You promoted your best software engineer. Now execution is slowing - and it doesn't make sense.

Meetings are quieter. Decisions bottleneck. Strong engineers hesitate instead of leading.

This is one of the most expensive failure modes in engineering orgs - not because people are incapable, but because technical excellence doesn't train human systems.

The cost: Decision velocity drops. Retention risk rises. Your leadership pipeline stalls.

I've seen this pattern from every angle - as an engineer, a leader, and an exec scaling teams under pressure for 25 years.

What makes my approach different is my background in anthropology and psychology. I don't just see the technical systems. I see the human ones - and I know how to bridge them.

One recent example: I helped a board that was ready to fire their entire engineering team. Same people. Redesigned system. They went from annual releases to shipping every two weeks - and had zero turnover in the following year.

The team wasn't the problem. The system was.

I help CTOs, VPs of Engineering, and CEOs turn strong engineers into trusted leaders - before you lose momentum, morale, or talent.

What changes:

↳ Meetings become productive, not painful 
↳ Delegation actually happens 
↳ Decision velocity increases 
↳ Retention risk drops 
↳ Leadership pipeline stabilizes

This isn't generic leadership training. It's systems-level coaching for engineers - grounded in how teams actually work and how leadership signals shape outcomes.

If you're watching this pattern emerge, let's talk.

👉 coded2lead.com

Robert Harris

The board’s first question caught everyone off guard:
"How many developers do we need to fire?"

Deadlines were slipping by months.
Bugs were outpacing features.
Product and Engineering were barely speaking.

From their perspective, it looked obvious:
People problem.

After 25 years inside engineering orgs, I’ve learned to pause when the entire system looks stuck.

Because most of the time...

It’s not the talent.

It’s the environment they’re operating in.

Six months later, that same "underperforming" team was shipping every two weeks.

No one fired.
No one quit.

The people didn’t change.

The system did.

Robert N. Harris

I turn your promoted engineers into force‑multiplying leaders | Founder, coded2lead | Book intro: coded2lead.com

"Robert jumps on a lot of grenades for us."
A developer told me that years ago.
It wasn’t a compliment.

But it opened my eyes -
and I started seeing this pattern everywhere.

Many engineering leaders accidentally train three specific dysfunction patterns - not through neglect, but through good intentions.

I broke down all three in this week’s Human Systems for Engineering Leaders.

The 3 Paradoxes of Helping No engineering leader sets out to harm their team. But intention and impact don't always travel together. And in my experie

Open article: The 3 Paradoxes of Helping by Robert N. Harris • 4 min read

"I'm going for a mental health maintenance walk."

I've said that to my team countless times -
because leaders normalize whatever they model repeatedly.

Last Monday everything broke at once, and I needed to take my own medicine.

Claude stopped Clauding.  
My computer stopped computing.  
My icemaker stopped making ice.  

It reminded me that entropy isn't just a good idea - IT'S THE LAW.

The old version of me would have powered through.
But powering through is how you train heroics.
And heroics are how you accidentally build burnout culture.

So I went for a walk.

Because the system is always learning -
even if you think nobody is watching.

If I don't step away when I'm overloaded,  
I teach them not to.

Culture isn't what you say it is.  
It's what you model under pressure.

Your software engineering team looks strong on paper.
But execution is slipping.

The team is talented.  
The roadmap is clear.  
The tooling is modern.

And yet...

• decisions keep stalling  
• the same bugs keep resurfacing  
• meetings get strangely quiet when it matters most

That pattern is a clue.

Leaders often jump to:  
"We hired wrong."

But when I see this pattern across an entire team, 
I start looking somewhere else.

Persistent hesitation in smart teams is rarely random.

It’s usually a human system signal.

I help CTOs & VPs turn promoted engineers into trusted leaders before execution stalls | Founder, coded2lead | Book intro: coded2lead.com

Your engineering team knows you're responsive.
You're helpful. You care.
And somehow... that's the problem.

Because your software team keeps coming back to you.

Every decision. Every blocker. Every judgment call.

Here's what that pattern is actually telling you:

- They've learned decisions belong to you
- They've learned "check with me first" is the real rule
- They've learned their judgment isn't trusted - even if you've never said that

You didn't create this on purpose.

You created it by being the most capable person in the room - consistently, visibly.

And now you're the constraining resource.

Because of that, your reach never exceeds your grasp.

Your team’s ceiling becomes your capacity.

And no amount of hiring fixes it - because every new engineer just gets absorbed into the same pattern.

The fix isn't delegation.

It's a different kind of trust.

One that looks less like "let me know if you need help"... and more like "you decide - I'll back you either way."

The most expensive question I ever asked my engineering team was:
"Any blockers?"


"Nope."  
"Good here."  
"All good."

Twelve seconds.  
Clean standup.  
Everyone aligned.

Or so I thought.

What I eventually realized was that I had built a perfectly calibrated silence machine.

The team wasn't agreeing with me.

They were doing the math.

Raising a blocker meant owning the problem in front of everyone.  
Admitting uncertainty meant looking like you didn’t have the answer.  
Questioning the plan meant becoming the person who slows things down.

So the calculation quietly ran in the background:

Is this worth it?

And most of the time the answer was no.

Silence in engineering meetings often isn’t alignment.

It’s risk management.

Once I started hearing silence that way, it changed the question I asked in the room.

Instead of  
"Does everyone agree?"

I started asking:

"What might we be missing here?"

You’d be amazed how often that changed the signal.

Have you ever discovered that a quiet meeting wasn't actually agreement?

If your software engineering org suddenly feels harder to move...
this pattern shows up a lot.

Leaders keep applying technical fixes...
to what are fundamentally human system problems.

And the system responds exactly as designed.

So they add process.  
They add tooling.  
They add more visibility layers.

And still:

• decisions bottleneck  
• teams hesitate  
• the same delivery patterns repeat

Underneath every tech stack is a human operating system.

And that layer quietly shapes everything that runs on top.

When a strong engineering team suddenly starts playing it safe,  
most leaders misread the signal.

When the whole team shifts behavior at once,  
assume adaptation before incompetence.

Human systems respond quickly to their environment.

Watch what the system is actually reinforcing.

If the system quietly rewards:

• keeping your head down  
• shipping fast over shipping right  
• protecting yourself over owning outcomes

the culture will converge in that direction.

The behaviors that frustrate leaders most often aren’t personality flaws.

They’re survival strategies that made sense in context.

I found burnout culture asleep on my office couch one Monday morning.

Our lead engineer had been there all weekend.

Finishing a feature I needed shipped.

I thought I knew what burnout culture looked like.
I thought I'd recognize it if I was creating one.
But there it was - impossible to ignore. 
And snoring. 

I didn't ask him to sleep at the office.
But I had built a system where it felt necessary.

That's what hit me standing in the doorway.
It wasn't his dedication that put him there.
It was mine.

My pace. 
My urgency. 
My silence about what was actually sustainable.

I had never said "work weekends."
But the system I built said it clearly.
And he heard it.

I wasn't a bad leader. 
I cared deeply about that team.

But caring isn't a culture.
It's just an intention.

Culture is what happens when no one is watching.
And when no one was watching - my team was sleeping in my office.

That was the hidden curriculum I'd been teaching.

Not the values on the team wiki. 
Not what I said in one-on-ones.

What the system had learned from watching me.

That's what nobody tells you when you hand someone a team.

The culture you build isn't the one you intend.

It's the one your behavior teaches.

Your best engineer is stuck again.
And they're waiting for you.


You have the answer in your head.

So you give it to them.

Problem solved. Back to work.

Except... you just taught them something you didn't mean to teach.

Not the solution - the lesson underneath it:

When you're stuck, wait for your leader.

That's the hidden curriculum you've been teaching your software team.

Not what you said. 
What the system learned from watching you say it.

You didn't build a team in that moment. 
You built a helper.

And every time you do it - with the best intentions - the system gets better at producing people who wait.

The question worth sitting with:

When someone on your team comes to you stuck... 
do you give them the answer?

Or do you give them the context to find it themselves?

I help YOU grow YOUR careers: from “stuck” to clear next steps, stronger CV, confident interviews, and promotion-ready communication.I do this as a practitioner, not a theorist. My main role is Engineering &amp; Delivery Manager in FinTech B2B: I lead cross-functional teams, hire engineers, run performance reviews, and build growth plans. That gives me a very practical view of what hiring managers and leaders actually look for.How I can help:🔹 CV / LinkedIn profile rewrite (clarity, positioning, results)🔹 Mock interviews (technical + behavioral) + feedback you can apply immediately🔹 Career strategy: roadmap for the next 3–6 months (skills, projects, visibility, negotiation)🔹 Transition support: Engineer → Senior / Lead / Manager (communication and leadership skills)My style: structured, direct, and supportive. You’ll leave with a plan and concrete actions, not motivational slogans.If you’re preparing for a job change or a promotion - feel free to connect and message me what you’re aiming for.

Valerii Popov

I used to think working 80 hours a week
made me productive. Then I realized:

I wasn't building more.
I was just spending more time fixing
what I broke while exhausted.

Here's what nobody tells you about "hustle culture":
Past a certain point, more effort doesn't create
more output, it creates negative returns.

Stanford research confirms it:
productivity drops sharply after 50 hours/week.

People working 80 hours often produce less
than those working 40, because they spend
the extra time correcting mistakes
made under cognitive overload.

There are three types of ceilings you can't break
through by "trying harder":

1️⃣ The Time Ceiling Human attention is finite.
The last 4 hours of a 12-hour workday aren't
productive, they're damage control.

2️⃣ The Metrics Ceiling.
When a metric becomes a target, it stops being useful.
Measure call center time? Operators hang up faster.
Measure task count? People split work into tiny pieces.

3️⃣ The Process Ceiling.
What works for 10 clients breaks at 100.
Manual control doesn't scale.
"Working harder" just multiplies chaos faster.

The hard truth:
Real growth always requires a temporary dip.

Netflix lost 800,000 subscribers transitioning
from DVDs to streaming. Stock dropped 77%.
But that was the only path to global dominance.

Microsoft Japan tested a 4-day workweek.
Productivity jumped 40%. But the transition
caused short-term coordination delays.

Most people stay stuck under their ceiling
because they're terrified of that temporary dip.

If you need to work twice as hard
just to maintain your current results?

You're not showing grit.
You're showing an inability to see
the wall in front of you.

Which ceiling are you hitting right now,
and what would it take to change the game
instead of just working harder at the old one?

–––
🤝 The Human Side of Tech - a series on teams, leadership, and management in IT
–––
🔔 Follow Valerii Popov for practical insights on leadership & career growth.
♻️ Share to help others grow as leaders.
🤝 Your engagement matters, I always respond in return.

Career Mentor ◆ CV & Interview prep ◆ LinkedIn Optimization ◆ Engineering Manager (FinTech) ◆ 10+ yrs

What happens when you accidentally
delete yourself from the internet?

October 2021.
Facebook, Instagram, WhatsApp - all gone.
Not slow. Not buggy. Just... gone.

For 6 hours, 3 billion people couldn't access any of them.

No cyberattack. No server fire.
Meta's own engineers made a configuration change
and accidentally unplugged the company
from the internet.

Here's what happened:
Meta runs a massive internal network connecting
data centers around the world. During routine
maintenance, engineers updated network settings.

The change broke the connection between
Meta's internal network and the outside internet.

Then the domino effect kicked in:
→ Internal systems detected the network
→ They stopped publishing Meta's address to the internet, like removing your store from Google Maps
→ For the rest of the world, Facebook and its apps simply didn't exist anymore

But here's the hardest part:
The outage also killed Meta's internal tools.
Engineers couldn't diagnose the problem remotely.
They couldn't access the systems they needed to fix it.

They had to physically send people to data centers,
with actual key cards and manual access,
to restore the network piece by piece.

The analogy:
Imagine a shopping mall that:
→ Accidentally removed all its signs and address from maps
→ And simultaneously locked the service entrance where the repair crew enters

Inside, the lights work. The doors exist.
But no one outside can find it, enter it, or quickly fix it.

The lesson for anyone building systems or teams:
The tools you use to run things and the tools you use
to fix things can't be the same system.

If your monitoring, communication, and recovery tools
all depend on the same infrastructure,
when that infrastructure fails, you're blind.

In practice:
1️⃣ Keep backup communication channels outside your main system
2️⃣ Design "break glass" procedures that work even when your primary tools are down
3️⃣ Test your recovery process when things aren't on fire

Because the moment you need to fix something
is exactly when your usual tools might not be there.

What's your team's "we're locked out" backup plan,
or do you assume your main systems will always be available?

–––
🛠️ Engineering Notes - about decisions, trade-offs, and the thinking behind them
–––
🔔 Follow Valerii Popov for real engineering decisions.
♻️ Share to spread better engineering practices.
🤝 Your engagement matters, I always respond in return.

I spent three months perfecting a business plan
that never launched....

Meanwhile, someone I knew from college,
who could barely spell "revenue",
threw together a janky website
on a free builder in one weekend.

His design looked like 1998. His copy had typos.
His customer support was... let's just say "inconsistent".

But here's the thing:
→ He had 10,000 paying customers within six months.
→ I had a beautiful PDF gathering digital dust.

💡Here's what I learned the hard way:
Perfectionism isn't professionalism.
It's procrastination dressed in a tuxedo.

The market doesn't reward polish.
It rewards solving problems fast.

While I was choosing between Arial and Helvetica,
he was capturing market share.
While I was refining my pitch deck,
he was getting feedback from real customers,
and iterating with their money.

School taught us that mistakes = failure.
The real world teaches the opposite:
perfect but unreleased always loses
to good enough and shipping.

The brutal math:
Every week you spend "perfecting" is a week
someone else is learning, earning, and improving.
That's not just lost time. It's lost revenue.
Lost feedback. Lost momentum.

Economists call it "opportunity cost".
I call it the most expensive tax you'll ever pay,
the tax on being afraid to suck.

What actually works:
1️⃣ Set a hard deadline. When the timer goes off,
you ship, no matter what.
2️⃣ Aim for "good enough to test",
not "good enough to frame".
3️⃣ Collect rejection like data.
Ten "no's" teach you more than one "perfect" draft.

The people winning right now?
They're not the smartest. They're not the most polished.

They're the ones willing to be messy,
get feedback, and fix it in public.

What are you polishing right now
that you should just ship?

–––
🤝 The Human Side of Tech - a series on teams, leadership, and management in IT
–––
🔔 Follow me for practical insights on leadership & career growth.
♻️ Share to help others grow as leaders.
🤝 Your engagement matters, I always respond in return.

Why zebras don't stress out, but we do.

A zebra gets chased by a lion.
Heart racing. Full sprint. Escapes.

Five minutes later? Calmly eating grass.
No therapy. No ruminating about the chase.
Just... back to normal.

Humans? We're different.

We sit in meetings thinking about deadlines.
We lie in bed replaying conversations.
We stress about things that haven't happened yet,
and might never happen.

Here's the key difference:
→ Fear is acute. It has a clear threat and a clear end.
The zebra sees the lion, runs, survives - done.
→ Stress is chronic. It's never fully resolved.
You're always in the "waiting room" of uncertainty.
And that's where the damage happens.

Not all stress is bad.

There's eustress - short-term, productive stress
with a clear endpoint.

Think: writing your thesis in three nights,
closing a tough deal, launching a product.
In those moments, adrenaline and cortisol
flood your system. You get a temporary superpower:
focus sharpens, productivity spikes.

This is your internal power plant.
It's how breakthroughs happen.
The first iPhone wasn't built in a spa.
Gagarin's flight wasn't a calm Sunday drive.

But then there's distress, when stress becomes chronic.
No endpoint. No recovery. Just constant tension.

That's when:
→ Your thinking gets narrow (tunnel vision)
→ Creativity dies (survival mode kills new ideas)
→ Memory fails (you forget meetings, lose focus)

It's like lifting weights 24/7 without rest.
Eventually, something breaks.

So how do you stay in "eustress" mode without burning out?

1️⃣ Balance wheel
Don't put all your energy in one place.
If work is your only pillar, any crisis there becomes catastrophic.
2️⃣ Bank of wins
Keep a "victory log". When facing something scary,
revisit past successes. Proof you've survived before reduces panic.
3️⃣ Control the basics
Sleep, food, routine. In chaos, your brain needs anchors.
Reduce unnecessary friction (delegate logistics, automate boring tasks).
4️⃣ Future self perspective
Imagine yourself a year from now,
you've already solved this problem.
What does that version of you see that current-you is missing?

The philosophy:
Stress isn't the enemy. It's the price of growth.
But chronic stress, stress without resolution,
is radiation. Invisible, slow, destructive.

The key? Close the loop.
Take action. Finish the cycle.

How do you handle being stuck in the "stress room"?
What actually works for you?

–––
🤝 The Human Side of Tech - a series on teams, leadership, and management in IT
–––
🔔 Follow me for practical insights on leadership & career growth.
♻️ Share to help others grow as leaders.
🤝 Your engagement matters, I always respond in return.

Two years of work vanished with a single click.

Marcel Bucher, a researcher at the University of Cologne, used ChatGPT Plus as his primary workspace for nearly two years.

Grant applications. Lecture prep. Paper drafts.
Course descriptions. Student exam analysis.

He didn't just use ChatGPT for one-off tasks.
He built a system around it, returning to
old conversations, refining drafts, relying
on accumulated context across project folders.

Then in August, he toggled a setting related to data consent.

Instantly:
→ All chat history: deleted
→ Project folders: emptied
→ No warning. No undo. Just a blank page.

He tried everything: different browsers, devices,
cache clearing, reinstalling the app,
toggling the setting back.

Nothing.

Support responded, eventually,
through a human after an AI agent:
"The data is permanently gone.
This aligns with privacy best practices and legal requirements."

Here's what makes this story strange:
OpenAI's own documentation says:
"If you turn off data sharing, your conversations will
still appear in your chat history,
they just won't be used to train the model."

But that's not what happened here.

Either the setting Bucher toggled was different
from what the FAQ describes, or there was
a product bug, or the UI labeled something
as "data consent" that actually triggered permanent deletion.

OpenAI confirmed the incident to Nature
and stood by the decision: once deleted,
data cannot be recovered - not through UI, API, or support.

Their recommendation?
"Users should make personal backups of professional materials."

The lesson isn't about blaming OpenAI or the user.

It's about this:
If a tool becomes your workspace, you need to own your data, not rent it.

In practice:
→ Export critical work regularly
→ Don't treat ephemeral tools as permanent storage
→ If you can't rebuild it from a backup, it's not safely stored

Because the moment a setting, a bug, or a policy
change wipes your work,
"I thought it was safe" won't bring it back.

Are you treating any tool as a workspace
without owning a backup of what's inside it?

–––
🔔 Follow Valerii Popov for clear takes on AI trends & industry news.
♻️ Share to keep your network updated.
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What happens when one typo
takes down a chunk of the internet?

February 2017. An engineer at Amazon Web Services
is debugging a billing issue in their S3 storage system.

They need to take a small number of servers offline,
routine maintenance.

They run the command from the playbook.
But one parameter is wrong.
Instead of removing a handful of servers,
the command removes way more than intended.

Critical subsystems go down, including the index
that tells S3 where every file is stored.
Without it? No one can upload, download,
or access their data.

For hours, huge chunks of the internet
stopped working: websites, apps, services - all frozen.

💡Here's what makes this story important:
This wasn't about one person making a mistake.
It was about a system that allowed one mistake
to scale into a catastrophe.

The trade-off AWS faced:
1️⃣ 𝐒𝐩𝐞𝐞𝐝 𝐚𝐧𝐝 𝐬𝐢𝐦𝐩𝐥𝐢𝐜𝐢𝐭𝐲:
Engineers need to quickly add/remove capacity.
Manual commands are fast and flexible.

2️⃣ 𝐒𝐚𝐟𝐞𝐭𝐲 𝐚𝐧𝐝 𝐩𝐫𝐨𝐭𝐞𝐜𝐭𝐢𝐨𝐧:
Add guardrails, rate limits on dangerous commands,
hard minimums you can't go below,
checks that slow things down.

You can't have both fully.
AWS chose speed. And one typo proved the cost.

After the outage, they changed the rules:
→ Safeguards so you can't remove too much too fast
→ Made removal operations slower and more deliberate
→ Worked on partitioning systems into smaller "cells",
so one failure can't take everything down

The universal lesson:
In any system, you face this choice:
Fast and flexible (but one mistake can cascade)
vs Slow and protected (but harder to move quickly)

Neither is "right". But you need to consciously choose,
and design for the consequences.

Where in your work have you optimized for speed,
and what would happen if one mistake scaled?

–––
🛠️ Engineering Notes - about decisions, trade-offs, and the thinking behind them
–––
🔔 Follow me for real engineering decisions.
♻️ Share to spread better engineering practices.
🤝 Your engagement matters, I always respond in return.

What do you do when your system starts
screaming alarms at the worst possible moment?

July 20, 1969. Apollo 11's lunar module
is descending to the Moon's surface.

Then the computer starts flashing warnings: "1201. 1202."

Alarms. Overload. System under stress.
Mission Control has seconds to decide:
Abort the mission, or trust the system.

They chose trust.

Here's what happened:
A hardware glitch, incorrectly positioned radar switch,
was flooding the computer with extra tasks.
But the software was designed to survive
exactly this kind of failure.

It did three things:
→ Recognized it was overloaded
→ Dropped low-priority tasks
→ Kept the critical navigation and landing systems running

The landing succeeded on fumes,
with seconds of fuel left.

What made this system special wasn't perfection.
It was designed to fail gracefully.

The engineers knew the system would
face unexpected stress. So they didn't optimize
for "never breaking". They optimized for
"staying safe and predictable when things go wrong."

Think of it like this:
Imagine you're driving in a storm.
❌ A bad system panics and locks up.
✅ A good system turns off the radio, dims the
dashboard, and keeps the steering and brakes working.

That's graceful degradation.

This applies to any project, not just software.
When your system hits overload:
→ Does it crash completely?
→ Or does it know what to protect and what to let go?

The best systems don't try to do everything
perfectly under stress. They know what matters most,
and they protect that at all costs.

When your project is under pressure,
what's the "navigation system" you refuse
to compromise, and what are you willing to drop?

–––
🛠️ Engineering Notes - about decisions, trade-offs, and the thinking behind them
–––
🔔 Follow Valerii Popov for real engineering decisions.
♻️ Share to spread better engineering practices.
🤝 Your engagement matters, I always respond in return.

Last week, I posted a scenario:
Your best bookkeeper is technically excellent,
but consistently combative with vendors and partners.

Defensive. Argumentative. Zero tact.

I asked: what's your first move?
The results:
→ 78% said: "Direct feedback & coaching"
→ 11% said: "Start planning a replacement"
→ 7% said: "Limit external contact"
→ 4% said: "Formal warning, document it"

What's striking isn't just what won, it's how decisively.

78% is a landslide.
Most leadership polls split 50/50 or 60/40.
This one didn't.

Why such strong consensus?
I think it comes down to this:
most managers believe behavior is coachable
if the person doesn't know they're the problem.

The scenario didn't say she's malicious
or intentionally toxic. It said she's defensive,
which often means she doesn't realize
how she's coming across.

That's fixable with clear, direct feedback.

But here's where context matters:
🟨 "𝐃𝐢𝐫𝐞𝐜𝐭 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 & 𝐜𝐨𝐚𝐜𝐡𝐢𝐧𝐠" 𝐰𝐨𝐫𝐤𝐬 𝐰𝐡𝐞𝐧:
→ The person is unaware of the impact
→ They're open to feedback (even if initially defensive)
→ The behavior is situational, not deeply ingrained

🟩 "𝐋𝐢𝐦𝐢𝐭 𝐞𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐜𝐨𝐧𝐭𝐚𝐜𝐭" 𝐦𝐚𝐤𝐞𝐬 𝐬𝐞𝐧𝐬𝐞 𝐰𝐡𝐞𝐧:
→ Coaching has failed or isn't realistic
→ The role can be restructured without losing value
→ You're buying time to assess if this is salvageable

🟦 "𝐒𝐭𝐚𝐫𝐭 𝐩𝐥𝐚𝐧𝐧𝐢𝐧𝐠 𝐚 𝐫𝐞𝐩𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭" 𝐢𝐬 𝐫𝐢𝐠𝐡𝐭 𝐰𝐡𝐞𝐧:
→ The behavior is entrenched and affects team morale
→ External relationships are core to the role
→ You've coached before and nothing changed

🟪 "𝐅𝐨𝐫𝐦𝐚𝐥 𝐰𝐚𝐫𝐧𝐢𝐧𝐠, 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐢𝐭" 𝐭𝐲𝐩𝐢𝐜𝐚𝐥𝐥𝐲 𝐜𝐨𝐦𝐞𝐬
𝐚𝐟𝐭𝐞𝐫 𝐜𝐨𝐚𝐜𝐡𝐢𝐧𝐠 𝐟𝐚𝐢𝐥𝐬, 𝐧𝐨𝐭 𝐚𝐬 𝐚 𝐟𝐢𝐫𝐬𝐭 𝐦𝐨𝐯𝐞.
The 78% got it right for a first move.
But if coaching doesn't work?
That 11% "start planning a replacement"
becomes the next step.

Leadership isn't about having one right answer.
It's about knowing which answer fits
which stage of the problem.

Have you ever coached someone on behavior
and seen them turn it around,
or realized too late that coaching
wasn't going to work?

📊 New Poll
I’ve launched a new vote:
You caught your employee stealing time...
A tough topic and something almost every faces at some point.
https://lnkd.in/dE5mmb2a

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Target just solved customer service.

They introduced the "10-4 Rule":
→ If a customer is within 10 feet: smile, wave
→ If within 4 feet: personally greet them, offer help

It's a protocol. A standard. A system.

Because apparently, the problem wasn't:
→ understaffing
→ long checkout lines
→ out-of-stock items
→ overworked employees

The problem was: not enough smiles per square foot.

So now, instead of fixing operations,
they've turned human emotion into a checklist:
if (distance <= 10ft) { smile(); wave(); }
if (distance <= 4ft) { greet(); offerHelp(); }

I can already see the performance review:
"Your smile-per-customer ratio was below target this quarter."😀

Here's the thing:
If you need to mandate friendliness by distance
measurement, that's not a service problem.

That's a red flag that your employees are either:
→ Wildly overloaded
→ Wildly unmotivated
→ Or both

But sure. Let's regulate the smiles. That'll fix it.

Happy Friday, everyone! 🎉
May your weekend be free of mandatory eye contact protocols.

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Last week, I posted a scenario:
Your entire team is being replaced.
You're keeping your job, but managing a new team
12 time zones away. Zero overlap. No live collaboration.
The job you loved is structurally gone.

The results:
→ 70% said: "Adapt & invest in new team"
→ 17% said: "Start looking for next role"
→ 13% said: "Set boundaries, go transactional"

What's striking:
70% chose to adapt, even though the scenario made
it clear this fundamentally isn't the same job anymore.

So why such a strong majority for "adapt"?
I think it comes down to three things:

1️⃣ The 6-month problem
Leaving after six months looks bad on a resume.
Many people felt trapped:
"I can't leave yet, so I have to make it work."
That's not optimism. That's pragmatism under constraint.

2️⃣ The belief that you can make it work
Several comments said:
"I've managed remote teams before. Async can work."
True, but there's a difference between choosing
async and having it forced on you after
building a synchronous culture.
The poll didn't ask "can you adapt?"
It asked "do you want to?"

3️⃣ The fear of being seen as "not adaptable"
One comment stuck with me:
"A good manager should be able
to make any situation work."
But adaptability isn't infinite.
Sometimes "adapting" means
accepting a job you don't want.

Here's the nuance most people missed:
"𝐀𝐝𝐚𝐩𝐭" 𝐰𝐨𝐫𝐤𝐬 𝐰𝐡𝐞𝐧:
→ You genuinely believe async management
can be fulfilling for you
→ The company shows investment
in making the transition work
→ You're not just enduring
until something better comes along

"𝐒𝐭𝐚𝐫𝐭 𝐥𝐨𝐨𝐤𝐢𝐧𝐠" 𝐦𝐚𝐤𝐞𝐬 𝐬𝐞𝐧𝐬𝐞 𝐰𝐡𝐞𝐧:
→ The type of work you valued
is structurally impossible now
→ You're staying out of fear, not conviction
→ Six months of the wrong job is worse
than explaining a short stint

"𝐒𝐞𝐭 𝐛𝐨𝐮𝐧𝐝𝐚𝐫𝐢𝐞𝐬, 𝐠𝐨 𝐭𝐫𝐚𝐧𝐬𝐚𝐜𝐭𝐢𝐨𝐧𝐚𝐥" 𝐢𝐬 𝐡𝐨𝐧𝐞𝐬𝐭 𝐰𝐡𝐞𝐧:
→ You need the paycheck, but won't pretend to love it
→ You're buying time while exploring options
→ You refuse to burn out trying to force a bad fit

The real question isn't "can you adapt?"
It's: "Are you adapting to a new challenge,
or just enduring a job you don't want anymore?"

One builds you. The other drains you.

If you voted "adapt", was it because you genuinely
believed you could make it work,
or because leaving felt too risky?

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Most people are using AI in the most expensive way possible.

They hand over the work that needs human judgment…
and then spend their best hours polishing
the kind of output that has a hard “good enough” ceiling.

That’s the productivity trap:
❌ AI becomes a draft factory you babysit
❌ your calendar stays full
❌ your growth stays linear

In the article, I break down a simple way out:
Two curves. Two filters. One rule.

If a task hits diminishing returns → push it through 4R
If a task has increasing returns → protect it. That’s your Human Zone.

The practical part: a 5-minute exercise to split tomorrow’s
to-do list into what AI should absorb vs. what you should own.

Question for you: what’s one task you still do manually,
even though it’s clearly diminishing returns, and AI should be doing it?

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TL;DR: Most people use AI backwards: they delegate high-judgment work and keep low-leverage busywork. Use the “two curves” test to decide what stays h

Open article: The Productivity Trap: Misusing AI by Valerii Popov • 4 min read

I analyzed dozens of non-linear career paths over the past year.

→ People who zigged when they were "supposed" to zag.
→ Engineers who became managers, then went back to IC roles.
→ Directors who stepped into senior contributor positions.
→ CTOs who returned to architecture.

The pattern I found?
The most successful professionals treat careers
like lattices, not ladders.

Here's the uncomfortable truth:
→ Senior roles often offer diminishing returns
→ High influence ≠ high impact
→ "Manager Mode" isn't inherently better than "Founder Mode"
→ Strategic realignment looks like failure to people still climbing

One example: A CTO stepped back to the architect.
His energy returned. His impact increased. His stress was halved.
His compensation? 90% of CTO pay.

I built a 4-part framework for making these decisions:
1️⃣ Impact vs. Influence
2️⃣ Energy vs. Compensation
3️⃣ Mode Switching
4️⃣ The Transparency Test

Each one has a specific action step you can take this week.

The question isn't "What's next?"
The question is "What's right?"
Which one are you asking yourself?

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TL;DR: Careers aren’t ladders - they’re lattices: sometimes a step sideways or “down” increases impact, energy, and alignment. Use four checks (impact

Open article: Why Going Back Can Be Smart by Valerii Popov • 5 min read

Last week, I posted a scenario:
Your employee has been stealing time,
repeatedly, deliberately, for months.

120 hours of sick leave banked
that should have been used.
A clear pattern of resistance every time
you ask her to correct it.

I asked: what's your move?
The results:
→ 77% said: "Candid 1:1, document, give one chance"
→ 14% said: "Loop in HR immediately"
→ 9% said: "Freeze approvals; require PTO preapproval"

What's striking: 77% chose conversation first,
but with one critical addition.
Document.

That word showed up in almost every comment.

People weren't saying
"just talk to her and hope it works".
They were saying:
"Have the conversation, make expectations clear,
and create a paper trail,
because if this doesn't change, you need evidence."

Here's why that matters:
This isn't like the combative bookkeeper scenario,
where behavior might be coachable.
This is documented, repeated time theft
spanning months, potentially years.

The 1:1 isn't about discovering if there's a problem.
It's about giving formal notice that the problem
has been identified and must stop.

🟨 Why "Candid 1:1, document, give one chance" works:
→ It protects you legally. If you escalate to termination
without a documented conversation, you're exposed.
→ It's fair. Even if the pattern is obvious,
giving one explicit warning shows good faith.
→ It sets a clear line. After this conversation,
any repeat = immediate escalation. No ambiguity.

🟩Why "Loop in HR immediately" (14%) makes sense:
If your company has strict time theft policies,
going straight to HR might be required, not optional.
Some commented:
"This is fraud. HR needs to know now."
That's valid, especially if the amounts are significant
or if this violates policy explicitly.

🟦 Why "Freeze approvals" (9%) is risky as a first move:
Preapproval signals you don't trust her, but you
haven't told her yet that you know about the pattern.
It's consequence before conversation.
Most felt: have the direct conversation first,
then if behavior continues, tighten controls.

💡 The key takeaway:
"Document" isn't about being punitive.
It's about being prepared.

If she corrects the behavior after one clear conversation?
Great. You gave her a fair chance.

If she doesn't?
You have everything you need to escalate
with confidence and legal protection.

Have you ever had to document a conversation
knowing it might be the first step toward termination?
How did you balance fairness with protecting yourself?

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An Australian marketer sat in a meeting and heard his boss say:
"Let's take this offline and synergise the actionables moving forward."

He couldn't hold it in anymore.
So he started writing it all down.
For years.

And those notes became a comedy show, a bestselling book, 
and a movement called Wankernomics - the study of corporate
BS as a language.

James Schloeffel and Charles Firth, the guys behind it,
have a simple thesis:
Corporate jargon isn't communication. It's camouflage.

As Firth puts it:
"Every adult is secretly a terrified 14-year-old afraid
of being exposed as a fraud. And the fancier the words,
the more convincing the illusion that you know what you're doing."

Some highlights from their work:
⭐️ "North Star"
Companies everywhere use this to describe their strategic vision.
Small problem: you can't see the North Star in the Southern Hemisphere.
One audience member admitted his company had
three separate North Star projects.
When asked how they navigate between three North Stars, the answer?
They created a "Compass" project to figure it out.

⭐️ "Solutions"
A plumber who says "I provide plumbing solutions"
charges twice as much as one who says "I'm a plumber."
The only function of the word? Sounds expensive.

⭐️ "Break down the silos"
Silos on farms exist specifically to keep products separate.
Mixing them is a disaster.
Maybe John from accounting and Jenny from marketing
are separated for a reason.

The best part?
This isn't just corporate.
Teachers, doctors, construction workers - everyone recognizes
their meetings in this.

Because corporate language isn't the language of business.
It's the global language of people afraid to look incompetent.

Happy Friday, everyone! 🎉
May your weekend be free of actionables, synergies,
and anyone asking to "circle back Monday".

I used to think quality meant "no bugs"

Then I spent a few years watching systems break
in creative ways. And I realized:
quality isn't about perfection. It's about predictability.

A high-quality system doesn't surprise you.
It behaves the way you expect - under load,
over time, when things go wrong,
and when new people touch it.

Here's what I look for now when I think about quality:
1️⃣ Behavior over time
Not "it works today", but "it won't break tomorrow".
Quality systems age well.
Changes don't turn them into a lottery.

2️⃣ Known failure modes
Reliable systems have designed failures:
timeouts, limits, graceful degradation, backpressure.
If you don't know how it fails, you don't control it.

3️⃣ Observability, not optimism
If you can't see what's happening,
"quality" becomes faith. The question "why is it slow?"
should have a fast path to an answer.

4️⃣ Changeability
High-quality systems make changes cheaper.
Small work, low blast radius, fast rollbacks.
If every change feels risky, quality is low,
no matter how few bugs you have.

5️⃣ It's a product property, not just work
Quality shows up in UX: predictable delays,
honest errors, no "weird" states.
Users feel it even if they can't name it.

I don't aim for zero bugs anymore.
I aim for systems that behave predictably,
fail gracefully, and stay manageable as they grow.

That's what quality means to me now.
What's your definition of quality evolved
into over the years?

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🌿 Sunday Self-Reflection
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Most of my worst decisions came from my brain
trying to save energy, not save the situation.

I've been thinking about
how my brain actually works under pressure.

Not in theory. In those real moments
when production is on fire,
a client is angry,
or a deadline is 2 hours away.

I've noticed two modes:
→ "Lazy monkey" mode - fast, cheap, pattern-based.
Main goal: survive while spending as little energy as possible.
→ "Smart nerd" mode – slow, analytical, expensive.
Main goal: understand reality and choose deliberately.

Most of the time, "lazy monkey" is good enough.
You don't need deep analysis to reply to emails.

The problem starts when things become urgent.
Because urgency doesn't switch on the "smart nerd".
It does the opposite.

Under stress, brain doubles down on shortcuts:
→ Action bias – doing feels better than thinking
→ Tunnel vision – I fall in love with the first hypothesis
→ Confirmation bias – I notice data that fits my story

The scary part? Everyone does this. Senior, junior, IC, manager.
Brains are optimized for survival, not truth.

💡What I'm trying to do now:
→ If nobody's life is at immediate risk,
I force a 5-minute pause before any irreversible action
→ I write down at least two plausible hypotheses
before touching the system
→ In incidents, I separate roles: one person acts,
another keeps asking "what are we assuming?"

None of this makes me perfect.

But it buys me just enough distance
from my "lazy monkey" to let the "smart nerd"
say at least one sentence.

Urgency doesn't only test our systems.
It tests which part of our brain is in charge.

When you're under pressure,
what's the first cognitive trap you tend to fall into,
and how do you catch yourself?

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You just found out your entire team is being replaced.
You're six months into a management role you love.

15 people reporting to you. Fully remote.
Different time zones, but it works.
You've built relationships. The culture is strong.
The projects are exciting.
You were finally hitting your stride.

Then leadership announces:
the entire team is being let go.
All 15 roles are moving to a different region,
12 time zones away.

You're keeping your job. But your team? Gone.

And now you're expected to manage
a brand-new team with zero overlapping work hours.

No live conversations.
No spontaneous problem-solving.
No seeing people grow.

Just emails. Async updates.
Transactional management.

The job you loved,
the relationships, the mentorship, the culture you built,
it's all gone.

What's left feels like a different job entirely.
And you can't shake the thought: 
"Am I next? Once this new team is up and running,
do they still need me?"

You want to stay.
You thought this was your long-term role.

But this isn't what you signed up for.
You also can't job-hop after six months,
it looks bad on a resume.

So now you're stuck in limbo:
→ Do you adapt and try to make it work?
→ Do you set boundaries and accept it's now transactional?
→ Or do you quietly start looking for the exit?

Have you ever had a job change so drastically
under you that it stopped being the role you wanted,
and had to decide: adapt or leave?

🗓️ Your vote helps others facing this situation.
Cast it, then drop your reasoning in the comments.
In a week, I'll share the results
and what I learned from your responses.

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What would you do after your team is offshored and you're asked to manage a new team 12 time zones away?

The author can see how you vote. Learn more

You just became a manager.
And you caught your employee stealing time.

First week approving timecards.

You notice one of your employees didn't put in
PTO for a sick day. You think it's an oversight
and ask her to add it.

An hour later, she approves her timecard,
without adding the hours.
You ask again: "It didn't go through."
She submits it this time. But there's an attitude.

Next pay period: She goes home early for
a maintenance emergency (3.5 hours). Doesn't log it.

You ask her to add the hours.
She argues: "It wasn't the whole day. It's not necessary."
You tell her it is.

Two pay periods later:
She calls out sick two days in a row.
Comes back. Approves her timecard, no sick time logged.

You ask her to add it. She only adds one of the
two days. You have to go back and ask for
the second day.

At this point, you're sure it's deliberate.
So you start digging.

She has 270 hours of sick leave in her bank,
even though she was just off for two weeks
straight for surgery.

You check her past timecards.
She didn't use a single hour of sick leave for those
two weeks. Her previous manager didn't notice.

You keep digging:
→ Another full week unaccounted for
→ Random days here and there

Since August alone: 120 hours of sick leave
kept in her bank that should have been used.

You weren't her manager then, so technically,
it's not your business.
But you're the one dealing with it now.

Have you ever inherited a problem employee,
and had to decide whether to coach or escalate?
What's your move?

🗓️ Your vote helps others facing this situation.
Cast it, then drop your reasoning in the comments.
In a week, I'll share the results
and what I learned from your responses.

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🤝 The Human Side of Tech - a series on teams, leadership, and management in IT
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Your brain has 50 tabs open.
And none of them will close.

You became a manager because
you were good at getting things done.
You had a system. You remembered everything.
You were on top of it.

But now?
Now it's not about one big project.
It's about a hundred small things:

→ Follow up with Sarah about that task
→ Check back on the client project next Tuesday
→ Remember Tom mentioned he needed help
→ Reply to that message later
→ Make sure the action items from yesterday's meeting actually happened

None of these are huge individually.
But there are so many of them.

And the worst part?
Your brain won't let go.

Even after work, random thoughts keep popping up:
"Did I check that?"
"I need to follow up on that tomorrow."
"Wait, did anyone ever finish that thing?"

You used to keep everything organized in your head.
But the more responsibility you have,
the more that feels impossible.

You're starting to realize: this isn't sustainable.
Something has to change.
So what do you do?

How do you actually handle the mental load,
and what's worked, or failed spectacularly, for you?

🗓️ Your vote helps others facing this situation.
Cast it, then drop your reasoning in the comments.
In a week, I'll share the results
and what I learned from your responses.

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How do you actually handle the mental load?

[URGENT] New Initiative:
Solving Our Time Management Problem

Dear Team,
I've noticed a troubling trend:
we're spending too much time working
and not enough time managing our time.

So I'm proposing we solve this the most proven
way possible, with a series of meetings.

Here's the plan:
💎 Monday: Quick sync to align on which meetings we need to discuss how to reduce meetings.
💎 Tuesday: Workshop titled "Macro-Level Recalibration". Everyone brings minimum 15 topics about minimizing wasted work.
💎 Wednesday: We'll shortlist the top 20 topics for Thursday's Productivity Enhancement offsite.
💎 Thursday: Split into two groups:
→ "Inter-group Communication"
→ "Idea Bottlenecking"
I'll float between rooms, taking the temperature.
💎 Friday: "Quick alignment" call to decide where to schedule another call for things we didn't get to discuss.

To sustain improvements, we're launching permanent committees called SI (Solution Innovators), meeting bi-weekly until productivity improves or the calendar runs out, whichever comes first.

Motivation: The team with the best solutions gets donuts.

Action required: By Wednesday 12 PM, send me your top 5 donut preferences + your availability for the next 3 weeks so we can find a slot for "Donut Preferences Alignment".

One more thing: I see morale has dipped slightly. Please generate 15 ideas for improving atmosphere (wacky clocks welcome). We won't discuss them, no time, just post in the shared thread so everyone can give feedback, which we'll add to the feedback overflow list and definitely discuss later at a separate meeting.

Don't worry about this over the weekend.
Just come Monday prepared.

Happy Friday, everyone!
May your weekend be meeting-free 😃

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