People are confusing generated intelligence with wisdom.
If I told you there were “artificial ingredients” in your food, would you eat it?
People are now using AI to fake being human more than ever…and people are proud of it!
When did we become so captivated by the artificial that we stopped valuing the real thing?
Tools like ChatGPT and Claude are incredibly powerful. I use them every day. This isn’t anti-AI.
The irony is that while technology continues to make communication easier, many interactions feel less human than ever. Everyone has the perfect answer, a polished LinkedIn profile, insights to share, and an impressive persona.
Yet genuine connection feels harder to find.
Fake videos.
AI-generated faces.
Fake podcasts.
Celebrity voices.
Fake personalization.
Deepfakes.
Fake “authenticity.”
AI can write your emails. It can write your posts. It can improve your grammar, organize your thoughts, and make you more efficient. Those are incredible advantages.
What it cannot do is replace your character.
Genuine people stand out.
In a world filled with automation, artificial intelligence, curated personas, and manufactured expertise, genuine people stand out. The leader who tells the truth when it’s uncomfortable stands out.
I think we need to ask ourselves a real question: have we become so obsessed with appearing intelligent, powerful, and impressive, that we forgot how to simply be genuine?
Many years ago, I invented the word: GENUOSITY.
Genuosity is the combination of authenticity and being genuine in your interactions with others.
Because trust, relationships, leadership, hiring, and long-term success are all built on genuine human connection.
AI can enhance communication and productivity, but it cannot replace trust, character, authenticity, or genuine relationships.
As more communication becomes automated, curated, and AI-generated, genuine human interaction becomes increasingly valuable and memorable.
Because as more content, communication, and interactions become automated, genuine human connection becomes increasingly valuable. In a world full of artificial signals, people are naturally drawn toward what’s real.
People hire people.
Always have.
Always will.
The tools will change.
Technology will evolve.
Trust has always been built the same way: one genuine interaction at a time.
That’s the part people will remember. It’s not about AI. It’s about trust.
That’s The Averity Experience.
Written By: Chris Allaire
Trust is eroding across the entire hiring market.
AI sourcing.
Automated screening,
AI outreach.
AI-generated resumes.
AI interview prep.
AI candidate matching.
Fake candidates.
Keyword stuffing.
Automation layered on top of automation.
At some point, you have to ask the obvious question:
The recruiting market has become flooded with automation pretending to be expertise. Candidates are using AI to write resumes. Companies are using AI to screen those resumes. Recruiters are using AI to interview candidates. Candidates are using AI to answer screening questions.
Hiring managers are increasingly seeing fake candidates, inflated resumes, keyword-stuffed applications, and rehearsed interviews. As a result, many candidates appear impressive on paper but struggle during real conversations.
On the other end, candidates are exhausted.
Spam messages.
Automated follow-ups.
One-click applications.
Zero feedback.
Zero relationships.
The hiring process has started to feel less human at the exact moment companies need great people the most.
Let’s get back to fundamentals.
At Averity, we believe technology should support recruiting — not replace judgment, relationships, and real qualification.
The best way to screen technology candidates is through real technical conversation, not automated keyword filtering.
Articulation.
Communication.
Intellectual Curiosity.
Attitude.
Aptitude.
Ultimately, these are the qualities companies are truly hiring for, but are they actually being evaluated during the hiring process?
Strong screening includes:
The goal is not to find the best resume. The goal is to find the best person for the role.
A good technology recruiter understands both people and technology, allowing them to evaluate candidates beyond resumes and technical keywords.
The best recruiters:
Great recruiting is advisory work — not resume forwarding.
Many internal hiring teams are overwhelmed by application volume, AI spam, scheduling fatigue, and lack of specialized screening experience.
Technology recruiting firms help companies:
The right recruiting partner acts as an extension of the business — not a transactional vendor.
AI can generate content and streamline workflows while accelerating hiring processes.
But AI cannot replace trust, judgment, relationships, and human understanding.
At Averity, we believe the market is entering an old phase that is new again — where trust becomes the differentiator again.
Ultimately, People still hire people and the right recruiting partner can make all the difference.
Written By: Chris Allaire
In this article — key takeaways:
The Averity Experience: Provide an unparalleled experience to everyone we interact with.
Everyone wants to work with and for “the best”.
The best technology recruiting firm isn’t defined by size, tools, or brand—it’s defined by how consistently it delivers results through trust, communication, and real human understanding.
What its not:
Those things are surface-level.
Ping pong tables, catered lunches, unlimited PTO, office perks — those are nice. They may look impressive on the surface, but they rarely earn trust, secure the right hires, or make a lasting impact.
The best is a culture. A standard. A way of operating.
In my world, it’s Technology Recruiting.
Firms like Averity have built their reputation on this exact model.
Why?
The best recruiting firms operate from a completely different foundation.
The best firms have a culture where:
That internal culture doesn’t stay internal.
It shows up in every interaction:
Candidates feel it. Clients feel it.
And when that’s real, everything changes.
There’s a dangerous shift happening in the market right now.
Automation is increasing.
AI screening is becoming more common.
“Efficiency” is often the selling point.
And less humanity.
The market is shifting toward automation, but this often reduces quality in hiring outcomes
Here’s the truth:
Great recruiting is not about passing tests, filtering resumes, or talking to bots.
It’s about:
That’s how real matches happen.
If you’re hiring or looking for a job, here’s what to look for:
You’ll know quickly.
Because the best firms don’t just say they care — they prove it in every step of the process.
Yes, results are part of the equation.
But results without integrity are not repeatable.
The firms that consistently deliver at a high level do it because:
That’s the difference.
There is no scoreboard. There’s no universal ranking system. No definitive leaderboard.
Awards can help. Reviews can help.
But the real signal?
That’s the market voting.
That’s reputation — earned, not marketed.
Being the best technology recruiting firm isn’t about scale, tools, or branding.
It’s about:
When that’s in place, everything else follows.
Because at the end of the day:
People hire people.
And the best firms never forget that.
The best technology recruiting firms combine strong communication, deep market knowledge, and a human-first approach. They focus on understanding both clients and candidates, rather than relying solely on automation or resume matching.
Look for transparency, responsiveness, preparation, and consistency. The best firms ask thoughtful questions, provide honest feedback, and follow through on commitments.
AI is a tool, not a replacement. The best recruiting firms use technology to enhance efficiency; however, they still rely on human judgment, relationships, and communication to make successful placements.
A recruiting firm’s internal culture directly impacts how they treat clients and candidates. Strong cultures lead to better communication, deeper understanding, and stronger long-term results.
Candidates should look for honesty, clarity, preparation, and someone who genuinely understands their goals — not just someone trying to fill a role quickly.
Written By: Chris Allaire
So, where is all this advice coming from?
Now, before taking anything seriously, are you asking:
If the answer is no… then why are you thinking like them?
Most of what you read these days is noise. Knowing who you listen to in business matters more than ever, because the wrong inputs quietly shape weak decisions, bad hiring, and wasted effort.
After all, people sound sharp, confident, and polished; but a lot of them have never actually carried the weight of what they’re talking about.
If you want to separate in 2026, this is one of the simplest levers:
Tighten who you listen to.
Right now, you’re hearing:
“Use AI to screen everything.”
“Speed wins.”
“Volume solves it.”
At first, it sounds great.
But the best teams? They’re doing the opposite.
Instead, they’re going deeper on fewer people, and actually understanding motivation, fit, and reality. After all, one bad hire costs more than a slower, better decision. That’s why better hiring decisions still come from judgment, not just automation.
One bad hire costs more than a slower, better decision.
Of course, bad advice doesn’t always look bad upfront.
Sometimes it sounds smart.
Sometimes it feels efficient.
Sometimes it aligns with what you want to hear.
But over time, it creates:
Ultimately, you don’t need more advice.
You need better inputs.
Because you will start thinking like the people you listen to.
So be ruthless.
Not about who sounds good—
but about who’s actually done it.
So, if you want better decisions in 2026, pay closer attention to who you listen to in business and be ruthless about filtering the noise.
Written By: Chris Allaire
What actually works when everyone has the same tools—but not the same judgment
In this article — key takeaways:
If you’re trying to recruit AI and Software Engineers in 2026 using the same playbook from 2021–2023, you’re already behind.
The biggest misconception right now?
That better tools = better hiring.
Many teams assume better AI tools automatically lead to better hiring outcomes. In reality, that is rarely true. Today, AI sourcing tools, LinkedIn scraping, and instant outreach generation are available to everyone. However, equal access to tools does not mean equal results.
Instead, many teams are seeing worse outcomes because:
As a result, the companies winning right now aren’t louder.
They’re HUMAN.
If you want to recruit AI talent and software engineers, start by rethinking your outreach strategy.
You can send 500 automated messages…
Or you can also send 15 thoughtful ones that actually start conversations. The second approach works better.
Top AI and Software Engineers aren’t sitting around waiting for job posts. They’re:
As a result, generic outreach rarely works with AI and software engineers who already know their value.
If your outreach looks like it was written by a machine, it’s ignored like one.
What works instead:
This isn’t about being “nice.”
More importantly, It’s about signaling credibility and effort.
In 2026, personalization is no longer optional when recruiting AI and software engineers. It is the first credibility test.
AI has a role in recruiting. Screening resumes at scale? Fine.
Organizing data? Great.
However, using AI to interview AI and software engineers is one of the fastest ways to lose top talent.
Here’s what strong engineers are telling us:
High-level engineers want to:
That requires a real conversation.
If your process removes the human element, the best candidates remove themselves.
Most companies are still guessing.
They assume:
In reality, top AI and software engineers in 2026 are optimizing for:
1. Problem Quality
Is this worth solving? Does it matter?
2. Technical Ownership
Can I make decisions, or am I maintaining someone else’s legacy?
3. Leadership Competence
Will I be working for people who understand what “good” looks like?
4. Signal Over Noise
Is this a focused environment—or chaos disguised as opportunity?
Yes, compensation matters.
But it’s rarely the deciding factor at the top end.
This is where most hiring processes break.
Companies want:
In 2026, the market is sharper:
So if you want a Ferrari, you cannot pay for a Honda.
More importantly, when your expectations and compensation are out of alignment, you do not just lose one candidate. You also weaken your reputation in the market. And because reputation compounds, that damage spreads faster than most companies realize.
Therefore, if you want to recruit AI and software engineers successfully, your compensation, scope, and expectations need to make sense together.
And reputation compounds—fast.
After years of automation, the pendulum is swinging back.
The best hires are still happening through:
Not through job boards, generic cold outreach, or AI-generated funnels.
This is where companies either:
Because when a high-impact role opens, speed doesn’t come from tools.
It comes from access and trust.
Recruiting AI and Software Engineers in 2026 isn’t about having better technology.
It’s about:
The companies that win aren’t trying to out-automate the market.
They’re doing the opposite:
Everyone has the same tools now.
That’s not the advantage anymore.
The advantage is knowing how—and when—not to use them.
If your hiring strategy still depends on volume, automation, and transactional outreach, you will keep losing the people you most want to hire.
But if you lead with judgment, thoughtful outreach, strong alignment, and real relationships, you will stand out to AI and software engineers for the right reasons.
If you’re hiring AI or Engineering teams and want a clearer picture of what top talent is actually responding to right now, this is exactly where Averity starts.
Written By: Chris Allaire
The AI Ecosystem will make you stronger or weaker.
Research from JYX and Carnegie Mellon shows that overreliance on AI erodes critical thinking and expertise. Like any muscle, judgment and skill require constant use — or they weaken over time. In other words, AI and critical thinking are deeply connected:
AI should sharpen you. If it’s dulling you, that’s a problem.
Where is the separation happening right now?
The more people rely on AI to do their thinking, the less capable they become at thinking on their own.
Just like a muscle. If you don’t use it, you lose it.
It can.
Overreliance on AI reduces active problem-solving, which weakens critical thinking over time, similar to muscle atrophy from lack of use.
It is an amplifier, but it feels productive. You’re moving faster, and generating more; but here’s what’s actually happening under the surface:
Because tools are now widely accessible.
The differentiator is no longer access, it’s the ability to interpret, validate, and apply information effectively.
That is why AI and critical thinking must work together. One gives you speed, while the other gives you direction.
By combining AI speed with human judgment, deeper thinking, and real-world decision-making ability.
They’re using it like a training partner, not a crutch. The keyword here is HELP.
HELP me with:
But are you pushing back and double checking its work? Are you looking at this with a few simple questions:
Think First, Then Prompt
Think before prompting, challenge outputs, and regularly make decisions without AI assistance to maintain independent judgment
Before you ask AI anything, take 2–3 minutes and outline your own answer. This keeps your brain in the driver’s seat.
Challenge the Output
Don’t just read it, push on it.
Treat AI like a junior analyst, not the decision-maker.
Blindly accepting outputs without questioning accuracy, assumptions, or completeness.
Rebuild From Memory
After using AI, close the tab and explain the idea in your own words. Can you repeat what was written? If you can’t, you didn’t learn it, you borrowed it.
Make Decisions Without It
Can you get to point B without Google Maps?
No prompts. No personal assistant. That’s your mental gym. Test yourself.
The people who win in this next ecosystem won’t be the ones who use AI the most. They’ll be the ones who can still think without it.
The people who win in this next ecosystem will not be the ones who use AI the most. Instead, they will be the ones who can still think without it.
That is the real edge.
In the end, AI and critical thinking are not enemies. However, they only work well together when AI remains a tool and human judgment remains in charge.
Written By: Chris Allaire
You have more competition now than ever before. A few years ago, the advantage was tools.
Software, data, automation, systems.
If you had the best stack, you were ahead.
Today?
Everyone has the same sports car.
The tools that used to separate professionals are now widely available to anyone with a laptop and a subscription.
Which means something interesting is happening.
The separation is no longer tools.
The separation is skill.
You’ve heard my analogy before.
Give a bad golfer the best clubs in the world.
Give a great golfer the best clubs in the world.
Do they suddenly become equal?
The great golfer gets even better.
The bad golfer just slices the ball farther into the woods.
The clubs didn’t create the talent.
They amplified it.
What skills do I have that tools can’t replace?
Instead of chasing every tool, high performers ask deeper questions.
In sports, the best athletes don’t try to play every role.
They dominate one position.
Yet in business, many professionals try to do everything:
At some point you have to ask:
Am I playing the position where I’m actually elite?
Or am I spreading myself thin trying to keep up with technology?
Simon Sinek talks about starting with why, but the next step is identifying where your real strengths live.
The most powerful careers usually sit at the intersection of three things:
That’s your lane.
Everything outside that lane becomes noise.
Tony Robbins often warns about a common trap:
People major in minor things.
AI can accelerate this problem.
You can spend hours:
This can FEEL productive.
But elite performers constantly ask:
Is this the highest leverage use of my talent today?
If the answer is no, then move on quickly.
The biggest unlock for high performers isn’t what they add.
It’s what they eliminate.
If something:
You don’t optimize it.
You remove it.
Learning to say no is one of the most powerful career skills in the AI era.
(5-step framework)
For professionals wondering how to stay valuable as AI advances, the answer isn’t chasing more tools.
It’s sharpening your edge.
Ask yourself:
What do people consistently come to me for?
Pattern recognition.
Decision-making.
Strategy.
Communication.
Technical depth.
That’s your foundation.
The best operators don’t try to be great at everything.
They remove work that pulls them out of their strengths.
This is where AI becomes powerful.
Not as a replacement.
But as a delegation engine.
Technology evolves.
Human expertise compounds.
Professionals who dominate a field develop something tools cannot replicate easily:
Judgment.
Judgment only comes from experience.
The smartest professionals are not outsourcing thinking to AI.
They are using it to accelerate execution.
Writers use it to move faster.
Engineers use it to test faster.
Researchers use it to analyze faster.
The tool doesn’t replace their talent.
It multiplies it.
Tools don’t create momentum.
Action does.
You can study systems, prompts, strategies, and frameworks forever.
But progress only happens when ideas turn into execution.
Execution is still the ultimate separator.
AI is extremely good at accelerating tasks, but it struggles with uniquely human abilities such as:
The professionals who stay valuable in the AI era are those who combine deep human expertise with AI leverage, rather than relying on AI to do the thinking for them.
No.
AI gives everyone access to powerful tools, but tools do not equal skill.
Just like giving every golfer the same clubs doesn’t produce the same score, giving every professional the same AI tools does not produce the same results.
AI amplifies what already exists:
The real separator remains human skill and judgment.
The professionals thriving in the AI era tend to follow a few consistent principles:
The future doesn’t belong to people who simply use AI.
It belongs to people who combine expertise, judgment, and technology effectively.
A useful framework is to look at the intersection of three things:
Where those three overlap is often your true professional edge.
AI should then be used to amplify that edge, not distract you from it.
Many professionals fall behind because they become distracted by tools instead of focusing on outcomes.
Common traps include:
Technology rewards those who already have clarity.
Without clarity, tools simply amplify confusion.
As artificial intelligence becomes widely available, the professionals who stand out tend to share several traits:
Tools are becoming universal.
Skill is becoming scarce again.
And scarcity is where value lives.
Written By: Chris Allaire
We are living in the golden age of tools.
From OpenAI to Zapier to Notion, automation platforms promise speed, scale, and simplicity. And they deliver — when used correctly.
But here’s the uncomfortable truth no one wants to say out loud:
Automation doesn’t create excellence.
Instead, it amplifies whatever already exists.
If the foundation is clear, automation creates leverage.
If the foundation is messy, automation creates chaos — faster.
That’s why Rule #5 in the Separation Playbook is simple: Manual First. Automation Second.
Manual First. Automation Second.
Right now, we’re watching a shift in the market right now.
AI tools are accessible to everyone, so your competitor has the same platforms you do.
Meanwhile, candidates are using these tools, and clients are adopting them too.
Therefore, the tools are no longer the differentiator.
Judgment is.
Before automating anything in recruiting, operations, sales, finance, or product development, there are three questions elite operators ask:
Most people skip this step, and the result is predictable.
They automate before they diagnose, so the system scales the wrong thing.
They scale before they standardize, which makes outcomes inconsistent.
They systematize before they simplify.
And then they wonder why the machine produces garbage.
In tech recruiting, this shows up constantly.
Companies want to:
But if you don’t understand:
You’re not scaling :efficiency.
You’re scaling noise.
We’ve seen this across ATS systems like Greenhouse and Lever. The software isn’t the problem. The inputs are.
When the process is unclear, automation multiplies the confusion.
Similarly, when the criteria are weak, automation spreads weak decisions at scale.
And when the human element is removed too early, trust erodes.
Top-tier leaders earn the right to automate.
They:
Only then do they automate.
Because automation should preserve excellence — not attempt to create it.
If you can’t:
Then you don’t have a scalable process.
You have a dependency.
That’s the core of manual vs automation: are you scaling mastery, or outsourcing understanding?
Ultimately, the answer determines whether automation becomes leverage or liability.
Let’s be clear.
This is not anti-AI.
Moreover, this is not anti-automation.
This is not anti-scale.
We use technology every day.
But we refuse to outsource thinking.
The plumber still knows plumbing even if he uses power tools.
Likewise, the surgeon still understands anatomy even with robotic assistance.
In the same way, an elite recruiter still understands people — even with AI at their fingertips.
So yes, tools are force multipliers.
But, humans are the force.
If you’re a CTO, CEO, Founder, or VP hiring in AI, Security, Infrastructure, Robotics, or Product, this matters.
Before automating:
1. Map the Workflow Manually
Write it out. Step by step. From first contact to final outcome. If you can’t explain it clearly, don’t automate it.
2. Identify Decision Points
Where does judgment matter? Where does nuance exist? Automation handles repetition. Humans handle ambiguity.
3. Remove Unnecessary Complexity
Most processes are bloated. Simplify first. Automation should follow simplicity — not hide inefficiency.
4. Stress-Test Without Tools
If your CRM, ATS, or AI assistant vanished tomorrow, could you still execute?
If the answer is no, you don’t have a system.
You have software.
The market right now is obsessed with speed.
But speed without understanding is fragile.
The leaders separating themselves in 2026 aren’t the ones who automated first.
They’re the ones who:
Then layered automation on top.
Because when you automate clarity, you scale power.
When you automate confusion, you scale regret.
Technology is extraordinary.
But so are you.
Before you automate the next workflow, ask yourself:
Automation is a privilege, not a shortcut.
Earn it.
And when you do, it becomes unstoppable.
Written By: Chris Allaire
Why action — not information — builds real leverage
There’s a quiet tax most leaders pay.
It’s hesitation.
In a market drowning in podcasts, newsletters, AI tools, dashboards, and “insights,” the real divider isn’t access to information.
Instead, it’s leadership execution.
Reputation isn’t built in theory.
It’s built by action.
Tony Robbins has said it for decades:
Knowledge is not power.
It’s potential power.
Real power is generated only when knowledge is applied.
Robbins often emphasizes something that elite operators already understand:
Meanwhile, the “I know, I know” mindset leads to stagnation.
We’ve all seen it:
“I know I should make that call.”
“I know we need to recruit proactively.”
“I know we should have that tough conversation.”
“I know we need to move faster.”
However, knowing without doing is disguised procrastination.
And in hiring, leadership, and business — procrastination is expensive.
In recruiting, I see it constantly.
A founder delays outreach because the org chart isn’t perfect.
A CTO waits for “final budget approval.”
A VP hesitates because the job description isn’t perfect yet.
Meanwhile:
The best talent gets proactively recruited by your competition.
The best candidates are getting offers because they add value, not fit a mold.
The companies separating right now aren’t the most informed.
They’re the ones willing to take a chance.
Look at companies that built while still iterating:
None waited for perfect conditions.
They moved.
Then they adjusted.
Then they compounded.
One of the most dangerous phrases in leadership is:
“I already know that.”
If you truly knew it, it would be visible in your behavior.
Applied knowledge creates progress.
Collected knowledge creates comfort.
And comfort feels safe…
until you realize someone else took the shot.
That’s why leadership execution is so visible in outcomes: it turns insight into behavior, and behavior into results.
Taking action doesn’t mean being reckless.
It means:
You don’t need a flawless strategy.
You need momentum and leadership execution that turns momentum into progress.
Momentum is built through consistent, imperfect action.
If you’re building a company, scaling a team, or leading a function, ask:
These aren’t philosophical prompts.
They’re operational diagnostics for leadership execution.
We’re not divided by tools.
Instead, action divides us.
Everyone can access the same information.
Few people act on it.
Execution is everything.
Take the shot.
Momentum is cheaper than regret.
If you’re a CTO, CEO, or VP building in AI, Security, Platform, or Product:
Waiting is not neutral.
It rewards the one with leadership execution — the one who takes action.
If you’re unsure whether to engage, start the conversation.
After all, if you don’t take a shot, you’ll never score.
Written By: Chris Allaire
Right now, everyone has access to the same information.
The same tools.
The same AI assistants.
The same tutorials.
However, that knowledge doesn’t equalize ability.
So the question isn’t:
“Can you figure it out?”
Instead, the question is:
“Can you see it immediately?”
Because when something matters — revenue, security, uptime, people, risk — nobody wants a well-intentioned generalist experimenting on their problem.
They want the person who’s seen this exact failure pattern a hundred times before.
That’s exactly why specialization in 2026 is becoming one of the most valuable advantages in the market.
Are you handing over your tax and financial documents to a mechanic?
If a pipe bursts, would you call an electrician?
Since when would you turn something critical over to a “generalist”? Come to think of it, what is a “Generalist” in the first place? When you study the best in breed and the people at the top of the pyramid, they’re not generalists. They’re EXPERTS.
In life, we know this, but why does this somehow get ignored in business?
Could they just Google it? Don’t they have ChatGPT?
Of course!
But because experience matters more than information.
The plumber doesn’t need to “look it up.”
They walk in, glance at the pipe, and already know where the problem is.
As a home owner, how does that make you feel?
Assured.
Confident.
At ease.
A great plumber doesn’t stop learning.
Rather, they just learn only what makes them a better plumber.
They don’t wake up thinking:
“Maybe I should add electrical work.”
Instead,they think:
“How do I diagnose faster? Fix cleaner? Prevent the next failure?”
That’s the difference.
Specialists don’t do less. They make less noise.
AI and automation makes it easier than ever to attempt everything.
However, it does not make it safer to be mediocre at many things.
The separation happening now isn’t about tools.
It’s about judgment.
Pattern recognition.
Depth earned over time.
The people who will pull away in 2026 aren’t adding more skills for the sake of relevance.
They’re doubling down on the thing that made them valuable in the first place and using technology to amplify that edge, not dilute it.
Generalists compete on price.
Specialists compete on trust.
And trust is the only currency that compounds.
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