Resume Bullet Rewrite Library
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32 curated before/after examples, one lesson each, with practical edit notes on every rewrite. No generic advice, every example shows the exact words that changed and why.
Grouped across 9 job areas.
Engineering
Helped → Co-built: Engineering Bullets Without Fabricating Seniority
Kept the 'contribution' framing (Co-built, not Led) so the candidate isn't claiming ownership they didn't have, but added a defensible scope detail and a specific window only this candidate can prove.
42/10084/100·anti-fabricationUtilized → Shipped: Frontend Bullets That Survive 6-Second Scans
Replaced 'Utilized' (the most over-used engineering AI verb of 2026) with 'Shipped', named the specific surface owned (search + filter on the candidate dashboard), and added the only number a frontend recruiter cares about: interaction latency.
34/10091/100·verb-swap-named-surfaceOptimized Performance → Cut p99 280ms: Backend Bullets With Proof
Replaced two filler nouns ('performance', 'overall system efficiency') with the actual query path, the actual percentile, and the actual remediation. Senior engineers always speak in p99 / p95, never 'overall efficiency'.
30/10093/100·specific-percentile-bulletsManaged Incidents → Cut MTTR 47%: SRE Bullets Without the Buzzwords
'Managed incidents' is the SRE equivalent of 'utilized React'. It could describe any job. The rewrite names the rotation size, the specific runbook rewritten, and the routing-rule count, all defensible in a 5-minute behavioural round.
32/10089/100·ops-domain-metricsDelivered Mobile Apps → 0.04% Crash-Free: iOS Bullets That Ship
Replaced two empty modifiers ('high-quality', 'robust') with the only number iOS leads track (crash-free sessions) and named the technical move (URLSession + structured concurrency) that produced it.
31/10087/100·named-platform-metricsBuilt ML Models → Shipped LLM RAG at 92% Helpfulness: ML Bullets
Three nouns added that only an ML engineer who shipped this could know: the architecture (RAG on GPT-5.4), the eval metric (helpful rating), and the live traffic volume (280k convos in 8 weeks). The original sentence could describe any data role.
29/10092/100·ml-eval-metrics
Product
Owned Roadmap → Killed 3 Bets, Shipped 4: Product Manager Bullets
Replaced 'multiple cross-functional teams' (the laziest PM AI phrase of 2026) with budget, team count, the kill-vs-ship ratio, and one outcome from the highest-impact bet. PMs who can quote a kill-rate are senior; PMs who only quote ships are juniors.
30/10091/100·pm-decision-portfolioLaunched Features → 64% WAU Adoption: PM Launch Bullets
Two PM AI clichés removed ('drive adoption', 'improve experience metrics'). Replaced with the feature name (scheduled-send), the cohort metric (% WAU), the time-to-adoption, and one downstream usage metric only the owner could pull.
34/10089/100·pm-adoption-metricsRan Experiments → 2.4 Wins/Mo: Growth PM Bullets
Growth PMs are graded on cadence + win-rate + compounding impact. The rewrite quotes all three. Generic AI writes 'ran experiments' and stops · junior tier.
33/10090/100·growth-pm-velocity
Design
Designed Checkout → +14% Conversion: Product Designer Bullets
Replaced two soft phrases ('user-friendly', 'collaborated closely') with the surface (checkout), the structural move (4→2 steps), and the only number a recruiter cares about (conversion lift, with sample size).
31/10090/100·conversion-design-detailBuilt Design System → 87% Component Coverage: Design Sys Bullets
Replaced three soft nouns ('consistency', 'velocity', 'product teams') with the three defensible facts: component count, surface-coverage %, and the build-time delta. The only outcome a design-system VP signs off on.
35/10088/100·platform-design-metricsConducted User Research → Killed a £400k Bet: UXR Bullets
Replaced two passive nouns ('research', 'decisions') with the study mix (generative + unmoderated), the sample size, and the only outcome that proves UXR value: a decision changed BEFORE engineering spent the money.
29/10091/100·research-decision-impactCreated Visual Identity → Shipped 240 Assets: Brand Designer Bullets
Brand-design bullets default to 'creative quality' · unverifiable. The rewrite trades polish-language for three defensible numbers: asset count, surface count, and adoption-team count within a specific time window.
33/10087/100·brand-design-scope
Data & Analytics
Built Dashboards → Killed 4 Hours/Wk of Manual Reporting: Analyst
Three filler phrases gone ('insights to stakeholders', 'data-driven decision making', plural 'dashboards'). Replaced with the tool, the user count, the cadence, the time saved, and the financial decision that flowed from the analytics.
32/10087/100·analyst-decision-impactBuilt Pipelines → Cut Snowflake £62k/Yr: Data Eng Bullets
Replaced 'scalable pipelines' (a phrase that means nothing in 2026) with the warehouse name, the £-saving, the pipeline count, the specific dbt patterns, and the warehouse-sizing detail. Data eng is graded on cost + reliability · quote both.
36/10092/100·infra-cost-bulletsBuilt Models → +£1.1M ARR From Churn Model: Data Science Bullets
Three vague nouns ('predictive models', 'customer outcomes', 'business strategy') replaced with the algorithm class, AUC, the operational workflow it landed in, the save-rate delta, and the £ARR attribution. Data scientists who can quote ARR attribution outrank those who only quote AUC.
31/10092/100·ds-causal-impact
Marketing
Leveraged Synergies → Cut CPL 31%: Killing AI Tells in Marketing Bullets
Every word in the original is an AI tell · 'leveraged', 'cross-functional', 'synergies', 'impactful', 'multiple channels'. The rewrite says exactly what changed and what it produced.
22/10089/100·ai-tell-removalDrove Content Strategy → 312% Organic Traffic: Content Bullets
Replaced two filler nouns ('brand awareness', 'audience engagement') with the only stack content marketers can defend: organic sessions, publish cadence, keyword intent, and the technical lever (internal linking).
32/10091/100·growth-marketing-numbersManaged Email Campaigns → 41% Open, 8.2% Click: Lifecycle Bullets
Two filler verbs gone ('managed', 'drove adoption'), replaced with the tool (Customer.io), the sequence length (7 steps), and the four numbers any lifecycle marketer must know about their own sends.
33/10089/100·lifecycle-stack-numbersLed Rebrand → +18pt Aided Awareness: Brand Marketing Bullets
Brand work is hardest to quantify, so the rewrite leans on the three facts brand teams CAN defend: surface count, budget envelope, and aided/unaided awareness tracker scores. Quoting the sample size (n=1,200) is the proof-of-rigour signal.
30/10088/100·brand-marketing-proof
Sales
Spearheaded → Led: The £1.8M Sales Bullet Rewrite
Replaced the ChatGPT-tell verb 'Spearheaded' with a result-first verb, added the actual ARR figure from the candidate's plan, and named the territory and quota attainment.
38/10092/100·verb-swap-outcome-firstManaged Accounts → 127% NRR: Account Manager Bullets That Sell
Replaced 'strong relationships' (unverifiable) with three defensible facts: book size (18 accounts), ARR band, and the operating motion (QBR cadence + 6 expansions). NRR is the one metric every revenue org screens for in 2026.
35/10090/100·post-sales-metricsGenerated Pipeline → £4.2M SQO in 6 Months: SDR Bullets That Hit
Four defensible numbers added: meeting count, time window, conversion rate, and ICP segment (mid-market FinServ). 'Strategic outreach' is the SDR-tier AI tell · recruiters now bin it on sight.
33/10088/100·top-of-funnel-numbersClosed Deals → Cut Cycle 38 Days: Enterprise AE Bullets
Two-cycle delta (142→104 days), deal count, ACV band, and one defensible tactical detail (the compliance audit pack delivered on a specific call). Enterprise sales leaders read tactical detail as proof of repeatable seller. Not luck.
36/10092/100·enterprise-ae-detail
HR & Recruiting
Fostered Diversity → Lifted Offer-Accept 16pts: HR Bullets That Land
HR bullets often default to soft language. The rewrite keeps the human focus but adds the two facts only this candidate can defend: team count and offer-accept delta over a specific window.
36/10090/100·qualitative-with-numbersFilled Roles → 24-Day Time-to-Hire: Talent Acquisition Bullets
Recruiter resumes are screened on three metrics: TTH, offer-accept, and source-mix. The rewrite quotes all three plus the role family (engineering) · generic AI never specifies which function the hires were in.
34/10089/100·ta-funnel-metricsImproved Onboarding → 90-Day Retention 84% → 94%: People Ops
Two AI nouns gone ('engagement programs', 'new hire success'). Replaced with the program length, the specific mechanics (buddy-pair, milestone checks), and the only retention metric People Ops gets paid on (90-day).
32/10088/100·people-ops-retention
Healthcare
Healthcare Bullets Without Inventing Numbers: A Truthful Rewrite
No invented percentages, no 'effectively' adverbs. The rewrite proves scope (3 wards, nights/weekends) and ownership (the named protocol). Both are details only this nurse can defend.
28/10082/100·qualitative-no-fabricationCoordinated Trials → Enrolled 142 Patients in 8 Months: Clinical
Clinical-research bullets default to 'supported' or 'coordinated' verbs with no scope. The rewrite names the trial phase, the protocol code, the site count, the enrolment number, and the schedule delta. All five facts are in the candidate's source data. They only need to surface them.
30/10091/100·clinical-research-detail
Finance
Built Forecasts → 96% Accuracy on £180M Plan: FP&A Bullets
FP&A roles are screened on plan size + forecast accuracy + cadence. The rewrite quotes all three plus the BU count and the cash-model cadence · five facts only the owner of the plan could surface.
36/10092/100·fpa-accuracy-bulletsManaged Close → Cut Close Cycle Day 8 → Day 4: Controller
Two filler verbs ('managed', 'ensured') replaced with the only three things controllers are graded on: close-cycle days, entity scope, and audit-finding count. Naming the tools (NetSuite + Blackline) signals stack literacy.
33/10090/100·controller-cycle-metricsBuilt Risk Models → Cut Fraud £820k/Yr: Risk & Fraud Bullets
Risk-and-fraud bullets must always quote BOTH detection lift AND false-positive impact · gains in one at the cost of the other are not real wins. The rewrite quotes both, names the fraud-type (CNP), and the transaction volume.
32/10093/100·risk-model-tradeoffs