DEV Community: Michele

# We Built Technology to Save Time. Why Are We Busier Than Ever?

Michele — Tue, 03 Nov 2026 11:15:50 +0000

Remember when saving time was the whole point of technology?

We built faster computers so work could be completed quicker. We created email so communication wouldn't take days. We developed smartphones so we could do almost everything from one device.

We automated repetitive tasks, introduced AI, created instant messaging, and made information accessible within seconds.

We have never had more tools to save time.

Yet, somehow, we have never felt more occupied.

So where did all that saved time go?

The productivity paradox

Think about a typical working day.

You wake up and check your phone.

There are emails, WhatsApp messages, notifications, calendar reminders, and updates waiting for you.

Before you've even started your day, your attention has already been divided.

You open your laptop to complete one task. An email arrives. Then a Teams notification. Then someone sends a message asking for a quick update.

You switch between applications, respond to messages, attend meetings, and finally return to the task you originally intended to finish.

Technology made every individual action faster.

But it also introduced hundreds of new actions.

Faster communication created an expectation of instant responses

Email was supposed to make communication easier.

Messaging apps made it faster.

Video conferencing removed geographical barriers.

But somewhere along the way, faster communication became an expectation of immediate availability.

A message sent at 10:00 AM often comes with an invisible expectation: respond as soon as possible.

Being online started looking like being productive.

Being available started looking like being responsible.

And being busy started looking like being valuable.

We didn't just make communication faster. We made ourselves permanently reachable.

Every saved minute gets filled with something else

Here's an interesting thought.

Imagine technology saves you two hours every day.

What would you do with those two hours?

Spend time with family? Read a book? Learn something new? Take a break?

But what often happens?

We fill those two hours with more meetings, more tasks, more emails, more projects, and more expectations.

The time we saved didn't necessarily become free time.

It became additional capacity for more work.

And when we consistently demonstrate that we can do more, the definition of a normal workload quietly changes.

AI is making this question even more interesting

Now we have AI tools that can write, summarize, research, generate code, analyze data, and assist with decision-making.

Tasks that once took hours can sometimes be completed in minutes.

That's incredible progress.

But here's the question:

If AI makes us ten times faster at completing certain tasks, will we work less?

Or will we simply be expected to produce ten times more?

Technology can increase productivity, but productivity and quality of life are not the same thing.

We should be careful not to confuse the two.

Maybe the real problem isn't technology

Technology itself isn't the enemy.

It has made healthcare more accessible, education more flexible, communication easier, and countless everyday activities more convenient.

The problem might be how we measure success.

We measure how quickly we respond, how many tasks we complete, how many meetings we attend, and how much work we produce.

But how often do we measure the time we actually get back?

How often do we use technology to create space rather than fill it?

Perhaps we need a different definition of productivity

Maybe the ultimate achievement of technology shouldn't be helping us do more things in less time.

Maybe it should be helping us do what matters and leaving us with more time to live.

Imagine a future where:

Automation means fewer working hours, not just more output.
Instant communication doesn't mean instant availability.
AI gives us more time to think, not more pressure to produce.
Productivity is measured by meaningful outcomes, not constant activity.

That would be progress worth celebrating.

One question to leave you with

We spent decades building technology to save time.

We now have faster devices, smarter software, instant communication, and AI.

But are we actually getting more time to ourselves?

Or have we just become better at finding new ways to stay busy?

I'd genuinely like to hear your thoughts.

Technology #Productivity #AI #DigitalLife #FutureOfWork

# Your Automation Is Not as Smart as You Think: The Hidden Cost of Blind Automation

Michele — Tue, 03 Nov 2026 11:08:49 +0000

We love automation.

We automate deployments, infrastructure provisioning, database maintenance, monitoring, certificate rotation, and almost everything that once required human intervention.

But here's an uncomfortable question:

What if your automation is doing exactly what you told it to do, but what you told it to do is wrong?

That's when automation becomes dangerous.

The illusion of successful automation

Imagine this:

You have an automated production maintenance job.

It starts successfully.
Every task returns OK.
The playbook completes.
The Jenkins job turns green.

Everyone is happy.

But did the system actually reach the expected state?

A successful command execution doesn't necessarily mean a successful operation.

A service restart doesn't guarantee application availability.

A successful deployment doesn't guarantee application health.

A completed database maintenance task doesn't guarantee cluster stability.

Yet, many automation pipelines consider exit code zero as the ultimate definition of success.

That's the problem.

Command execution vs. outcome validation

There are two ways to approach automation.

Approach 1: Command-driven automation

Execute the command.
Check the return code.
Move to the next task.
Report success.

Approach 2: State-driven automation

Understand the initial system state.
Execute the required operation.
Wait for the system to converge.
Validate the expected final state.
Stop if the state is unexpected.

The second approach is what production-grade automation should aim for.

Build automation that thinks in states

Consider a simple infrastructure maintenance workflow.

Instead of asking:

"Did the quiesce command execute successfully?"

Ask:

Is the cluster healthy before maintenance?
Did the target node enter the quiesced state?
Are proxy transactions behaving as expected?
Did reclustering complete?
Is the cluster stable after the operation?

Notice the difference?

We are no longer automating commands. We are automating decisions based on system state.

Five questions every automation engineer should ask

What happens if the task succeeds but the expected state is not achieved?
What happens if the automation runs twice?
What happens if the process fails halfway through?
Can the automation detect an unexpected system state?
Can it safely stop without causing further damage?

If your automation cannot answer these questions, it might be time to rethink its design.

The next evolution: Self-validating automation

I believe the future of infrastructure automation isn't about writing more playbooks or reducing the number of manual commands.

It's about building systems that can:

Observe infrastructure.
Understand the current state.
Make controlled decisions.
Execute changes.
Validate outcomes.
Recover or stop safely.

This is where traditional scripting evolves into intelligent operations.

Final thought:

Don't measure automation by how many manual steps it eliminates.

Measure it by how reliably it protects your systems when things don't go as expected.

Because in production, a green pipeline is nice.

A correct and healthy system is what actually matters.

DevOps #Automation #SRE #Ansible #Infrastructure