 5 specific article headlines targeting search terms - Section structure (what each article covers) - Data sources (where to find supporting information: city websites, school data, census info, local news) - Photos/visuals that strengthen this content - Internal linking strategy (how to connect articles for SEO) DEPTH OVER BREADTH STRATEGY: Show me how to create 20+ pieces of content about ONE neighborhood that collectively establish unmatched expertise rather than shallow coverage of many areas. Include an update cadence: How to maintain and refresh this content quarterly so it stays current and continues ranking in search results.
turn subscribers into advocates
editorial calendar for search intent
ship first 5 issues that rank
conversion assets that qualify prospects
mine content from client conversations
rules for evaluating purchases
where better choices compound
categorize spend + opportunity cost
audit a medical bill (CPT/NCCI/upcoding)
audit a contract for compliance issues
validate financial service fees
optimize business expenses
benchmark vendor rates
define your wealth philosophy
model long-term financial scenarios
filter status spending from useful spending
track non-visible forms of wealth
AI teaches you to build a private retirement simulator in Python
5,000+ scenario retirement forecast + stress tests
balance money + time across causes
find local volunteer/board/donation needs
vet 3-5 effective nonprofits by your mission
skills-based non-monetary ways to contribute
define your giving values + target change
triple-attack: expenses + income + investing
beginner 3-fund + FIRE-optimized accounts
simple FIRE dashboard + course-correction triggers
FIRE number + years-to-FI + gap analysis
simple monthly/annual P&L from assumptions
plain-language whitepaper brief (problem/solution/goal/who)
does this project really need a blockchain?
team share, vesting, ROI red flags
competitors + key difference (need vs nice)
clear vs vague goals + biggest hurdle
complete fill-in spending analysis system
behavioral-economist analysis: patterns, triggers, 30-day reset
financial-detective pass for leaks, subscriptions, annual cost
market-rate comparison + negotiation scripts for bills
schedule bills around income, allowances, circuit-breakers
yes/no purchase criteria, waiting periods, opportunity cost
financial-therapist 5-7 question interview + trigger analysis
adds [INCOME OPTIMIZATION] — 'I need more income, not better budgeting.' Add this parameter to your prompt: '[INCOME OPTIMIZATION]: I need strategies
turn a meal plan into a sectioned, costed grocery list
maximize budget impact across categories
make shop-local sustainable
gift via small businesses, not Amazon
share finds to multiply impact
find local shops matching your values