How to Estimate Time for a Development Task?

At Peerlist, every Monday starts with a planning meeting. We line up everything: features, bugs, high-priority issues, user research. And the first question that always comes up in planning is “How much time will this take?”

Estimating time is hard for all of us. Even outside software, most people struggle to guess how long things will take. But in tech, time estimates impact everything, release cycles, launch dates, marketing campaigns, promotions. This can even block users.

One missed estimate and the whole system feels the ripple. And that's why you need to have a framework to find the time estimate!

Now, I get it, we will never be 100% accurate. But we have to be close. Because if you're a developer, you’ve probably said one of these:

“This should take 2 hours max.”

“Let me just write this function and push it tonight.”

Spoiler: you didn’t.

Estimation is a skill no one teaches you. But it’s one you will use every single day.

As someone who started by writing PHP scripts in a quiet corner of the internet and now leads an engineering team building Peerlist, I have learned (and unlearned) a lot about how to estimate tasks.

And the most important lesson?

You’re almost always wrong. But if you are usefully wrong, that’s a win.

Let’s break it down.

1. First things first: Don’t estimate time. Estimate unknowns.

Mostly devs jump into hours or days! That's a trap. This task sounds simple; I should be done with it in half a day! But you calculated this without understanding the implementation details of it.

So, before you put a number on anything, figure out:

• How many parts of the task are familiar vs new?

• Are there any integrations or dependencies (people, APIs, platforms)?

• Have you done something similar before?

The more unknowns, the more time you will burn just understanding the problem.

If something is entirely new, say a new SDK or you’re integrating a system you have never touched, your best guess is usually 3x off.

2. Break the task till it feels boring

Finding out the total time for a task at once is a failure loop. You are always going to miss one thing, and that will add the most amount of time.

But the solution to this problem is simple - Break big things to tiny tasks that you can easily estimate.

If you say "Build user login flow," that could mean 30 minutes or 3 days.

But if you say:

• Design login UI (30 mins)

• Hook up form validation (15 mins)

• Write API call and handle errors (1 hr)

• Set up JWT/token handling (45 mins)

• Test edge cases (30 mins)

Now you are dealing with boring building blocks. And boring is predictable. This will give you clarity and an early alert if something goes wrong.

3. Don’t forget “setup + stuck + slack”

This is where most developers (including past me) screw up. When you estimate something will take 2 hours, you’re thinking:

• “Code writing: 1 hour”

• “Bug fixing: 1 hour”

No buffer! No time for anything else!
But you will need some time to -
- Get back to the context (setup)
- Fix some silly bug you got stuck at (stuck)
- Cooling off time to breathe and think about what you are working (slack)

Rule of thumb: double your estimate. Not because you are bad at coding, but because you are bad at predicting the future.

4. Estimating with AI in the loop? New rules.

Things have changed.

We are no longer writing every single line. Tools like Cursor, Claude, and even auto-complete in your IDE can handle boilerplate, syntax, and even full function bodies.

But this adds a new layer: you still need to know what you are asking for. So now, clarity takes precedence over everything else!

AI can:

• Accelerate known tasks (e.g., regex, CRUD APIs)

• Help debug faster (if you ask the right thing)

• Reduce context switching by suggesting in place

But AI can’t:

• Read your exact product needs

• Handle edge cases without thinking about them

• Replace critical thinking in architecture or state management

So when estimating with AI:

• Known patterns? Cut your time by 30–50%.

• Unknown logic-heavy tasks? Add buffer.

Debugging AI suggestions sometimes takes longer than writing them yourself. So for AI, you will need clarity of execution, your prompts, and some debugging +
reviewing time too!

You can use AI to accelerate your development process, but you still need to consider all these factors for better estimates.

5. Always add a buffer for review and refactoring

Here’s a pattern I’ve seen in almost every developer (my past self included):
We think once the PR is up, the task is done.

I wish it were that simple. 🫠
Code that works isn’t code that’s done.

There’s still a lot left in the journey from “works on my machine” to “live in production.”

You need to account for:

• Code review feedback

• Small (but necessary) refactors

• Writing tests (yes, please)

• A useful commit message or changelog

• Thorough testing

• Final improvements after testing

This part is where most time estimates fall apart, because we forget to include it.
But we are not estimating when the code is written. We are estimating when the task is done, as in, shipped and usable by real users.

So your estimate has to include everything that gets you to production.

6. Bonus: Say it out loud

This is one of the most underrated tips.
A lot of people think it won’t make a difference, but I strongly disagree.

Before giving your estimate to a teammate, say it out loud:

“Okay, login flow - design, logic, auth, error handling… should be around 3–4 hours.”

Just speaking it forces your brain to walk through the steps.
If something sounds off, it probably is.

And if you are unsure, say that too:

“This part is new for me. If everything goes well, 3 hours. But I’m adding 2 more for the unknowns.”

That kind of honesty builds trust and saves you later.

Plus, when you say it out loud, others might instantly catch something you missed.
They will point out edge cases, dependencies, or past blockers, and you can course-correct before it's too late.

TL;DR (but don’t skip the thinking part)

• Estimate unknowns before estimating time.

• Break tasks until they feel boring.

• Add time for setup, stuck moments, and context switches.

• Use AI to accelerate, not over-trust.

• Always include review, test, and feedback loops.

• Say your estimate out loud to sanity-check it.

Estimation will always be a guessing game. But better guesses come from experience, pattern recognition, and self-awareness.

You won’t always be right. But with the right process, you will be predictably wrong. And that’s what makes you a reliable engineer, not perfection, but clarity.

Over time, you will end up building your own internal library of patterns:
“This kind of task usually takes longer than I think.”
“This integration always has hidden issues.”
“This teammate is great at flagging tricky parts. I should ask them before I commit to a timeline.”

AI tools can help accelerate your workflow, but they don’t replace your judgment. They amplify it. So the better your thinking, the better your outcomes.

So, whether you’re estimating for yourself, your team, or an entire product roadmap, take it seriously. Not rigidly, but intentionally. You will ship better. Communicate better. And you will sleep better 😅

Let me know how you estimate tasks, especially now, with AI in the loop. Would love to hear your approach, frameworks, or even the mistakes you have learned from.