Leonard Rodman, M.Sc. PMP® LSSBB® CSM® CSPO®

Coding in Claude Code isn’t magic. It’s craftsmanship.

Watching how soccer balls are made is the perfect analogy. Nobody just “makes a ball” in one motion. There’s a process. Cut the pieces. Shape the panels. Stitch the structure. Test the feel. Fix the weak spots. Repeat until it becomes something that can actually perform.

That’s exactly what coding with Claude Code feels like when you do it well.

You don’t just throw one vague prompt at it and pray.

You think through the system.
You break the work into steps.
You finish one piece before moving to the next.
You inspect what changed.
You test the output.
You catch the weird edge cases.
You iterate until the thing holds together.

The people who get frustrated with AI coding usually treat it like a vending machine.

Prompt goes in.
Perfect app comes out.

That’s not how this works.

Claude Code is more like having an extremely fast builder sitting next to you, but you’re still the architect, the reviewer, the tester, and the person responsible for the final product.

The quality comes from the process.

Not the first prompt.
Not the fanciest model.
Not pretending you can skip the hard part.

The real skill is learning how to guide the work step by step without losing the thread.

And when you get into that rhythm, it feels incredible.

Think.
Build.
Check.
Refine.
Repeat.

That’s the game.

Repost if you’re learning to build with AI, like if this hit, and follow me for more AI workflow breakdowns.

Making friends as an adult is weirdly brutal.

Not because you forgot how to be friendly.

Because adult life is designed to delete friendship by default.

Work eats your weekdays.
Partners and kids eat your weekends.
Moves break your routines.
And everyone’s calendar becomes a polite way of saying “no.”

Then you look up and realize:

You’re not lonely.

You’re under-booked on real connection.

Here’s the uncomfortable truth.

You don’t “meet friends.”
You build them.
On purpose.
With reps.

Friendship is proximity + repetition + shared vulnerability.

So if you want more new friends this year, stop treating it like a magical accident.

Treat it like a system.

Pick one “third place” and show up every week.
Same day. Same time.
Run club. Pickup basketball. Yoga. Trivia. Volunteering. Book club. Coworking spot. Church. Whatever.

Not because it’s your passion.

Because it’s your pipeline.

Then do the part most adults avoid:

Make the first move.

Not “we should hang sometime.”

Actual specifics.

“Want to grab coffee after next week’s class?”
“I’m trying a new spot Saturday at 10 - want in?”
“I’m headed to that meetup Thursday - come with?”

Yes, it’s awkward.

So is being 42 with zero people you can call on a Tuesday.

Also, stop waiting for instant chemistry.

Adult friendship is slow-cooked.

You don’t need a soulmate friend.
You need a bench.

3-5 people you see regularly.
Who know your name.
Who’d notice if you disappeared.

One more thing:

If you’re always “too busy,” you’re not busy.

You’re over-optimized.

This year, trade a little efficiency for a lot more life.

Repost, like, and follow if you want more posts like this.

You don’t need to be a genius to win with AI.

That’s one of the dumbest lies on the internet right now.

People act like the future belongs to:
founders
engineers
VC-backed weirdos
and the LinkedIn guy who "built 19 agents before breakfast"

Relax.

Normal people can win too.

Just not by trying to outsmart the smartest people in the room.

You win by becoming useful faster than everyone else.

That’s the whole game.

Most people still use AI like a toy.

They type vague prompts.
Get bland output.
Roll their eyes.
Go back to doing everything the slow way.

That’s why the bar is still absurdly low.

If you’re average, your advantage is not brilliance.

It’s willingness.

Willingness to experiment.
Willingness to look dumb.
Willingness to practice.
Willingness to use the tools every day instead of saying you’ll "get into it later."

Because later is where people go to die professionally.

Here’s how regular people actually pull ahead:

Pick one thing you already do
and become ridiculously good at doing it with AI.

One thing.

Not ten.

Writing.
Research.
Meetings.
Content.
Sales.
Job hunting.
Decks.
Spreadsheets.
Learning faster than everyone around you.

One workflow can change your career.

Then you stack another.

And another.

That’s how "naturally talented" people are made.

They’re usually not more gifted.

They just started earlier
and practiced longer.

Another truth people don’t want to hear:

You do not need to build the next AI company.

You might just need to become the most capable person on your team.

That alone can change your income,
your leverage,
your confidence,
and your options.

The AI race is not just about who builds the model.

It’s about who becomes more effective because the model exists.

That includes:
employees
freelancers
creators
salespeople
marketers
analysts
project managers
teachers
recruiters
operators
and random hungry people with Wi-Fi

Especially the random hungry people with Wi-Fi.

Most people lose because they get distracted by the spectacle.

The jargon.
The demos.
The benchmarks.
The nonstop flood of "everything changed again" content.

Ignore it.

You do not need to know everything.

You need to know enough to create leverage.

Enough to save time.
Enough to do better work.
Enough to solve real problems.
Enough to become hard to replace.

That’s it.

AI is one of the few shifts where a curious amateur can still catch up insanely fast.

Not because the tools are perfect.

Because most people are lazy.

They want the future.

They just don’t want to train for it.

So if you’re average, good.

Average means you still have upside.

The winners in the AI era won’t just be the smartest people.

They’ll be the people who got serious before everyone else was forced to.

Start small.
Use it daily.
Ignore the noise.
Build real skill.

That’s how average starts looking unstoppable.

Repost, like, and follow for more AI takes like this.

AI is either making kids wildly more creative
or quietly teaching them to stop creating.

And honestly, both arguments have receipts.

That’s why the conversation around AI and children gets so messy.

On one hand, this is the most powerful creative unlock most kids will ever touch.

A child with a half-formed idea can now turn it into a story, a song, a comic, a game concept, a lesson plan, a character world, or a prototype in minutes.

That is insane.

Kids who used to get blocked by drawing skill, writing skill, coding skill, or confidence can suddenly experiment at the speed of imagination.

That matters.

Because creativity is not just talent.

It’s momentum.

It’s curiosity.

It’s getting excited enough to keep going.

AI can absolutely give kids more shots on goal.

More exploration.
More iteration.
More confidence.
More range.

But here’s the part people don’t want to say out loud:

if AI starts doing too much of the thinking, the kid isn’t creating anymore.

They’re selecting.

They’re approving.

They’re consuming polished output and calling it self-expression.

That’s the danger.

Not that AI exists.

That it can make mediocre effort feel like mastery.

And children are especially vulnerable to that trap because they’re still building frustration tolerance, taste, patience, and problem-solving muscles.

A lot of real creativity comes from struggle.

From staring at the bad draft.
From fixing the awkward sentence.
From redrawing the hand five times.
From wrestling with the part that doesn’t work.

That friction is not a bug.

It’s where originality gets built.

So no, the question isn’t whether AI makes children more creative or less creative.

The real question is this:

are we teaching them to use AI to extend their imagination

or to outsource it?

Because those are two very different futures.

Used well, AI can help a kid think bigger.

Used poorly, it can train a kid to avoid thinking deeply.

That’s the knife’s edge.

Parents, teachers, and builders should be aiming for one standard:

AI should help children create more, not struggle less in every possible way.

Let it brainstorm.
Let it inspire.
Let it teach.
Let it help them prototype.

But don’t let it replace the blank page.

Don’t let it replace effort.

And definitely don’t let it replace the weird, imperfect, frustrating process that turns kids into original humans.

AI is a tool.

Not a substitute for imagination.
Not a shortcut to identity.
Not a replacement for the creative grind.

We’re not just deciding what kids can make with AI.

We’re deciding what kind of thinkers they become because of it.

Repost if this conversation matters. Like and follow for more.

Practicing AI skills feels pointless until it suddenly isn’t. It’s just like planting seeds for a future harvest

You spend an hour testing prompts. You automate a tiny workflow. You learn how agents work. You build a custom GPT. You connect two tools together and it saves 7 minutes.

Not exactly a life-changing harvest.

But that’s how sowing oats works. You don’t plant today and eat tomorrow. You plant because future you is going to need something to harvest.

AI is the same way.

Every prompt you test, every workflow you build, every bad output you debug, every automation you break and fix, every hour you spend learning what these tools can and can’t do is a seed.

And most people are wildly underestimating how valuable that field is going to become.

Because AI skill doesn’t compound like a normal software tutorial. It compounds like judgment.

You start noticing where AI helps and where it creates mess. You start seeing which tasks should be automated and which should stay human. You start understanding context windows, tool calls, memory, retrieval, evals, agents, workflows, and failure modes.

You stop treating AI like a magic text box.

You start treating it like infrastructure.

That’s the shift.

The winners won’t be the people who tried ChatGPT once. They’ll be the people who built instincts early. The people who practiced before they had to. The people who learned how to delegate to machines before their company made it mandatory.

You can’t cram AI fluency the night before your job changes. You can’t fake real reps. You can’t read one thread, save one prompt pack, watch one demo, and suddenly understand how to use AI to multiply your output.

You have to practice.

Messy practice. Boring practice. Daily practice. The kind that looks unimpressive from the outside but quietly becomes an advantage.

Eventually, the field starts producing. The prompt library becomes leverage. The automation experiments become systems. The weird tool knowledge becomes career insurance. The small workflows become a serious edge.

And the person who looked like they were “playing with AI” two years ago suddenly looks like the only person in the room who knows what’s going on.

So sow the oats now.

Not because every experiment will work. Most won’t.

Not because AI will replace every skill. It won’t.

But because the future is going to reward people who know how to work with intelligent systems.

And the best time to build that fluency was yesterday.

The second-best time is during lunch today.

Repost this if more people need to stop watching the AI shift and start practicing for it.

I didn’t order a Sunday delivery of flowers from FTD because I needed flowers. I ordered them because I wanted my mom to feel loved on Mother’s Day.

That’s what companies sometimes forget about “special occasion” products.

They aren’t really selling the object.

They’re selling the moment.

I paid the normal delivery fee.

Then I paid an extra delivery fee on top of that to make sure the flowers arrived on Mother’s Day. And I picked FTD because I thought they wouldn’t mess up.

They didn’t arrive.

No flowers.

No proactive message.
No update.
No “we’re sorry, here’s what happened.”

I called on Monday when my mom said she didn’t get the flowers. FTD said the flowers were still at the florist, and the solution offered was to deliver them two days after Mother’s Day with a $10 discount.

Yeah.

Did ChatGPT 3.0 come up with that solution?

And honestly, that’s where the lesson is.
The problem wasn’t just the failed delivery.
The REAL problem was the failed recovery.

Every company makes mistakes. Holiday logistics are hard. Demand spikes. Things break.

But if a customer pays extra for a time-sensitive promise and you miss the time-sensitive part, the product has changed.

A Mother’s Day bouquet delivered two days after Mother’s Day is not the same product.

It’s a reminder that the moment was missed.

The better move would have been simple:

Proactively notify the customer.
Own the miss.
Refund the premium delivery fee and then some. Maybe a full refund. We got that full refund in the end, but my wife had to fight them to get it, it wasn’t easy and it wasn’t relaxing. And it didn’t feel like an apology. It felt like taking a pound of flesh.

Make the recovery feel like an apology, not a transaction.

This is where customer loyalty is actually built.

Not when everything goes perfectly.

When something goes wrong and the company proves it understands what the customer actually bought.

P.S. mom said she still loves me

Learn from this!

Building a PowerPoint takes forever and most AI slides look generic and boring. That’s why Templafy’s free AI PowerPoint generator caught my attention.

It turns an idea into a structured presentation in under 5 minutes.

No credit card.
No trial.
No limits.

Just describe what you need.

Templafy asks smart follow-up questions before it starts building.
Then you can edit the content slide by slide.
That means no random output.

No messy structure.

No guessing what will appear in the deck.

You stay in control of the message.
Templafy handles the structure.
Then you download, edit, and present from PowerPoint.

It’s already trusted by 4M+ professionals.
Including teams at KPMG, BDO, and Adobe.
Save this carousel for your next proposal, report, or client deck.

Try it here: https://lnkd.in/gr8SxEj2

Usually, pulling complex SEO stats means bouncing between tools, exports, filters, spreadsheets, keyword lists, growth trends, KD scores, clusters, and strategy docs.

With Agent A, I can just describe what I want in plain English.

For example:
“Find trending AI marketing keywords in the US over the last 3 months, filter for growth + volume, cluster them, score them, and turn it into a content roadmap.”

And it came back with:
✅ 566 keywords analyzed
✅ 58 trending keyword opportunities
✅ 45 topic clusters
✅ Average growth rate of +214%
✅ Low-competition SEO openings like “how is AI changing SEO” with KD 0
✅ A phased roadmap for what to publish first, what to build next, and where the big authority plays are


That’s the part that blew my mind.

This wasn’t just a keyword list.

It was a full strategic view of where demand is moving, what topics are exploding, which keywords are still under-served, and how to turn those insights into content.


As an AI influencer, this is exactly how I use Ahrefs:
I look for the latest trending topics before they become obvious.
Then I use those trends to guide what I post, what I test, what I explain, and what I create.

The goal is simple:
Create content where demand is already rising.
That’s how you stop guessing and start giving yourself a real shot at going viral.

Agent A makes that process incredibly easy.

Instead of spending hours trying to pull the right SEO data, I can ask for the exact research I need on almost any topic and get back growth trends, keyword difficulty, topic clusters, content opportunities, and a roadmap I can actually use.

AI doesn’t replace strategy.

But when it’s connected to great data, it makes strategy move a lot faster.

#AI #SEO #Ahrefs #ContentMarketing #AIMarketing #CreatorEconomy #DigitalMarketing #Ahrefspartner

Your resume is killing your AI job prospects before a human ever reads it. Not because you’re unqualified. Because it reads like everyone else’s.

“Passionate about AI.”

“Experience with automation.”

“Strong problem-solving skills.”

“Familiar with ChatGPT.”

Cool. So is everyone with Wi-Fi.

If you want an AI job in 2026, your resume can’t just say you’re interested in AI. It has to prove you can use AI to create business value.

That means less vague enthusiasm and more receipts.

Don’t write:

“Used AI tools to improve productivity.”

Write:

“Built an AI-assisted intake workflow that reduced manual triage time by 40% across customer support requests.”

Don’t write:

“Experienced with LLMs.”

Write:

“Integrated OpenAI and Claude APIs into internal automation workflows using Workato, webhooks, and structured prompt outputs.”

Don’t write:

“Helped team adopt AI.”

Write:

“Created repeatable AI enablement playbooks for sales and operations teams, improving asset creation speed and reducing dependency on manual handoffs.”

The companies hiring for AI roles don’t need another person who knows the word “agents.”

They need people who can connect messy business problems to working systems.

So your resume needs to show three things:

You understand the workflow.

You can build or implement the solution.

You can measure the outcome.

That’s the holy trinity.

And please, stop making your resume sound like a museum plaque.

AI hiring managers don’t want a list of responsibilities. They want evidence that you can walk into chaos, find the bottleneck, and use AI to make something faster, cheaper, smarter, or more scalable.

The best AI resumes in 2026 won’t be stuffed with every shiny tool name.

They’ll be specific.

What did you build?

What model, platform, or automation tool did you use?

What system did it connect to?

Who used it?

What changed after it launched?

That’s what makes someone stop scrolling.

Because “I used AI” is not a skill anymore.

It’s the new “I know Microsoft Office.”

The skill is knowing where AI belongs, where it absolutely doesn’t, and how to turn a cool demo into an actual business process.

If you want an AI job, rewrite your resume like a builder, not a tourist.

Show the systems.

Show the _outcomes_.

Show the judgment.

Show that you’re not just playing with AI.

You’re using it to move work.

Repost this if someone in your network is job hunting, like it if it made you rethink your resume, and follow me for more on AI, work, and career leverage.

Everybody’s flexing their “AI stack.”

Almost nobody’s talking about what the stack is actually doing.

It’s not magic.

It’s not some cute little productivity upgrade.

And it definitely isn’t “here’s 14 tools I tried this weekend.”

The real shift is this:

the best founders are using AI to collapse entire layers of friction.

Support gets faster.
Content gets cheaper.
Outreach gets more personalized.
Product ships sooner.
Ops stop drowning in repetitive work.
Meetings stop eating the company alive.

That’s the game now.

Not “who has AI.”

Who built AI into the workflow deeply enough that headcount, time, and execution all start to look different.

That’s why a stack like this matters.

Intercom AI + ChatGPT API
for support that doesn’t sleep.

ChatGPT + image generation + copy tools
for marketing teams that can create in hours instead of waiting a week for one asset and three approvals.

Clay + GPT-4
for outreach that actually sounds relevant instead of mass-produced spam with a first name token shoved in.

Tableau + ChatGPT
for turning “we have data” into “we have a decision.”

Figma AI + Uizard
for getting from vague idea to clickable prototype before the meeting even ends.

Zapier AI + Make
for eliminating all the dumb little tasks that quietly steal half your company’s energy.

Fireflies + Notion AI
for making sure your team stops pretending anyone’s reading scattered meeting notes.

But here’s the part the graphics usually miss:

tools don’t replace departments.

Operators do.

A mediocre team with AI is still mediocre, just faster and louder.

A sharp team with AI becomes unfair.

They test more.
Ship more.
Learn faster.
Waste less.
Miss fewer signals.
And they stop hiring people just to move information from one tab to another.

That’s the real stack.

Not software.

Leverage.

And the companies that understand that are going to look insanely lean compared to the ones still building like it’s 2019.

A lot of businesses are still treating AI like a sidekick.

Something for brainstorming.
Something for writing a rough draft.
Something to summarize a call.

Cool.

Meanwhile, the killers are using it to redesign how work happens.

That’s a very different conversation.

Because once AI starts touching support, sales, product, design, analytics, ops, and internal knowledge all at once, you’re not just adding tools.

You’re rebuilding the company’s operating system.

That’s why this matters.

Not because every tool on this graphic is perfect.

They aren’t.

Not because every founder needs this exact stack.

They don’t.

It matters because the direction is obvious:

the winners are building systems, not playing with prompts.

And every founder who ignores that is basically choosing slower growth, higher overhead, and more chaos than they need.

That’s an expensive way to learn.

What’s in your AI stack right now?

Repost if you think more founders need to stop dabbling and start rebuilding.

Your LinkedIn reach is bad and nobody is seeing it. Not because you lack experience. Because you only show up on LinkedIn when you’re job hunting, fundraising, selling, or panicking.

By then, it’s usually too late.

Your professional presence is something you build before you need it.

But let’s be honest: most busy people don’t have hours to spend writing posts, tracking trends, engaging with feeds, or figuring out what sounds “authentic” without sounding cringe.

That’s why Raaye caught my attention.

Raaye is an AI LinkedIn Manager built for professionals who want to grow their career presence without living on LinkedIn.

It helps you go from:

idea → post → schedule → engage → analyze

All in one workflow.

The real value isn’t just “AI writes posts for you.”

It’s that Raaye helps you build a credible professional presence consistently.

You can create and schedule a week of LinkedIn content in minutes.
You can turn rough ideas into polished posts that still sound like you.
You can stop asking “what should I post today?” every morning.
You can stay visible without forcing generic viral content.
You can use AI comments, feed summaries, and trend insights to engage smarter instead of scrolling endlessly.

And that matters because LinkedIn is no longer just a networking site.

It’s where people discover talent.
It’s where inbound opportunities start.
It’s where recruiters notice patterns.
It’s where your expertise becomes searchable, visible, and remembered.

The best professionals I know are not short on experience.

They’re just under-visible.

Raaye feels like a practical tool for solving that.

Not by turning you into a “creator.”

But by helping you show up consistently, clearly, and professionally.

For busy founders, operators, job seekers, consultants, and ambitious professionals, that can be a real career advantage.

Check it out: https://tr.ee/QY6daJ

Getting along with your boss is not about agreeing with everything they say. It is about understanding how they think, what they care about, and how to communicate in a way that makes their job easier.

ChatGPT can help with that.

Before a difficult conversation, you can use it to practice what you want to say. Instead of walking into a meeting frustrated, you can ask ChatGPT to help you turn a complaint into a clear, professional request.

For example:

“I feel like my workload is becoming unmanageable. Help me say this to my boss in a calm, constructive way.”

You can also use ChatGPT to prepare updates your boss will actually appreciate. Many managers do not want every tiny detail. They want to know what is done, what is blocked, what needs a decision, and what is coming next.

A simple prompt might be:

“Turn these project notes into a concise update for my manager.”

ChatGPT can also help you understand your boss’s perspective. If they seem demanding, vague, or overly critical, you can describe the situation and ask:

“What might my manager be worried about here, and how can I respond productively?”

That does not mean your boss is always right. It just helps you pause before reacting and choose a response that moves the situation forward.

The real value of ChatGPT is not that it gives you magic words. It helps you slow down, organize your thoughts, and communicate with more intention.

A better relationship with your boss often starts with better communication. ChatGPT can be a useful tool for getting there.

Meditating every day is basically riding a bike for your mind.

Not in a cheesy wellness-poster way. In a “you can actually feel the system getting stronger” way.

When you ride a bike every day, you’re not trying to become a professional cyclist. You’re building rhythm. You’re getting your body moving. You’re training balance, endurance, and recovery one ride at a time. Meditation works the same way. You sit down. You breathe. Your mind wanders. You notice. You come back.

That’s the rep.

Not silence. Not enlightenment. Not some perfectly calm monk-brain where no thought ever appears again. Just noticing when your attention gets hijacked and bringing it back, over and over.

That sounds small until you realize your entire life is basically attention management. Your stress depends on where your mind goes. Your work depends on where your focus goes. Your relationships depend on whether you can pause before reacting. Your happiness depends on how often you’re actually present for the life you’re already living.

And most people are walking around with zero training. Notifications own them. Anxiety owns them. Urgency owns them. Other people’s moods own them. The algorithm owns them. Then they wonder why they feel mentally exhausted by lunch.

A daily meditation practice is like getting on the bike before the day runs you over. Even 10 minutes changes the tone. You start catching the spiral earlier. You stop treating every thought like an emergency. You notice the gap between stimulus and reaction. You become harder to drag around by noise.

That doesn’t mean meditation fixes everything. It doesn’t. And it doesn’t replace sleep, exercise, therapy, community, or solving the actual problems in your life. But as a daily practice, it’s one of the highest-return habits available.

No gear. No subscription. No commute. No optimization rabbit hole. Just sit down, breathe, and practice coming back.

The first few sessions might feel boring. Good. The first few sessions might feel chaotic. Also good. That’s not failure. That’s you finally noticing what your mind is doing all day.

Ride the bike anyway. Ten minutes today. Ten minutes tomorrow. Ten minutes the day after that.

Not because you’re trying to become a different person overnight. Because future you deserves a calmer nervous system, a steadier mind, and a little more space between the world poking you and you poking back.

Start today at lunch. Your brain could use the ride.

Repost this if more people need a daily mental bike ride.

Getting good results out of AI is a lot like scoring points in a fencing match.

You do not win by waving the blade around and hoping something lands.

You win by being intentional.

In fencing, every touch starts with distance, timing, and a clear line of attack. The same is true with AI. A vague prompt is like lunging from too far away. It looks energetic, but it usually misses.

The best results come when you set the measure first:

What do you want?
Who is it for?
What constraints matter?
What does success look like?

Then you engage.

Sometimes the first response is not the winning touch. It is a probe. You test the guard. You see how the system responds. You adjust your angle, refine your ask, add context, and go again.

Good prompting is not about one perfect command. It is about a disciplined exchange.

A fencer does not blame the sword for every missed point. They study the action. Was the attack clear? Was the timing off? Was the target defined?

AI works the same way.

The people getting the best results are not necessarily the ones using the fanciest tools. They are the ones who know how to direct the exchange. They give context, define the target, control the tempo, and make each follow-up sharper than the last.

AI is not magic.

It is a match.

And the point usually goes to the person with the clearest intent.

There’s a moment every January where “Happy New Year!” stops being festive…

…and starts being a cry for help.

Like:

January 1–2
Totally normal.
We’re all still metabolizing champagne.

January 3
According to Larry David… this is the line.
After this, you’re not spreading joy.
You’re forcing small talk.

January 4–7
Now it’s weird.
Not illegal.
Just weird.

January 8–15
At this point you’re basically wishing me “Happy New Year” as a personality trait.

January 16–31
No.
Now it’s not a greeting.
It’s a hostage negotiation.

If you missed the window, just say:
“Hope your year’s off to a good start.”

Clean.
Adult.
No one gets hurt.

So what’s the actual cutoff for you?

January 3?
First Monday back?
Or are you out here saying it in February like a menace?

AI fluency is becoming the new Excel fluency. And most people are still opening Claude like it’s a fortune cookie. No shade to fortune cookies, they’re bomb.

They type:
“Write this better.”
“Summarize this.”
“Give me ideas.”

Then they blame the model when the output is mid.

That’s not an AI problem.

That’s a user problem. And ultimately using AI is like riding a bike. You just need practice.

Claude101.com is basically the free crash course for people who don’t want to get left behind.

It walks you from:

Claude basics
team workflows
projects
slides
skills
Claude Code
API builds
and even how to stop Claude from just politely agreeing with your bad ideas


The wild part?

It’s free

The even wilder part?

Most people still won’t do it

They’ll spend 3 hours scrolling takes about AI replacing jobs…

Instead of spending those same 3 hours learning how to use the thing.

This is the part nobody wants to admit:

The gap isn’t between people who have AI and people who don’t.

The gap is between people who actually learn the workflows and people who keep treating AI like autocomplete with a fancier logo.

Claude101.com is one of those resources you should probably open before your coworker does.

Because once AI skill becomes table stakes, “I’m still figuring it out” stops sounding curious.

And starts sounding foolish

Lately, I’ve been thinking about the phrase “stop and smell the roses.”

It sounds simple. Almost too simple.

But in a world that rewards speed, constant progress, packed calendars, and the next milestone, pausing can feel surprisingly difficult.

We rush from meeting to meeting. Goal to goal. Deadline to deadline. And somewhere along the way, we can miss the small moments that make the work — and life — meaningful.

A kind message from a teammate.
A problem finally clicking into place.
A quiet morning before the day begins.
A conversation that reminds us why we started.

Stopping to smell the roses doesn’t mean losing ambition. It means creating enough space to appreciate the journey while we’re still on it.

Success matters. Growth matters. Hard work matters.

But so does presence.

This week, I’m reminding myself to slow down long enough to notice what’s already good.

What’s one “rose” you’re appreciating today?

#Leadership #Mindfulness #Growth #Gratitude #WorkLifeBalance

Icon came.
Blew up the internet.
Then died.

Omneky raised a ton.
Then became a rounding error.

Not because “AI ads” is fake.
Because ads are not a tool problem.

Ads are a system.
And the missing piece was always the same:
a real human feedback loop from people who have actually spent serious money.

That’s why Airpost is interesting.

Airpost is a hybrid AI ads machine built for performance advertisers.
Platform + service.

AI does the heavy lifting.
Experienced creative strategists do the part AI keeps hallucinating:
taste, context, iteration, and ruthless prioritization of what actually wins.

The core idea is simple (and kind of unfair):
a taxonomy for how ads work.
Strategic pattern → narrative angle → execution.
So you can find what’s working, then scale it into dozens of new swings per week.

Airpost is built by the ReadySet team.
The “we shipped an AI wrapper” crowd can’t fake that.
They’ve deployed $100M+ in ads, and it shows in the positioning.

And the proof points are spicy:
DoorDash reportedly saw Airpost ads beat internal ads by ~40% better CAC.
Cloaked ran $1M+ in spend through Airpost ads.

If you’re spending $250k+/mo on paid social, this is the real pitch:
Stop asking your team to be a content studio.
Give them an ad factory that learns.

Launching Jan 20, 2026.

#partner [https://lnkd.in/g_rr36jp)

Most people think the weekend starts Saturday morning.

It actually starts Friday afternoon.

How you close out your week decides whether you spend Saturday genuinely recharging or quietly carrying Monday's stress around with you.

A few things that make the difference:

Tie up the loose ends. Send the email you've been avoiding. Reply to the message sitting in your drafts. Unfinished tasks have a way of following you home and whispering in your ear all weekend.

Write down Monday's three priorities before you log off. Future you will thank present you. Walking in Monday with a clear plan beats walking in to a blank slate and a racing mind.

Do a five-minute reset. Clear your desk, close the tabs, file the chaos. A clean starting point on Monday is a gift you give yourself on Friday.

Actually disconnect. The work will be there Monday. Protecting your weekend isn't slacking, it's the thing that lets you show up sharp when it counts.

The goal isn't to grind harder on Friday. It's to land the plane properly so you can step off and switch off.

Do Friday right, and the weekend stops feeling like a frantic recovery. It starts feeling like rest.

How do you close out your week?

Your resume is competing against AI now.

Not just other candidates.

AI.

Because the average resume in 2026 reads like it was written by the same prompt.

Polished.
Generic.
Soulless.
And instantly forgettable.

Here’s how to tune yours up so it survives the bots
and wins the humans.

Start with the uncomfortable truth:
Hiring is filtering.

AI screens.
ATS parses.
Recruiters skim.

So your resume needs two things at once:

Machine clarity.
Human conviction.

Make it pass the machine test

Single column.
Normal headings.
No text boxes.
No fancy graphics.
Simple fonts.

If a scanner can’t reliably pull your titles, dates, skills, and results, you are invisible.

Now the part that actually makes you stand out in a sea of AI

Stop describing your job.
Start proving your impact.

Every bullet should answer:

What did you change?

Not “responsible for…”
Not “worked on…”
Not “helped with…”

Changed.

Use this bullet formula:

Problem - Action - Result - Proof

Problem: what was broken or missing
Action: what you actually did
Result: the measurable outcome
Proof: a link or artifact if possible

Metrics beat adjectives.
Every time.

“Improved customer retention” is fluff.
“Cut churn from 5.2% to 3.9% in 90 days by rebuilding onboarding emails” is a receipt.

Add receipts.

A one-page “proof strip” near the top:

Portfolio
GitHub
Case study
Demo video
Writing sample
Before and after

Skills-based hiring keeps accelerating, and proof travels farther than pedigree.

Kill the AI voice

If your summary sounds like it could belong to anyone, it will.

Replace it with a clear point of view:

“I build X for Y by doing Z.”
“I’m strongest when the problem is messy and the stakes are real.”
“My edge is turning ambiguity into shipping.”

AI can write words.
It can’t write your judgment.

Customize without rewriting your life

Do not make 50 versions.

Make 1 strong base resume.
Then for each job:

Mirror 10 to 15 keywords from the posting.
Reorder bullets so the most relevant wins are first.
Swap in 2 to 3 bullets that match the role exactly.

You’re not gaming the system.
You’re communicating in the language the system is scanning for.

Finally, show you’re more than a tool-user

In 2026, “I know the tools” is table stakes.

Hiring managers want to see how you think, collaborate, and drive outcomes, especially as AI automates more of the easy work.
Business Insider

So highlight:

Cross-functional wins
Decision-making under constraints
Tradeoffs you owned
Projects you drove from zero to shipped

That’s the difference between “AI-assisted candidate”
and “person who gets things done.”

Repost, like, and follow if you want more 2026 job-search playbooks.

The scary future of AI is not that it becomes conscious.

It’s that we become passive.

A new independent evaluation from Mount Sinai found ChatGPT Health under-triaged more than half of the cases that physicians said required emergency care. The study tested 60 scenarios across 21 specialties and 960 total interactions.

Read that again.

Not “got a few things wrong.”

Not “needs refinement.”

More than half
of the cases
where a real human should have been told:

go to the hospital.

And the machine said:
you can probably wait.

This is the part of the AI future people keep missing.

The danger is not just bad answers.

It’s outsourced judgment.

We are training people to do something insanely dangerous:

feel symptoms
open app
ask machine
wait for permission
delay action

That loop is going to kill people.

Not because AI is evil.

Because it is confident.
convenient.
always available.
and increasingly treated like authority.

That is the nightmare.

Not robot doctors taking over hospitals.

Normal people
alone
at 11:47 PM
scared
short of breath
half-hoping it is nothing
asking the world’s smoothest liar
whether this can wait until morning.

And getting told yes.

This is how the scary future actually arrives.

Not with chrome robots.

With soft language.

With beautiful interfaces.

With products designed to feel calm
when you should be panicking.

The machine does not need to be right all the time.

It just needs to be trusted
at the wrong moment.

That is enough.

And this is bigger than healthcare.

Because once society gets used to AI as the first stop for medical judgment,
it becomes the first stop for legal judgment,
financial judgment,
emotional judgment,
moral judgment,
parenting judgment,
everything.

We are not just building tools.

We are building a generation
that reflexively asks software
to interpret reality for them.

That should terrify you.

Especially because ChatGPT Health launched into a market where experts were already warning it is not regulated like a medical device or diagnostic tool, with no mandatory safety controls, risk reporting, post-market surveillance, or requirement to publish testing data.

So yes,
the future will be full of astonishing AI.

It will also be full of people dying,
losing money,
making terrible decisions,
and misunderstanding their own lives
because the machine sounded composed.

The scariest version of AI is not a superintelligence.

It is a very normal intelligence
wrapped in trust
scaled to billions
and consulted in moments
where hesitation has a body count.

Delve just pulled off a Valentine’s Day growth hack that feels unfair.

They asked the community one question
“What do you value about Delve?”

Then they did the obvious thing nobody actually does
they listened
collected the sticky notes
and turned them into a real billboard

That’s not “cute branding”
That’s a content engine
a trust signal
and customer research
all in one stunt

Even the line is a flex
not “SOC2 + HIPAA”
“Built with love for YOU.”

If you’re building in a boring category
this is how you make people feel something
and get shared for it

https://delve.co

AI agents are becoming a commodity.
The differentiator is the OS that ships them.

Because “we built an agent” is not the hard part anymore.

The hard part is:

Getting to production fast
Not in 6 months
In weeks

Making it safe to scale
With monitoring
Observability
Billing controls
Security and compliance

And turning agents into revenue
Not just “cost savings” in a deck

That’s why Vida caught my attention.

Vida is an AI Agent Operating System built for ROAI and speed-to-market.

Crawl-walk-run deployments
A framework that plugs into your stack
And gets real agents live quickly

Plus white-label and reseller options.

So if you’re a SaaS business trying to add a new product line
Or an MSP, BPO, or call center looking for a new margin engine
Vida is built to be a money maker, not just a cost saver.

Also - omnichannel is not an add-on here.

Inbound and outbound via:
Phone
Text
Email
Webchat

At real scale too - tens of thousands of calls and texts daily, and hundreds of millions of AI agent interactions supported.

If your “agent strategy” currently ends at a demo…

Maybe it’s time to start thinking like an operator.
Check it out today at [https://lnkd.in/gQYcBHUc)

2019 would never believe 2026.

2019 was standing in the doorway of the future with clean shoes, a half-packed suitcase, and hope folded carefully in its pocket. It thought the years ahead would arrive like open windows, like music from crowded rooms, like plans written in pen because surely the world was steady enough to keep them.

2019 thought we were tired then.

It did not know tired could become a climate.
It did not know “normal” could be something we mourned and then slowly forgot the shape of.
It did not know the future could show up wearing a mask, holding a receipt, asking for a subscription fee, and charging extra for breathing room.

Now here we are in 2026, living in the aftermath of too many things at once. Everything costs more than it should. Everyone is carrying something they do not have the language for. The news feels like a storm that learned how to refresh itself. We laugh, but it comes out thinner now. We say “it is what it is” like a prayer, like a little white flag we wave just to get through the day.

2019 would ask why we look much older.

In our eyes.
In the way we pause before getting excited.
In the way we do not trust good news until it survives the week.
In the way we have learned to hold joy gently, like something that might be taken back.

2019 would not understand how groceries became a luxury, how rest became a strategy, how peace became something you schedule between obligations. It would not believe so many dreams got postponed, renamed, downsized, or buried beneath bills, burnout, and the pressure to keep functioning while the world keeps flickering.

Back then, the future still looked glossy. It had concert tickets, airport gates, crowded tables, easy hugs, five-year plans, and the careless optimism you only recognize after it is gone. We thought we were anxious, but at least the ground still felt like ground. At least tomorrow seemed possible.

2026 feels different.

It feels like standing under a sky that keeps changing its mind.
It feels like scrolling through a tragedy while eating dinner.
It feels like waking up and trying to build a small, survivable life out of noise.

And still, somehow, we are here.

Still making coffee.
Still sending memes.
Still falling in love, still missing people, still finding songs that understand us.
Still laughing in kitchens.
Still lighting candles.
Still planting tiny joys in the cracks of an impossible year.

Maybe that is the part 2019 would believe least of all.

Not that 2026 is awful.
Not that the world got heavier.
Not that we became fluent in uncertainty.

But that after all of it, after every strange and bitter season, we are still trying.

Still here.
Still soft in places.
Still looking for beauty like it owes us an explanation.
Still pretending we are fine, and then sometimes, miraculously, actually being fine for a moment.

2019 would never believe 2026.

Some days, neither do I.