InkProfit · Field Manual
Internal — Crew Only
Crew Field Manual · April 2026

The system changed.
This is how we change with it.

A10. COSMO. Rufus. Three quiet shifts that broke every SOP we wrote before 2025. This manual is our ground-up rebuild — domain by domain, account by account. Read it, run it, push back on it. This replaces nothing yet, but every SOP it conflicts with is on the rewrite queue.

For: Crew (Ads + Publishing teams) From: Zain Status: Living document Reading time: 40 min

Note to the Crew

If your accounts have been bleeding since March, it's not because you stopped doing your job. The job changed under us. Every team, every L-level, every niche — the same curve. February peak. March cliff. April keeps falling. That's the market, not you.

What is on us, starting now: 50% standard SOP, 50% reasoning from the new rules in this manual. If you run only the SOPs, you'll keep losing. If you run only your gut, you'll lose differently. Half and half. Test, log, escalate. Self-learning is now a KPI — see the Crew Learning Log.

I'm not going to write you a script for every account. I'm giving you the new rules. You apply them.

— Zain

Contents

  1. The Diagnosis — Where We Are
  2. The 2026 Shift — A10, COSMO, Rufus
  3. Publishing Crew Playbook
  4. Niche Research
  5. Book Creation
  6. Cover & Design
  7. Listing Details (SOP Rewrite)
  8. A+ Content
  9. Video Ads & Sponsored Brands
  10. Ads Crew Playbook
  11. Targets & Breakeven Math
  12. Campaign Architecture
  13. Bids & Placement Modifiers
  14. External Traffic & BRB
  15. Optimization — What's Outdated
  16. OPT Log Fix
  17. SOP Rewrite Queue
  18. Crew KPIs & Learning Log
  19. Glossary & Reference
01 — DIAGNOSIS

Where the portfolio actually stands

A clean look at what changed across our book of accounts, drawn from the STS sheet through April 2026.

Daily royalty average — Feb peak to April

AccountFeb avg/dayMar avg/dayApr avg/dayACOS Feb→Apr
Amelia$1,036$279$18752% → 35% → 69%
PWY$410$133$12132% → 35% → 52%
FLE$266$120$14052% → 54% → 77%
Gaurav$270$117$11158% → 67% → 80%
Dan$237$119$10237% → 39% → 51%

Critical accounts

RHEA — ACOS
164%
Spending $1.64 to make $1. Pause non-branded immediately.
GAURAV-2 — ACOS
213%
Worse than RHEA. Likely listing/category misfit.
GOS — ACOS
88%
Recoverable with placement audit + intent-layer rebuild.
Aaron + Mitchell
$0
Royalty $0 vs $1–2K spend. Attribution or category broken — investigate before any bid moves.
Pattern: the drop is uniform across managers, niches, portfolios. Romance, mental health (FLE), finance, kids, reference, fiction — all the same curve. That kills the "operator error" hypothesis. It's the system that changed.
02 — THE SHIFT

What actually changed under us

Three layers got rewritten. Most of our SOPs are still A9-era. That's the gap.

Layer 1 — A10: the new ranking core

A9 was simple: bid × relevancy × velocity. A10 layered three new pillars on top:

Layer 2 — COSMO: intent inference

COSMO is the knowledge graph under search and ad delivery. It infers why someone is searching, not what they typed. "Book for anxiety in teens" and "anxiety book teens" are now different audiences, eligible for different ads. Match types still exist — but they sit on top of intent matching. Broad match in 2026 is a semantic engine, not a fuzzy-string engine.

Layer 3 — Rufus: the AI shopping interface

Rufus mediates 15–20% of mobile queries and ~38% of Black Friday 2025 sessions. Rufus reads your listing — title, description, A+ text, reviews — to answer the buyer's question. Rufus-mediated clicks convert ~3.5× higher than search clicks because the AI pre-qualifies intent. If your listing reads like a keyword soup, Rufus skips you. If it reads like a clear answer, Rufus lifts your sentences.

The bottom line for the Crew: the system used to reward density. It now rewards clarity, intent match, and external pull. Our ad accounts are not broken. Our doctrine is.
03 — PUBLISHING CREW

Build the book the algorithm can read

Publishing flow needs a rebuild for an AI that summarizes (Rufus) and an algorithm that infers (COSMO). Walk every step.

Niche Research

The "low-comp keyword + generic book" era is dead. COSMO clusters readers by intent, not keyword. Specificity is now a moat.

What's working in 2026

Niche signalVerdictWhy it matters for us
Bold & Easy coloringGoBiggest growth trend since late 2024. Still scaling. Test on accounts with kids/leisure portfolios.
Wellness journals with promptsGoFLE territory. Guided prompt journals outsell blank consistently. Push into burnout/anxiety sub-segments.
Cottagecore / cozy micro-nichesGo<200 books per sub-theme, $500–3K/mo realistic. Good early-stage account fit.
Personal finance — system-basedGoReaders reject "get rich" framing. Specific systems (debt, budgeting, sinking funds) win.
Educational layered workbooksGoRepetitive low-content is dying. Layered complexity holds dwell time and review depth.
Generic lined journals / blank notebooksAvoidIf we're still publishing these on any account, stop. No semantic anchor for COSMO.
Mass AI-generated fictionAvoidRufus reads reviews. Bad AI fiction gets shredded fast and the signal kills rank for the whole pen name.
Generic "self-help" without a problem hookRiskyWithout a specific reader problem, COSMO can't cluster you. You bid against everyone — see RHEA.

Niche Research Checklist (replaces ad-hoc niche selection)

  • Define the reader in one sentence: audience + problem + outcome. If you can't, stop here.
  • Run 5 Rufus queries from the reader's POV. Note which titles surface and what language Rufus uses to describe them.
  • Pull top-10 BSR competitors. Read review text — extract the actual language readers use. That language becomes our title and description vocabulary.
  • Map demand depth: 3 distinct sub-problems the book can solve, not 1 search term.
  • Validate category traffic with Publisher Rocket. Avoid ghost categories.
  • Confirm 12-month sales trend, not just 30-day. Avoid temporary spikes.
  • Log into BTS doc before any cover/design work begins.
Do
  • Pick a sub-niche with one identifiable reader profile
  • Read reviews to learn the reader's language
  • Validate with a Rufus question
  • Check 3 sub-problems before committing
Don't
  • Chase the broadest keyword in the category
  • Build for "everyone interested in X"
  • Trust BSR alone
  • Enter a niche where top-10 all have polished A+ and 1K+ reviews

Book Creation

Rufus reads inside your book — Look Inside, sample reads, review-mined themes. The current SOP "Write a Book Using AI" is solid for outline-driven generation but needs updates for Rufus-readability.

What Rufus rewards inside the book

Update to "Write a Book Using AI" SOP

Current SOP says: research → competitor analysis → outline → chapter-by-chapter generation. Add these steps:

  1. Step 2.5 — Reader-language extraction. Pull 30 review snippets from competitor books. Build a phrase bank. Use this language in the book itself, not just metadata.
  2. Step 4.5 — Rufus-readability pass. After outline, ask: "Can each chapter answer 1 specific reader question?" Rewrite if not.
  3. Step 6 — Humanize pass. Use the existing "How to Humanize AI Written Text" SOP. NLP layer down-weights stilted text. This is now mandatory, not optional.
  4. Step 7 — AI disclosure. Per Amazon's 2025+ policy, AI-assisted content must be disclosed in KDP form during upload. Non-disclosure risks suspension.
Do
  • 2-page hook before any preface
  • Descriptive chapter titles ("How to fall asleep when your mind won't stop")
  • Include "what you'll learn" or "what to expect" section
  • End each chapter with a one-line takeaway
Don't
  • Skip the humanize pass on AI-generated content
  • Use clever-but-vague chapter titles
  • Pad with filler — Rufus and reviewers both notice
  • Skip AI disclosure on KDP upload form

Cover & Design

Cover hits the human before the algorithm. CTR feeds dwell-time and conversion signals downstream. Weak cover punishes everything.

2026 cover trends actually winning

Cover Test Checklist (mandatory before going live)

  • Title readable at 200px thumbnail? If not, redo.
  • Genre signaling correct in 1 second?
  • Tested vs 5 top-10 competitor thumbnails side by side?
  • Mobile thumbnail rendered (70%+ of buyers are on mobile)
  • 3 versions evaluated by author + 1 second eye before lock-in
  • Logged in BTS doc with version history
Cover heuristic: if it only works at full size, no one clicks it on mobile. If it only works at thumbnail, paperback buyers pass. Both must work.

Listing Details — Rebuild of the SOP

Our current Listing Details SOP covers 9 elements: Title, Subtitle, Author, Keywords (PB/HC + Kindle), Categories (PB/HC + Kindle), Description, HTML Description (Book Beam), Book Blurb, A+ Content. The structure is right. The logic inside it is A9-era. Specifically: the keyword approach uses variant stuffing, which now wastes slots.

The current SOP example for "Ramadan":
ramadan bedtime stories for kids / ramadan stories for children / ramadan books for kids / ramadan tales for kids / islamic stories for children
Five slots, one intent. Under COSMO, these all collapse to a single semantic cluster. We're paying for 5 slots and getting 1.

The new 7-slot logic — one intent angle per slot

Each slot must target a different angle. Same Ramadan book, redone:

SlotIntent angleExample phrase
1Reader problem / outcome"teach my child about ramadan"
2Audience age / format"picture books for muslim toddlers"
3Trope / theme"family-centered islamic traditions"
4Occasion / use-case"ramadan gift for nieces and nephews"
5Comparable / category context"goodnight moon style for muslim kids"
6Specific value / benefit"teach gratitude through stories"
7Long-tail problem search"how to explain fasting to children"

Title formula — internal standard

[Outcome / Problem] + [Format] + [Audience]

Bad: "Anxiety Workbook"
Better: "The Anxiety Workbook for Teens: 12 Weeks of Guided Exercises to Quiet a Racing Mind"
Total title + subtitle ≤ 200 characters. NLP layer flags unreadable, stuffed titles. If a human wouldn't say it, the algorithm down-weights it.

Description — write it for Rufus

Every sentence in the description should be liftable by Rufus to answer a shopper question. Specific claims, clean sentences, zero stuffing.

Do
  • Open with the reader's problem in their own words
  • Short paragraphs, clean HTML formatting
  • 5–7 specific lift-able claims
  • Audience signal ("for X who struggle with Y")
  • Confident outcome line at close
Don't
  • Stuff every sub-keyword variant
  • Vague hype ("the most powerful book ever written")
  • Open with author bio or accolades
  • ALL CAPS marketing lines
  • Block-paste keywords at the bottom

Categories — the 3-slot rule

SlotStrategyGoal
1Broad parentCredibility, foot traffic
2Mid-competition sub-categoryReachable BSR rank
3Tight niche where we can rank top-20Bestseller badge eligibility

Watch ghost categories — appear in browse menu but get zero browse traffic. Validate with Rocket category traffic data before committing.

A+ Content

A+ was a "nice to have" under A9. Under A10/Rufus it's a primary ranking and AI-feeding asset. Books with A+ see ~12% higher conversion. Rufus actively scrapes A+ text modules. Image-only A+ is now leaving money on the table.

The 6-module A+ structure (new internal standard)

  1. Hero banner. One line: reader's problem + book's promise. Image with text overlay.
  2. "Who this is for." 3–5 specific reader profiles. Lift-able by Rufus.
  3. "What's inside." Concrete TOC preview or 5 chapter highlights with one-line outcomes.
  4. Author credibility. One short paragraph. Specific, not braggy.
  5. "Frequently asked." 4–6 reader questions answered in plain text. This is the goldmine for Rufus.
  6. Closing CTA. Series cross-sell or "read sample" prompt.
Do
  • Text-rich modules — Rufus needs words to scrape
  • Specific FAQ section
  • Comparison tables when relevant (this book vs others by same author)
  • Reader profile descriptions
Don't
  • Image-only modules with text baked into image (Rufus can't read it)
  • Repeat description verbatim
  • Generic stock photos with zero info
  • Skip A+ on backlist titles — they need it most

Video Ads & Sponsored Brands

SB Video is one of the highest-leverage formats we under-use. Custom-image SB ads get 48% higher mobile CTR than product-only. Video pulls dwell time and pre-sells intent before the click.

The 5-beat video script — internal standard

  1. Hook (0–2s): Reader's specific problem as question or pain point. No "Hi I'm…"
  2. Promise (2–6s): What the book gives them. One outcome.
  3. Proof (6–14s): Visible book pages, A+ glimpse, or single review quote on screen.
  4. Differentiator (14–22s): What this book does that the next 5 search results don't.
  5. CTA (22–30s): "Read the sample. Decide in 5 minutes." Confident, no pressure.

Video Production Checklist

  • Vertical AND horizontal cuts (mobile vs desktop)
  • Captions baked in (most plays are silent)
  • Cover hero shot in first 2 sec and last 2 sec
  • No copyrighted music — Amazon will reject
  • ≤30 seconds
  • One clear CTA
  • Logged in BTS doc with cuts + market versions
Eligibility: SB requires Brand Registry or Author Page with sales history. Any account doing >$2K/mo royalty without SB unlocked = priority unlock task this week.
04 — ADS CREW

Run ads against intent, not match types

The auto + broad + phrase + exact mining structure that worked under A9 leaks money in 2026. COSMO already does the matching. Our job: organize intent, control placement, feed external pull.

Targets & Breakeven Math

Stop setting ACOS targets by feel. Set by math.

Breakeven ACOS = Royalty per sale ÷ List price

$5.14 royalty on a $12.99 paperback = 39.6% breakeven. Anything under is profit. Anything over is paying Amazon to take readers. Run every account at its breakeven, not "industry average."

ACOS bands by stage

StageTargetStrategy
Launch (0–60 days)+10–20% over breakevenBuy rank, feed velocity. Loss leader by design.
Growing (60–180 days)≈ breakevenHold rank, build review base.
Mature (180+ days)−10–20% under breakevenProfit phase. Cut underperformers, double on winners.
Series book #2+Higher than breakeven OKRead-through pays back the loss. Track series LTV separately.

2026 industry average is 32–35% ACOS. Top performers hold 23–26%. RHEA at 164% and GAURAV-2 at 213% are far past the threshold where bid tuning matters — those are listing/category problems, not ad problems.

Campaign Architecture — Intent Layers, Not Match Types

Old: one campaign per match type. New: one campaign per intent layer, match type as a control inside.

LayerTargetsBid postureACOS expectation
ProblemReader pain / outcome KWs ("how to sleep with anxiety")Aggressive — highest intentBelow breakeven
CompetitorCompeting author/title KWs + ASIN targetingModerate — defensiveAt/below breakeven
BrandedAuthor name + previous titlesDefensive minimumLowest ACOS, profit core
Generic / HeadBroad category terms ("self help," "romance")Cap-and-controlHighest, often unprofitable alone

Match types still matter — but as control layers, not the organizing principle. Exact for proven phrases, phrase for testing, broad sparingly with negative-keyword rigor (because COSMO is now doing the matching for you).

Do
  • One campaign per book per intent layer
  • Separate ebook / paperback / hardcover campaigns
  • Tag every campaign name with intent layer (e.g. "PWY · Book01 · Problem · Exact")
  • Aggressive negative keywords at ad-group level
Don't
  • Run "auto + manual" as your only structure
  • Mix Problem and Generic KWs in one ad group
  • Bulk-add 200 KWs to one campaign
  • Use account-level negatives for situationally bad terms

Bids & Placement Modifiers

Most of our SOP work is on bids. The math has changed and most operators get this wrong.

Final CPC = Base bid × Dynamic adjustment × Placement multiplier

$1.00 base × Dynamic Up & Down (max 100% TOS) × 50% TOS multiplier = $3.00 effective CPC. Operators forget this. One keyword burns the daily budget and they wonder where the spend went.

Bidding strategy by stage

StageBiddingPlacementWhy
LaunchDynamic Up & DownTOS +25–50%Buy velocity. Algo rewards conversion-likelihood with up-bids.
ScaleDynamic Up & DownTOS +20%, PP +20%Stack what works. Watch compounding burn.
StabilizeDynamic Down Only0% on losers, +20% on winnersCut waste. Down-only stops Amazon over-bidding shaky placements.
Defend (branded)Fixed Bids, lowLow TOSDon't need Amazon to optimize the author's name.
Action item for the L1s: Pull placement reports for RHEA, GAURAV-2, GOS this week. I expect to find 30–60% of spend on a placement that hasn't converted in 30+ days. Zero out those modifiers before any bid changes.

External Traffic & Brand Referral Bonus

A10 weighs an external sale ~3× an internal click in rank. Almost no account in our book sends external. This is the single biggest unfair-advantage gap we have.

Brand Referral Bonus (BRB)

Brand Registry-enrolled accounts get ~10% of sale price credited back on sales driven from external traffic via Amazon Attribution tags. Stack with the 3× rank lift and external traffic becomes our single highest-leverage move.

External Traffic Setup Checklist (per account)

  • Brand Registry enrolled (or pending via IP Accelerator if trademark filing)
  • Amazon Attribution tags created for every external channel
  • One landing page per book (not just an Amazon link) for tracking
  • Pinterest + email at minimum — both evergreen, low-cost
  • TikTok/Reels for romance/fantasy/YA fiction accounts
  • BookFunnel/StoryOrigin newsletter swaps for series
  • Tracking dashboard: external CPC vs Amazon CPC vs BRB recovered
Compliance: Amazon prohibits combining BRB and Amazon Associates affiliate links on the same click. Pick one. BRB is almost always better economics for first-party books.

Optimization — What's Outdated, What to Try

Auditing our actual SOP behaviors against 2026 reality. The audit:

Tactics to retire

TacticStatusWhy retire
The 5-minute campaign pauseMythNo evidence Amazon "resets" anything in 5 min. Post-pause "boost" is regression to mean. Stop building SOPs on it.
Auto-only or auto+manual default structureOutdatedCOSMO does the matching. Intent-layered campaigns outperform mining-from-auto.
Bid-only optimization (raise/lower 10% weekly)OutdatedIgnores placement compounding. Tuning the wrong knob.
Image-only A+ ContentOutdatedRufus can't read image text. Invisible to AI summarization.
Variant-stuffed backend keywordsWasteful5 slots collapsing to 1 intent. Lose 4 slots of reach.
Same campaigns for ebook + PB + HCOutdatedDifferent price points, different reader behavior, different breakeven.
"Industry average" ACOS targetsLazyUse breakeven math. Industry average is irrelevant to our P&L.
Aggressive broad without rigorous negativesBleedingCOSMO broad-matches on intent. Without negatives, we spend on synonyms we never wanted.

What to try — high-leverage moves

MoveDifficultyExpected lift
Rewrite description for Rufus-readabilityLow5–15% conversion lift
Convert A+ to text-rich 6-module structureMedium10–20% conversion lift
Re-bucket campaigns into 4 intent layersMedium10–25% ACOS reduction
Audit placement modifiers, set winners onlyLow5–15% ACOS reduction in 2 weeks
Set up Amazon Attribution + 1 external channelMedium3× rank lift on external + 10% BRB
SB video for top 3 books per accountMedium2–4× CTR vs product-only
Dayparting on top-spending campaignsLow5–10% ACOS reduction
Search Term Report → 100+ new KWs/quarterMediumUp to 4× sales scale (case-dependent)
Trope-clustered KW expansion (fiction)Medium10–25% reach lift on series

New Weekly Optimization Checklist (replaces current bidding-focused one)

  • Pull Search Term Report — add 5+ new KWs, 3+ new negatives per book
  • Review placement-level performance — adjust modifiers (NOT just bids)
  • Check breakeven ACOS vs actual — adjust targets where breakeven changed
  • Review external attribution — track BRB recovered vs spent
  • Spot-check 1 listing per week for Rufus-readability (read description aloud)
  • Review one A+ Content asset for text-richness
  • Audit dayparting performance — pause hours with consistent loss
  • Log what was tested + result in your weekly Crew Learning Log

OPT Log Fix

The OPT Log shows L1 optimization activity. Hassaan's L1s have been logging 60–85% non-optimized days (0️⃣) on 7 accounts. That's the biggest single avoidable bleed in the book right now.

New OPT Log rules

  1. 3 consecutive 0️⃣ days = automatic L-level escalation review. If L1 can't run optimizations 3 days in a row, the account is reassigned or the L1 needs L2 supervision.
  2. Optimization log entry must include the intent layer and placement changed. "Adjusted bids" is not a valid log entry.
  3. Weekly placement-modifier audit is now an L1 deliverable, not optional.
  4. Search Term Report harvest is logged separately — minimum 5 new KWs and 3 new negatives per account per week.
  5. Listing-side flag — if L1 sees ACOS >100% for 7 days, escalate to publishing crew for listing audit before bid changes.
  6. Crew Learning Log entry per week per L1. No log = optimization isn't measurable.

SOP Rewrite Queue

Concrete list of what's getting rewritten and the priority. Anyone can pull a P0 — assignment in the next sync.

SOPPriorityWhyOwner
Bidding SOP (Asana 1209509081406353)P0Uses A9-era Ad Rank formula. L1s execute it daily. Every day costs us money on RHEA / GAURAV-2.Zain + Inam
Listing Details SOP (Asana 1210283955451775)P0Variant-stuffing keyword logic wastes 4 of 7 slots. Highest-volume SOP. Touches every new title.Inam
Level 1/2/3/4 SOP (Asana 1208779988398298)P0Defines what each L-level does daily. Currently anchored to A9 doctrine. Every team member runs against this.Zain
Amazon Features Update April 2024P12-year-old. Replace with rolling 2026 update doc.Zain
Write a Book Using AIP1Add Rufus-readability + humanize + AI-disclosure steps.Publishing crew
A+ Content + Video Ads ExampleP1Replace with text-rich 6-module structure + 5-beat video script.Publishing crew
OPT Log doctrineP1New rules above need to land in actual OPT Log doc.Hassaan + Inam
NEW — Placement-Modifier Audit SOPP0Doesn't exist yet. Highest-leverage missing SOP.Zain to draft
NEW — External Traffic + BRB Setup SOPP1Doesn't exist. Biggest unlock for accounts >$2K/mo.Zain to draft
NEW — Crew Learning Log doctrineDoneTemplate already drafted. Roll out next sync.Crew

Crew KPIs & Learning Log

Self-learning is now a measured KPI, not a soft expectation. The Crew Learning Log template is the mechanism — every Crew member fills it out weekly.

The 9 KPIs we actually grade on

  1. Optimization rate — % of working days with logged optimizations (target: ≥85%)
  2. Test rate — # of hypothesis-driven tests logged per week (target: ≥1 per L1, ≥2 per L2+)
  3. Negative-KW additions per account per week (target: ≥3)
  4. New-KW additions per account per week (target: ≥5)
  5. Placement audit completion (target: weekly, all accounts)
  6. Listing-flag-to-publishing hand-off speed (target: same week as flag)
  7. External traffic setup — # of accounts moved from 0 channels to 1+ (target: 2/quarter per L2+)
  8. Learning Log quality — does the entry show reasoning, not just activity (graded subjectively in 1:1s)
  9. Self-flagged questions — Crew bringing 2+ specific questions per week (target: yes; zero questions = stuck and hiding it)
The 50/50 rule, restated: 50% standard SOP, 50% reasoning from the new rules. If your week was 100% SOP, you're not learning. If it was 100% improvising, you're not running the standard. Both fail.
05 — REFERENCE

Glossary & Reference

A9 vs A10

A9 was Amazon's product ranking algorithm from ~2014–2024, weighted on bid × relevancy × sales velocity. A10 (2024–present) added semantic relevance, external traffic quality, and engagement depth as primary pillars.

COSMO

Amazon's commonsense knowledge graph that infers user intent from co-buy and search-buy behaviors. Powers Rufus and the broad-match layer in advertising.

Rufus

Amazon's conversational AI assistant. Mediating 15–20% of mobile search queries. Reads listings to answer shopper questions. Rufus-mediated clicks convert ~3.5× higher than search clicks.

Brand Referral Bonus (BRB)

Amazon program crediting ~10% of sale price back to brand-registered sellers for sales driven from external traffic via Amazon Attribution. KDP-eligible if Brand Registry enrolled.

Breakeven ACOS

The ACOS at which ad profit is zero. Royalty per sale ÷ list price. Above = paying Amazon. Below = profit.

Intent layers (Problem / Competitor / Branded / Generic)

2026 replacement for match-type-first campaign structuring. Organize by reader intent, control match type within.

Placement modifier compounding

Final CPC = Base × Dynamic × Placement. $1 × 2× Dynamic × 1.5× TOS = $3 effective. Common cause of unexplained budget burn.

External reading (for the curious)

Internal references

One last thing

This manual is a living document. If something here doesn't match what you're seeing in the data on your accounts, that's not a problem — that's the entire point. Tell me. The fastest way to improve this is for the Crew to push back on it with real account evidence.

If a section costs you a sale, I want to know in the next 1:1.

We figure this out together or we lose together. I'd rather the first one.

— Zain