Worked estimation examples

Real stories run through the estimation conversation end to end (login, payments, migrations, spikes), plus the questions to land before anyone votes a number.

A sticky-note character holding up an estimate card with a 3 on it, while a second one beside a login form points at a padlock and a password reset arrow.
Chapter 1Estimating a login feature

How to estimate a login feature: the hidden scope (password reset, 2FA, federation, rate limiting, sessions) and the questions to land before anyone votes.

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Chapter 2Estimating an SSO integration

How to estimate an SSO integration: the work lives outside your codebase, in the identity provider's quirks. The questions to answer before you vote a number.

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Chapter 3Estimating a payment integration

How to estimate a payment integration: sandbox vs live, refunds, webhooks, idempotency, PCI scope. The conversation that has to happen before any number lands.

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Chapter 4Estimating a search feature

How to estimate a search feature: relevance, ranking, faceting and who owns the index. The questions that turn 'add a search bar' into a real estimate.

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Chapter 5Estimating a notifications system

How to estimate a notifications system: channels, preferences, deduplication and delivery guarantees. Why 'send an email' quietly becomes a six-week project.

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Chapter 6Estimating a file upload

How to estimate a file upload: size limits, virus scanning, resumability, storage and retention. The drag-and-drop is the easy part; underneath is the ticket.

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Chapter 7Estimating a dashboard

How to estimate a dashboard: data sources, refresh cadence, time zones, drill-down, permissions. The chart is easy; the data pipeline behind it is the work.

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Chapter 8Estimating a flaky test

How to estimate a flaky test: why it's two estimates, not one, and why a time-box beats arguing about points when the answer depends on what you find.

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Chapter 9Estimating a bug with no repro

How to estimate a bug with no repro: you can't size the fix, only the search. How to time-box the investigation instead of voting on a story nobody can see.

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Chapter 10Estimating a performance regression

How to estimate a performance regression: the work is mostly diagnosis, not the fix. How to size it when the cause is unknown and an SLO is on the line.

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Chapter 11Estimating a customer-reported bug

How to estimate a customer-reported bug: the account on the ticket decides the size. How to separate the one-line fix from the response that eats the sprint.

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Chapter 12Estimating a database migration

How to estimate a database migration: backfill, lock duration, rollout and rollback. 'Add a column' is one line of SQL; the estimate is about the second clock.

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Chapter 13Estimating a data migration

How to estimate a data migration: moving data between systems, reconciliation and cutover. The transform runs in an hour; the cleanup runs for a quarter.

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Chapter 14Estimating a framework upgrade

How to estimate a framework upgrade: why a major version bump is a project, not a ticket, and how to break it into stories you can actually size.

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Chapter 15Estimating a dependency upgrade

How to estimate a dependency upgrade: the long-tail bump that hides N spikes in one ticket. Read the changelogs first, then estimate what you found.

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Chapter 16Estimating a CI/CD overhaul

How to estimate a CI/CD overhaul: pipeline work has no demo, so slice by what can be deleted. The quarter-long story that hides on the backlog as a refactor.

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Chapter 17Estimating a third-party API swap

How to estimate a third-party API swap: semantic gaps, dual-running and the assumptions baked into the old vendor's quirks. The new API only looks identical.

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Chapter 18Estimating a rate-limit rollout

How to estimate a rate-limit rollout: thresholds, dry-run periods, customer comms. The code is half a day; picking limits nobody complains about is the work.

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Chapter 19Estimating a design-system change

How to estimate a design-system change: token rollouts, deprecation paths, codemod coverage and the 200 call-sites that use the old component. Size the downstream.

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Chapter 20Estimating an accessibility fix

How to estimate an accessibility fix: a11y issues are features you didn't ship the first time. Why to size the class of problem, not the single instance.

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Chapter 21Estimating a feature-flag rollout

How to estimate a feature-flag rollout: staged percentages, kill-switches, gating metrics and the cleanup nobody schedules. A flag is a small product, not a deploy.

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Chapter 22Estimating a research spike

How to estimate a research spike: a spike is a time-box with a deliverable, not a story. How to keep it from quietly becoming the work it was meant to scope.

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Chapter 23Estimating a prototype

How to estimate a prototype: it's a deliverable sized for learning, not for use. How to keep the throwaway from becoming the production code nobody planned for.

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Chapter 24Estimating an ML experiment

How to estimate an ML experiment: it's research with engineering attached. The model is easy, the data is the work. How to size a budget, not a forecast.