How we learned to log bugs properly

Dat Nguyen — Thu, 30 Apr 2026 17:56:44 +0000

We weren’t slow at fixing bugs — we were slow at understanding them

In our previous post, we talked about a simple realization:

We weren’t slow at fixing bugs.
We were slow at understanding them.

That led us to a deeper question:

What does a “good” bug log actually look like?

⸻

Most bug reports fail before debugging even starts

A typical report looks like this:

“It’s broken”
“Webhook not working”
“App doesn’t respond”

From a user’s perspective, that’s completely reasonable.

But from a developer’s perspective, it’s missing everything we need:

Where did it happen?
What did the user do before that?
What failed exactly?
Can we reproduce it?

So the real process becomes:

Support asks follow-up questions
Devs try to guess
Time gets lost before any fix even begins

The problem isn’t debugging.

It’s the input we start with.

⸻

A useful bug is not a message — it’s a reconstructable event

After running into this repeatedly, we started thinking differently.

A bug report shouldn’t be something you read.
It should be something you can reconstruct.

At minimum, a useful log should answer:

Where did this happen? (URL / screen)
What failed? (request, error, response)
What led to it? (user actions, event sequence)
Under what conditions? (device, browser, network)
When did it happen? (timestamp)

Once you have that, debugging changes.

You’re no longer asking:

“What might have happened?”

You’re asking:

“Why did this specific sequence lead to failure?”

⸻

Why user-reported steps are not enough

One of the most fragile parts of debugging is reproduction.

We usually rely on:

users
or support teams

to describe steps.

But by the time that happens:

details are forgotten
steps are incomplete
or slightly inaccurate

Even small differences can make a bug impossible to reproduce.

⸻

Reproduction should come from the system, not memory

So we stopped asking users for steps.

Instead, we derive them from the actual session.

We look at what really happened:

page navigation
clicks and interactions
network requests
state changes

From that, we reconstruct a simplified sequence of events leading up to the issue.

Not a perfect script — but usually enough to trigger the same failure again.

That turns reproduction from guesswork into something much closer to replay.

⸻

Bugs are rarely universal

Another thing we kept seeing:

The same issue doesn’t affect everyone.

Sometimes it only happens:

on a specific browser
on a specific device
for a specific user
under certain network conditions

Without that context, bugs feel random.

With it, patterns start to emerge.

That’s why environment data matters just as much as the error itself.

⸻

What we actually log now

Over time, our logs evolved into something closer to a structured issue.

For each bug, we capture:

The failure itself

request URL
method
status code
response body

Where it happened

page URL
screen / feature

What led to it

sequence of user actions
navigation flow

The environment

browser
OS
device type
network conditions

When it happened

precise timestamp

Reproduction context

a reconstructed path to trigger the issue again

At that point, a bug stops being a vague report
and becomes something you can actually work with immediately.

⸻

What changed for us

The biggest shift wasn’t logging more.

It was logging the right things.

Before:

we had errors
but no context

Now:

we have context
and the error becomes obvious

We spend less time asking:

“What happened?”

And more time on:

“How do we fix it?”

⸻

What we’re still figuring out

Even with all of this, it still feels incomplete.

There are still cases where:

everything looks technically correct
but the outcome is wrong for the user

No error. No exception.

Just a mismatch between what the system did and what the user expected.

Those are harder to capture.

And it raises a bigger question:

What does a truly complete bug log look like?

⸻

If you’ve run into similar cases, I’d really appreciate your perspective.

We’re still building this and learning from real-world usage:
👉 https://flashlog.app

We weren’t slow at fixing bugs — we just didn’t understand them

Dat Nguyen — Wed, 15 Apr 2026 11:21:08 +0000

Most bug reports are useless. So I built this.

I used to think building an AI customer support chatbot would help reduce bugs. The idea was simple: if users could report issues easily through chat, we wouldn’t miss anything.

And at first, it actually worked. We started receiving bug reports faster, fewer things slipped through the cracks, and it felt like real progress.

But after a while, a different problem showed up.

Most of the reports… weren’t very useful. Users would say things like “it’s broken”, “button not working”, or “app doesn’t run”. We knew something was wrong, but we had no idea what they did before, where it happened, or how to reproduce it.

I remember one time our team spent almost 2 hours just trying to understand a single bug before we could even start fixing it. And it wasn’t a rare case.

Even worse, many issues were only reported after users got frustrated and left. By the time we saw the problem, the damage was already done.

That’s when it clicked for me. The problem wasn’t that we were slow at fixing bugs. We just didn’t understand them early enough.

Once I saw that, everything changed. We were already working with AI — chatbots, context handling, trying to understand user intent. So I started wondering: what if we applied the same idea to bugs?

Instead of waiting for users to describe issues (poorly), what if we could capture what actually happened?

So I built a small internal tool. It watches for errors in real time, captures the context around them, and turns that into something developers can actually act on — not just logs, but something closer to a ready-to-fix ticket.

The first time we ran it, it caught bugs before users even noticed them. More importantly, when a bug happened, we didn’t have to guess anymore. We knew what happened.

That’s how Flashlog started.

We’re still building and testing it with early users, improving it based on real-world feedback.

If you’re dealing with similar issues, you can try it here and let me know what you think.

Any feedback, brutal or not, is super valuable at this stage.

DEV Community: Dat Nguyen

How we learned to log bugs properly

We weren’t slow at fixing bugs — we just didn’t understand them

Most bug reports are useless. So I built this.