by Gary Worthington, More Than Monkeys

Estimation doesn’t have to be guesswork. It doesn’t have to drain your team or derail your sprints. But for that to be true, your team needs shared reference points.

That’s where golden stories come in.

Golden stories are examples of real work your team has done; clear, well-understood tickets that represent different levels of complexity. You use them as benchmarks for estimation, anchors for conversation, and a tool for reducing ambiguity.

This guide walks you through how to generate golden stories with your team and how to use them to improve sprint planning.

What Is a Golden Story?

A golden story is a canonical example of a 1-point, 3-point, 5-point, or 8-point task or whatever scale you use. It’s a story your team has actually delivered and agrees was:

• Well-scoped and fully understood at the time of estimation
• Delivered without major surprises
• A clean representation of a particular complexity level

These stories become calibration tools. Instead of estimating in the abstract, you estimate by comparison. The goal is not to be “right,” but to be consistently aligned.

Reminder: Points Are Not Time

Points are not hours, and they’re not meant to be.

A 3-point story doesn’t mean “half a day,” and an 8 doesn’t mean “two days” unless of course you want to lock your team into a brittle, misleading model that falls apart the moment something changes.

Points are a relative measure of effort, complexity, risk, and unknowns. That’s it.

You don’t need to convert them to hours because velocity does that for you. Once you’ve run a few sprints, you’ll know how many points your team typically delivers and can use this for sprint planning.

Trying to reverse-engineer time from points breaks the model. Use throughput, cycle time, and velocity to get your time-based metrics. Let points do their job: compare complexity, not clock time.

Step 1: Identify Real Stories You’ve Delivered

Start by looking at stories your team has completed in the last 1–3 months. Pull in a range of sizes. For each story, ask:

• Was it well-understood when we estimated it?
• Was the outcome close to what we expected?
• Would we be happy to use this story again as an example?

If so, tag it. You’re looking for 1 or 2 stories per size bucket that the team recognises and remembers.

Step 2: Curate Your Golden Set

From the candidates, pick five stories that cover a range of typical work. Here’s an example golden set you can use or adapt:

1. Reset password using email Size: 1
Standard form, known auth flow, no external dependencies.

2. View transaction history for past 6 months Size: 3
Pagination, simple backend filtering, light frontend changes.

3. Send notification when transaction exceeds £500 Size: 5
Involves thresholds, event triggers, and notification preferences.

4. Add new debit card to account Size: 8
Third-party API, PCI concerns, validation, retry logic.

5. Support agent impersonates a user Size: 13
Security-sensitive, requires permission control, auditing, and UI context switching.

You can display these on a Confluence page, in Miro, directly in your estimation tool or even on good ol’ fashioned index cards. Anywhere the team can access them during planning will do.

Step 3: Use Golden Stories in Sprint Planning

Whenever a new story comes in, don’t start with a number. Start with comparison:

• “Is this more complex than the transaction history story (3)?”
• “Is this smaller than the notification trigger (5)?”
• “Does it involve the same level of unknowns as the debit card integration (8)?”

Use these prompts to flush out uncertainty. If a story can’t be confidently compared to a golden one, it’s not ready. Split it, groom it, or spike it first.

Step 4: Maintain and Evolve the Set

Golden stories aren’t static. As your team grows, what used to be an 8 might become a 5. Every 1–2 quarters, revisit your set:

• Has anything changed in your architecture or tooling?
• Are your story sizes drifting?
• Are you frequently seeing work that doesn’t match any current example?

Update your golden stories based on real delivery, not abstract theory.

Why Golden Stories Work

They reduce ambiguity.
They speed up planning.
They build a shared sense of effort and complexity.

Estimation stops being a performance and becomes a collaborative calibration exercise. You don’t need to be precise. You just need to reduce the cost of being wrong.

Final Tip

Keep it lightweight. Don’t over-process this.

One of the fastest ways to improve estimation is to stop guessing in isolation and start comparing as a team. Golden stories give you the language to do that.

Gary Worthington is a software engineer, delivery consultant, and agile coach who helps teams move fast, learn faster, and scale when it matters. He writes about modern engineering, product thinking, and helping teams ship things that matter.

Through his consultancy, More Than Monkeys, Gary helps startups and scaleups improve how they build software — from tech strategy and agile delivery to product validation and team development.

Visit morethanmonkeys.co.uk to learn how we can help you build better, faster.

Follow Gary on LinkedIn for practical insights into engineering leadership, agile delivery, and team performance