Why duties do not get interviews
Duty bullets fail at every layer of modern resume screening. They are interchangeable across candidates with the same job title and carry no differentiating signal. Eye-tracking research shows recruiters spend an average of 7.4 seconds on initial resume review, and quantified results catch the eye while duties blur. Hiring managers need evidence to predict performance delivery, and duty statements provide none. Research estimated 27 million qualified Americans get rejected by automated screening for reasons unrelated to actual ability.
The impact formula
Every bullet should follow a three-part structure: action verb + what you did + measurable result. The action verb signals ownership. The middle clause names the work. The measurable result anchors the bullet in something evaluable. This formula satisfies all three layers of screening simultaneously.
When a hard number is unavailable, use alternatives: scope, comparison, durability, recognition, or speed. Any of these is stronger than "responsible for."
Twenty before-and-after rewrites
Software engineering
- Before: Responsible for backend development and code reviews. After: Rebuilt the payments API, reducing transaction failures 42% and saving $180K annually.
- Before: Worked on the data pipeline. After: Shipped a streaming pipeline that processes 2M events/sec at sub-second p99 latency.
- Before: Contributed to mobile app features. After: Owned the iOS checkout rewrite that lifted conversion 18% and cut crash rate from 0.9% to 0.05%.
Marketing
- Before: Managed social media accounts and created content. After: Grew Instagram from 8K to 47K followers in 6 months, generating 340 qualified leads monthly.
- Before: Ran email campaigns. After: Designed a lifecycle email program that lifted conversion 31% and added $640K in pipeline per quarter.
- Before: Worked on SEO. After: Took the blog from 12K to 180K monthly organic visits in 18 months.
Sales
- Before: Responsible for meeting sales targets. After: Closed $2.4M in new ARR across 18 enterprise accounts, exceeding quota by 135%.
- Before: Managed customer relationships. After: Owned 22-account book worth $4.1M ARR with 118% NRR and zero churn over two years.
- Before: Used Salesforce. After: Rebuilt territory pipeline hygiene, lifting forecast accuracy from 62% to 91%.
Project management
- Before: Led cross-functional teams on multiple projects. After: Delivered three product launches on time and under budget, coordinating 24 engineers across 4 timezones.
- Before: Tracked project status. After: Reduced average project cycle time from 14 weeks to 9 by introducing weekly checkpoints.
Customer success
- Before: Handled customer accounts and resolved issues. After: Managed a 45-account portfolio worth $3.2M ARR with 96% retention and 1.2-day median resolution time.
- Before: Conducted onboarding sessions. After: Designed an onboarding curriculum that cut time-to-first-value from 22 days to 6 and lifted activation by 41%.
Operations / Finance
- Before: Reviewed monthly reports. After: Identified $1.1M in recurring vendor overbilling and recovered 12 months of overpayment in one quarter.
- Before: Worked on process improvement. After: Cut weekly close from 7 days to 2 by automating reconciliations across three payment processors.
Data / Analytics
- Before: Built dashboards. After: Replaced 14 manual reporting workflows with one self-service Looker model used by 90+ stakeholders weekly.
- Before: Analyzed customer data. After: Identified a churn signal four weeks earlier than existing alerts, retaining $780K in ARR in first six months.
Design
- Before: Designed product features. After: Led the redesign of onboarding, lifting day-7 activation 27% and cutting support tickets per new user by 38%.
- Before: Worked on the design system. After: Shipped a component library that reduced engineer-design rework time per ticket by 40%.
HR / Recruiting
- Before: Managed the hiring pipeline. After: Filled 38 roles in 12 months at a 4.2-week median time-to-fill with 89% offer acceptance and 94% one-year retention.
Why outcome bullets matter even more under AI screening
Keyword-based ATS systems only checked for token presence. Outcome-based models read the bullet itself and rank on what they find. Impact bullets are now the input used to decide if a candidate ranks in the top tier. Duty-list resumes score poorly because there is nothing to find. Impact-bullet resumes score well because the work is legible to the model.
How to rewrite your bullets in one sitting
Most candidates can convert their entire resume in 60-90 minutes by following the same loop on every bullet:
- Read the bullet aloud. If it could appear on the resume of any other person with the same title, it is a duty.
- Ask: what changed because I did this? Revenue, time, cost, scope, quality, retention, conversion, error rate.
- Add a number. If no exact number exists, use scope, comparison, or speed.
- Cut everything else. Action verb, the work, the result.
- Test against the seven-second scan. Check whether the number is what you remember.