Fractional CIO & Strategic Advisor | Helping Non-Technical Leaders Make Technical Decisions | Scaled Orgs from $0 to $3B+

Strategic IT Leadership for Growing Companies

Helping non-technical founders and small business leaders scale without getting slowed down by their own systems

The Problem
Most companies don’t fail because they dream too small.
They fail because their technology trips them up before they ever hit full speed.

Systems that don’t talk to each other

Vendors that overpromise and underdeliver

Teams that pull in different directions

Operational chaos hidden behind "we’ll fix it later"

Growth without fundamentals isn't a shortcut—it's a detour. Real business expansion is about building systems that scale with integrity, not just adding layers of complexity to a shaky core.

The Outcome
I help you build a stronger, smarter, simpler technology foundation — one that scales with your business, not against it.

✅ Faster operations
✅ Smarter use of tools and teams
✅ Fewer expensive mistakes
✅ A clear, flexible roadmap for growth
✅ More time spent leading — less time fighting fires

My Approach
I’m not here to sell you systems you don’t need or waste months writing strategy decks nobody reads.

I’m here to help you:

Fix what’s broken (before it costs you real money)

Align your people, process, and platforms (so they work together, not against each other)

Build momentum you can actually feel (and measure in real-world results)

I bring 30 years of hands-on experience building and scaling IT in organizations that grew from to over $3B — many times as the very first IT hire, often leading global distributed teams.

What you get is simple:
Real strategy. Real execution. Real growth.

No bloat. No buzzwords. No bureaucratic nonsense.

Services
Fractional CIO Leadership
Part-time executive leadership to align your tech and business strategy, manage vendors, and build internal capabilities without hiring a full-time CIO.

Project Rescue and Turnaround
When critical projects stall, I step in to realign teams, simplify the chaos, and deliver results.

Vendor and System Sourcing
Find the right systems and partners that fit your business — not someone else’s template.

Strategic IT Roadmapping
Clear, practical roadmaps that connect today’s actions to tomorrow’s growth.

Who I Work Best With
Founders and business leaders who:

Are serious about scaling

Know tech is crucial but don’t want to live inside it

Value momentum over perfection

Want a partner who talks business, not just tech

Ready to Clear the Bottlenecks and Build What's Next?
Let's start with a simple conversation.
No sales pitch. Just clarity on where you are — and what’s possible next.

Phillip R. Kennedy

The VP forwarded the CEO's angry email to the whole engineering team at 9:47 PM on a Thursday. 

Daniel's manager replied-all at 9:48: "I'll handle this. Everyone log off."

Twelve seconds. Two completely different leaders.

The CEO's email was four sentences. A client's integration broke during a routine deployment. The client called the CEO directly. The fourth sentence: "I need to understand who is responsible."

The VP read it and clicked Forward. Added the entire engineering distribution list. Twenty-three people. Two words at the top: "See below."

No context. No plan. Just a CEO's anger, amplified to two dozen engineers on a Thursday night, most of whom had nothing to do with the deployment.

Daniel was brushing his teeth when his phone buzzed. He'd been at the company four months. He'd worked on a small piece of the integration three weeks earlier. Close enough to wonder. Close enough to lose sleep.

His shoulders went up. He started mentally composing a defense for code he'd written at 2 PM on a random Tuesday.

Then his phone buzzed again. 9:48.

"I'll handle this. Everyone log off."

Seven words. No exclamation point. No performative urgency. Just: this is not your problem tonight. It's mine.

James fixed it by 11:30. Configuration issue. Not a code defect. Nobody on the team caused it.

The next morning, James emailed his team: "Issue resolved. Config problem. Nothing any of you shipped caused this. If last night's email stressed you out, that's worth a conversation. My door's open."

Daniel saved that message. Not because it was eloquent. Because it was the first time a manager acknowledged that an internal communication could cause harm, and took ownership of it.

The VP forwarded blame at the speed of a click. James absorbed it in twelve seconds.

Same crisis. Same night. Two completely different engineering cultures.

Your team already knows which one you are.

♻️ Repost if you've had a manager whose first instinct was to protect the team, not forward the pressure 

➕ Follow me (Phillip R. Kennedy) for more on engineering leadership that absorbs the hit instead of passing it down

I've spent 30 years watching what great technical leaders actually do.

Almost none of it looks like leadership on paper.

18 things I've seen the best ones do:

1. Say "I don't know" out loud so the team learns it's safe to say it too.

2. Kill a meeting to protect four hours of uninterrupted build time.

3. Put a junior engineer on the project everyone said she wasn't ready for. Then quietly clear the path.

4. Sit in the architecture review and ask the quiet person in the back what they think. Then actually wait for the answer.

5. Walk into a budget meeting and make technical debt visible to executives who only see features shipped.

6. Recognize the engineer who prevented the outage. Not just the one who fixed it.

7. Take the call from the angry stakeholder so the team can keep building.

8. Fight for an infrastructure investment that won't show results for six months. Then fight again when someone tries to cut it in Q3.

9. Tell their best engineer "you should interview for that role" before she'd ever considered leaving the team.

10. Share their own worst production mistake in a retro. Watch the room exhale.

11. Push for a promotion before the engineer asks. Then build the case so well it's undeniable.

12. Translate a forty-five minute technical explanation into two sentences a CFO can act on. Without losing what matters.

13. Block the fourth "urgent" request in two weeks. "Urgent" is not a strategy.

14. Pair a twenty-year veteran with a six-month hire. Tell both of them they're going to learn something.

15. Turn "this is broken" into "what would good look like?" Same facts. Completely different energy.

16. Advocate for sustainable pace when everyone above them is performing urgency.

17. Create space for exploration that might not ship anything. Then defend it when someone asks for the ROI.

18. Remember that the job was never to be the smartest person in the room. It was to make the room smarter.

None of this shows up on a dashboard. Most of it never gets recognized in a performance review.

But the engineers remember. And they become leaders who do the same things.

That's how you scale more than systems.

♻️ Repost if you've had a leader who did one of these and it changed your trajectory 

➕ Follow me (Phillip R. Kennedy) for more on technical leadership that builds people, not just products

He texted me eighteen months after leaving the company. 7:32 AM on a Tuesday. "Congrats on the promotion. You earned it."

He had zero organizational reason to care.

James had been my CTO for three years. Left to start his own company. Most former bosses disappear when the org chart changes. Within a month, the relationship becomes a LinkedIn connection you scroll past.

James never did that.

When I got stuck on an architecture decision after he'd gone, I almost didn't reach out. He replied in twenty minutes: "Coffee Thursday?" Asked three questions that reframed the problem. No lecture. No "remember who helped you" energy.

When a product manager kept changing requirements mid-sprint, James said something I still use: "Your job isn't to stop the changes. It's to make the cost visible to the people requesting them."

When I left for a startup, most of leadership went quiet. That silence tells you which relationships were real. James responded in an hour: "Exactly the right move. Need references?"

The promotion text came a year later. His own company, across the country. My career had zero impact on his.

I've had many managers. Most competent and forgettable. James is the only one whose influence outlasted his badge access.

He never managed from the org chart. The authority was incidental to the relationship. When the authority left, the relationship didn't.

Most leaders aren't this way. Not because they're bad people. Because organizations reward transactional leadership. When someone leaves, the incentive to stay connected disappears.

Leaders who stay were always outside that system. They invested in the person, not the role.

The test that matters more than any review: would people who used to work for you still take your call? Not because you can help them. Because it was never about that.

♻️ Repost if you've had a leader whose influence outlasted their title

➕ Follow me (Phillip R. Kennedy) for more on leadership that survives the org chart

She said she was "doing fine" and "learning a lot." Two weeks later she put in her notice.

I'd asked all the right questions. How are you settling in? Anything blocking you?

Surface-level questions get surface-level answers. And surface-level answers hide problems until they become resignation letters.

That exit taught me first 1:1s aren't introductions. They're the moment you earn honest communication or guarantee you'll never get it.

Most leaders fill that meeting with org charts and project updates. Nobody gets uncomfortable. Nobody learns anything.

After thirty years, here's what actually surfaces truth:

"Walk me through the last time you dug into someone else's code." Tells you more about team culture in three minutes than any survey. Listen for colleagues who help vs. territory that's guarded.

"What's the most frustrating part of getting your work done here?" Not "any concerns?" That gets "everything's great." Ask what frustrates them, then sit in the silence. The pause tells you whether honesty feels safe.

"When you disagree with a technical decision, how does that play out?" If the answer is "I don't usually disagree," that's not harmony. That's someone who learned speaking up costs more than staying quiet.

"If a friend asked whether they should join this team, what would you honestly tell them?" People rarely lie when it's framed as advice to someone they care about.

"How do you know when you've done good work here?" If they can't answer, your org hasn't made it clear.

You don't need ten questions. You need three honest ones and the discipline to stop talking after you ask them.

The engineers who answer carefully are often your best performers trying not to get fired for saying what's broken. The ones who say "everything's great" in week one say it again in their exit interview.

♻️ Repost if you've learned more from one honest answer than a dozen safe ones

➕ Follow me (Phillip R. Kennedy) for more on leading teams with better questions

He'd been the fastest developer on the team for nine years. Last quarter, a mid-level with half his experience outshipped him three to one.

She wasn't a better coder. She'd quietly changed what her job was.

Rachel started using AI agents the way a good manager uses a team: delegate predictable work, provide context, review output, redirect when something drifts. Agents handled integrations, test coverage, docs. She focused on architecture and judgment calls between what agents produced and what the system needed.

Still an IC on the org chart. Her daily work looked like management.

David coded line by line. Nine years of it. Genuinely good. He'd see no IDE on her screen and assume she was slacking.

Then sprint reviews told a different story.

Rachel shipped three features in a cycle where David closed four tickets. Not because she was smarter. Because she'd changed the ratio between thinking and typing.

His response is one I hear constantly: "That's not real engineering."

I get it. If you built craft through your hands for a decade, watching someone achieve more by orchestrating feels like a violation. Not just a career concern. An identity one.

But stripped of hype, here's what's happening.

The IC role is shifting from production to orchestration. From writing every line to directing, reviewing, and integrating work AI produces. The skills this demands aren't new. They're management skills. Providing context. Reviewing with judgment. Knowing when to intervene. Maintaining quality when production outpaces review.

Every engineer is becoming a manager. Not of people. Of systems that produce at a pace no human can.

The IC track isn't dying. It's evolving. More judgment. More context. Less typing. More thinking.

For engineers willing to make that shift, it's the best version of the job they've had.

♻️ Repost if your role is quietly shifting from building to orchestrating

➕ Follow me (Phillip R. Kennedy) for more on the real AI shift in technical work

She accepted an offer for 15% more. Her manager started a counteroffer. I told him to stop.

The money wasn't the problem. He just didn't know what the problem was.

Days before notice, her fix prevented a major outage. Week before, her refactoring cut response times in half. Her architecture decisions saved thousands in cloud costs monthly.

Her manager knew none of this. Not because he didn't care. Because he was a non-technical founder at a $12M company and nobody taught him what to look for.

He saw tickets closed. Features shipped. Through that lens, every engineer looked the same.

She didn't feel underpaid. She felt invisible.

This is the pattern I see most in growing companies. The founder is sharp. Competent in their domain. But they evaluate engineering like a restaurant kitchen: if food comes out, everything's fine.

The engineer preventing outages looks identical to one doing unremarkable work. Both close tickets. The difference is invisible unless you know what great engineering looks like.

That's not a character flaw. It's a knowledge gap. And it's expensive.

After she left, I told him: you don't need to understand code. You need three sentences.

"I heard your fix Tuesday prevented a customer issue. Tell me about it." Engineers know instantly if recognition is genuine. Specificity is the difference.

"What technical work happened this month I'd never see in a sprint review?" This teaches you what's invisible.

"What should I understand better about what engineering does?" Most leaders won't ask. Feels vulnerable. That's why it works.

The counteroffer would've cost $30K. She'd have stayed six months and left anyway. Her best work looked the same as average to the person signing her check.

Engineers don't leave for better offers. They leave when no one can tell the difference.

♻️ Repost if you've seen an engineer leave because leadership couldn't see it

➕ Follow me (Phillip R. Kennedy) for helping non-technical leaders keep great engineers

She stopped getting invited to strategy meetings in month four. By month eighteen, she'd stopped noticing.

That's the scary part.

Not the exclusion. The adaptation. Priya rebuilt their payment system from scratch. Designed architecture that scaled them from 200 to 2,000 concurrent users without adding. When their biggest client threatened to leave over reliability, her monitoring work saved the account.

The CEO texted the CTO about technical feasibility. Never Priya. The CFO questioned velocity at board meetings she wasn't in. Product roadmap happened Tuesdays. She found out Thursdays, after decisions were locked.

She wasn't failing. She was being compressed. Compression doesn't feel dramatic. You don't notice the ceiling dropping. You just start hunching.

By month twelve she'd stopped proposing improvements. By eighteen she was executing what others decided, calling it "being a team player," wondering why she was so tired.

I asked her when she'd last made a decision nobody above her rerouted. Too long before she answered.

Decades of this work. The pattern repeats. The CEO calls engineering "the IT group" at board meetings. Not just a wrong label. Labels shape budgets. Budgets shape headcount. Headcount shapes what Priya gets to build. When systems fail and the first question is "who did this" instead of "what happened," leaders absorb that. Stop taking risks. Stop volunteering hard truths. Shrink to fit.

She left. Smaller company. CEO with an engineering background. Six months later she told me: "I forgot what it felt like to have an idea and be allowed to finish the sentence."

She hadn't gotten smarter. She'd gotten room.

If something in your chest just tightened, pay attention to that. Not every struggle is a skills gap. Sometimes the ceiling is just low.

♻️ Repost if you've felt the difference between being grown and being compressed

➕ Follow me (Phillip R. Kennedy) for building environments where technical leaders thrive

They spent eight months building an AI recommendation engine. Beautiful machine learning. Garbage recommendations.

Their product catalog had 847 duplicate entries and descriptions from 2020.

The AI did exactly what it was designed to do. Found patterns and served them confidently. Customers got recommended discontinued products, duplicates of things in their cart, accessories for items no longer sold. Confident wrong answers at machine speed.

This company isn't unusual. They're the norm.

The pattern is becoming too common. The CEO hears AI is table stakes. The board wants a strategy. So leadership announces an initiative while their systems run on spreadsheets, manual uploads, and that one person who reconciles the data every Friday.

Customer records in seventeen tools. Support tickets referencing orders that don't exist in the main database. Three definitions of "active customer" depending on which dashboard you open.

Then they layer AI on top and wonder why it doesn't work.

AI doesn't fix broken systems. It scales them. Wrong answers with perfect grammar. Three versions of truth delivered faster than ever.

The most effective AI deployment I saw last year was boring. Nine months of cleanup before writing a single prompt. Data consolidated. Duplicates resolved. Systems connected. One source of truth.

No press release. When they turned on AI, it just worked. Not because the technology was special. Because it had something sane to work with.

Before you spend another dollar on AI: would a new employee be confused by your current systems? If yes, so will the AI. Just faster and more expensively.

The companies quietly winning aren't the ones with the biggest AI budgets. They're the ones who did the boring work first.

♻️ Repost if you've watched AI get layered on a foundation that couldn't support a spreadsheet

➕ Follow me (Phillip R. Kennedy) for technology decisions that actually work

He told the CEO he was 60% sure. The CEO said, "That's 20% more than I had when I started this company. Go."

Daniel had been circling a platform decision for three weeks. Two viable paths. Trade-offs he could model, risks he couldn't. The data said "maybe" in fourteen different ways.

He kept requesting more analysis. Another benchmark. One more comparison. His director finally said, "You're not gathering information. You're avoiding a decision."

She was right.

Daniel could architect systems most people couldn't diagram on a whiteboard. The problem was never capability.

He'd confused certainty with competence.

He believed good leaders decide because they know the answer. So when he didn't know, he assumed he wasn't ready. More data. More time. The team stalled.

The CEO's response broke something open. Every founder who's built something real knows certainty almost never arrives on time.

Daniel made the call Thursday. "Here's what we're doing, here's why, and here's what I'm not sure about. We'll learn the rest by building."

Six months later, two of his assumptions were wrong. The team had adapted. What he'd agonized over mattered less than the momentum of actually moving.

This pattern lives everywhere. The leader who won't commit until every variable is known. The founder polishing the deck instead of making the call. The executive requesting another quarter of data before approving a hire they know they need.

It looks like diligence. Past a certain point, it's avoidance in a professional costume.

Courage doesn't follow confidence. It's the other way around.

Daniel told me a year later: "I used to think my job was to have the answer. Now I think it's to make the call and help the team navigate what we find on the other side."

That's not a technology insight. That's a leadership one.

♻️ Repost if you've made the right call on incomplete data and didn't know it until later 

➕ Follow me (Phillip R. Kennedy) for more on leading through uncertainty

They hit every sprint target for eleven months. Green across every dashboard. The board loved them.

Their production system was rotting from the inside.
I got called after the third senior engineer left in six weeks. The CEO was baffled. "Velocity is up. Deployment frequency is the highest it's been. Why are they leaving?"

I spent a week with the team before opening a dashboard.

Engineers had learned to game every metric leadership tracked. Points inflated. Deployments split into smaller chunks. Tickets closed at "good enough."

The burndown charts were beautiful. The codebase was held together with workarounds nobody touched.

Nobody had raised it. The one engineer who tried, eight months earlier, got told metrics showed everything was fine. Last time anyone spoke up.

The moment I knew the team was in trouble wasn't in a report. It was in planning. A junior engineer pushed back on a timeline. Got two sentences in. The room went still. Not respect. Warning. She stopped. "Never mind, we can make it work."

On a healthy team, that sentence never gets cut short.

The signs that matter have nothing to do with velocity. When something breaks, does the team ask "what failed" or "who failed?" When someone says a deadline is unrealistic, does the room listen or reroute? Does the team celebrate three weeks of database work nobody outside engineering will notice?

These behaviors don't fit in Jira. They're the difference between a team that ships metrics and one that builds systems you can bet a company on.

His best engineers hadn't left for comp. They left because they'd been saying the system was fragile, leadership pointed at green dashboards, and they decided to let the next team deal with it.

Prevention never shows up on a dashboard. But it's the reason you still have a business.

♻️ Repost if you've seen the gap between what metrics show and what's really happening

➕ Follow me (Phillip R. Kennedy) for seeing what dashboards miss in engineering teams

I watched him delete a Slack message. He'd started typing a direct answer to an engineer's architecture question, stopped, and forwarded it to his direct report instead.

He'd been VP for eleven days.

James had been a director for three years. Engineers loved working for him. Answered questions directly. Showed up in code reviews to learn. Knew the last five production incidents by heart.

Eleven days in, something shifted. A quiet recalibration of who he thought he was supposed to be.

Stopped joining sprint demos. Replaced architecture chats with "strategy alignment" meetings. When engineers pinged him, he forwarded the message.

He wasn't arrogant. He was doing what he thought VPs do. Every VP he'd watched kept distance. Details were for directors.

The system was turning a connected leader into an abstraction.

I'd seen it dozens of times. The title lands and the operating system changes. Not because the person changed. Because the calendar fills differently. Information arrives filtered. You stop hearing what engineers think and start hearing what managers think engineers think.

Three months in, his team didn't recognize him. Engineers routed through his chief of staff. The architect who used to argue with him had stopped, because James was no longer in the room where those arguments happened.

I told him: "You used to spot the caching problem before anyone filed a ticket. Now you find out in a weekly summary. That gap is where your judgment lived."

He made a few changes. Kept one architecture session weekly. Not to decide. To listen. Stayed in sprint demos for his most critical product. When engineers pinged him, he answered directly.

Small things. But the team noticed immediately: proximity isn't beneath me.

The title doesn't have to change you. But it will, unless you choose which connections to protect.

♻️ Repost if you've watched a promotion quietly rewire someone

➕ Follow me (Phillip R. Kennedy) for leadership that stays connected to the work

The CTO told me he'd spent his weekend studying AI augmented development. His background was finance. His best engineers were leaving. He thought the two problems were connected.

They weren't.

Daniel had been CTO for eighteen months. Smart. Great with numbers, strategy, board communication. Zero engineering experience. He assumed credibility meant closing the gap. So he studied. Tutorials. Whitepapers. Architecture reviews full of detailed implementation questions.

His engineers didn't see a leader learning. They saw a bottleneck forming.

Every decision became a research project. Three-week sprints stretched to six because nothing moved until he felt informed enough to approve. He thought he was being thorough. His team experienced it as distrust.

The senior engineer who left first told me: "I don't need my CTO to understand AI development. I need him to trust that I do and make the call."

That's the gap. Not technical knowledge. Decision-making confidence. Daniel didn't need to understand how to setup OpenClaw. He needed to recognize his senior architect had been right about the last four calls and earned trust to make the fifth without a two-week wait.

The hardest part of leading technical teams without a technical background isn't the knowledge gap. It's saying "I don't fully understand this, I trust your judgment, here's my decision." That terrifies most non-technical leaders. It's also what stops your best people from updating their LinkedIn profiles.

We worked on this together. He stopped studying how to technically implement AI. Started making faster calls based on who recommended them and what they optimized for. Approval cycles shortened. His team stopped leaving.

He told me: "They didn't need a better engineer. They needed faster decisions."

His engineers could have told him that on day one.

♻️ Repost if you've learned that leading technical teams is about decisions, not expertise

➕ Follow me (Phillip R. Kennedy) for more on leading technical teams with confidence, not code

His hands were shaking over the keyboard. He'd deployed the change that took checkout offline. Everyone in the room knew it.

Revenue stopped. Tickets stacking. VP of Sales pinging me for an ETA I didn't have.

The room wanted someone to bark orders. Demand root cause. Point at the deployment log.

I sat down next to him. "How many customers are affected right now?"

Not "what happened." Not "whose change."

He stopped staring at the error logs. Pulled up monitoring. "About 1,200 in checkout. Another 300 getting timeouts on product pages."

"Good. Checkout first. Walk me through the rollback."

His hands stopped shaking by the third sentence.

A leader's emotional state during an incident becomes the team's operating environment. Instantly. Walk in radiating urgency and everyone matches it. They talk over each other, chase parallel theories, make decisions that feel productive and create more problems.

Walk in calm and something shifts. The engineer who caused the outage stops bracing for blame and starts working the problem.

The fix took ninety minutes. He found it himself. A config flag that behaved differently in production than staging. After systems were restored, I told the team to go home. Handled the sales update myself. Scheduled the postmortem for two days later, because running a blameless retro on no sleep is how you get a blame-filled one.

Two days later, he proposed the fix: automated config comparison between staging and production. Nobody asked him. He volunteered because the incident room had been safe enough that owning it didn't feel like a career risk.

A year later he led our incident response. Calm. Methodical. Sat next to the person panicking instead of standing over them.

He learned that from a Tuesday afternoon when his hands were shaking and nobody blamed him for it.

♻️ Repost if you've seen calm leadership change the outcome of a crisis

➕ Follow me (Phillip R. Kennedy) for more on leading technical teams through hard moments

We've all made the "perfect résumé" hire. Strong credentials. Nailed the technical interview. Three months in, you realize they can solve any problem except the ones that actually matter.

I've hired hundreds of people over thirty years. The pattern that predicts success has almost nothing to do with algorithms or credentials.

It's curiosity. How someone behaves when they hit a problem they don't know how to solve.

One of my best hires had two years of experience and a community college degree. Struggled in the technical round. But when conversation shifted to a real problem we were facing, he asked diagnostic questions that showed he'd operated systems under real pressure. Not textbook answers. Thinking from the weeds.

A year later, three teams called him first when something broke. Not the fastest coder. The one people trusted to think before acting.

What I've learned about what actually predicts success:

Give candidates a real problem, not a puzzle. Walk them through a challenge your team faces. Twenty minutes of real conversation beats an hour of whiteboard performance.

Watch what happens when they don't know. The best say "I haven't seen this, but here's how I'd start." People who bluff in interviews bluff on your team.

Listen to what they ask about. The system, the users, the team? Or just the stack, the title, the comp?

Look for ownership instinct. Ask about a project that went sideways. People worth hiring talk about what they learned. Not who was at fault.

Create unstructured time. Thirty open minutes surface what no template will.

You can teach your tech stack in months. You can't teach someone to care about the problem behind the ticket.

The résumé says where someone's been. The conversation tells you who they are. Most hiring processes only measure the first.

♻️ Repost if your best hire looked nothing like you expected on paper

➕ Follow me (Phillip R. Kennedy) for more on building teams that scale on trust

Career advice nobody's giving: Quit. Stack Mac Minis. Subscribe to every AI model and claw bot. Emerge in 90 days as something the market doesn't have a job title for yet.

J.D. Meier

Microsoft 25 years | Leading Innovation for a Sustainable Future | Leadership | Strategy | Transformation | Sustainability | Program Management | Former Head Innovation Coach for Satya Nadella

AI changed the leadership game.

I help leaders close the AI Leadership Gap.

Become the leader others can’t ignore.

—

THE AI LEADERSHIP GAP

Most leaders added tools.
Few upgraded their leadership.

That gap is widening — fast.

—

3 WAYS I HELP YOU WIN YOUR FUTURE

1. LEADERS IN TRANSITION
New boss, new org, new role, new arena. You need clarity, confidence, and an edge. Fast.

2. LEADERS WHO WANT TO INNOVATE
You own innovation, transformation, or future growth. You need systems that turn ideas into breakthroughs that ship.

3. LEADERS WHO WANT TO BE THEIR BEST
You want to lead like the top 1%. You want the mindsets, skillsets, and toolsets to operate at your highest level for sustained excellence.

—

WHY LEADERS TRUST ME

For 25 years at Microsoft, I turned ideas into breakthroughs.

As Satya Nadella's Head Innovation Coach, I built frameworks that scaled innovation and value creation across industries. 

I've trained 10,000+ leaders, from Fortune 100 executives to fast-moving teams, and I'm the bestselling author of Getting Results the Agile Way.

—

CORE CAPABILITIES
AI
Disruptive Technologies 
Strategy
Leadership 
Innovation 
High Performance
High Performance Teams
Leading Change
Scaling Impact 
Digital Transformation


Director of Innovation & Sustainability, Industry Solutions

★ Spearheaded the end-to-end development and implementation (from program design to enablement and launch) of the go-to-market strategy for sustainability among Industry Solutions field sales personnel. 

★ Collaborated with worldwide sustainability teams to define and execute go-to-market initiatives across a portfolio of targeted accounts while maintaining a focus on readiness, enablement, and activation in the field. 

★ Established and grew a Sustainability Swarm Team with 200+ members to share sustainability knowledge and swarm on customer engagements. 

★ Served as a “super connector” building relationships between field personnel and experts to provide assets, guidance, and support to field staff for customer engagements.

★ Created a Sustainability Show to share real-world lessons learned from engagements, for practitioners, by practitioners.

★ Coached Digital Advisors and Industry Digital Strategists on innovation management, as well as the innovation mindset, skillset, and toolset.

★ Envisioned and coached the process, model, and approach for a global and scalable innovation capability that produced 957% return on the initial investment of $2.47M.

How does strategy change with AI?
 
It doesn’t.
 
And it does.
 
Rich Rumelt says bad strategy hides behind ambition.
 
“Like a quarterback whose only advice to teammates is ‘Let’s win,’ bad strategy covers up its failure to guide by embracing the language of broad goals, ambition, vision, and values.”
 
Good strategy, he says, has:
 
1. A diagnosis
2. A guiding policy
3. A set of coherent actions
 
Roger Martin simplifies it even further:
 
Strategy is choosing where to play and how to win.
 
Both are right.
 
Strategy is choice under constraint.
 
So what does AI actually change?
 
It changes the constraint.
 
It expands the opportunity landscape.  
It alters the economics of intelligence.  
It makes certain positions newly viable.  
It makes others obsolete.
 
You still need a diagnosis.  
You still need trade-offs.  
You still need coherent action.
 
But the frontier of what is possible just moved.
 
That’s the shift.
 
The leaders who win in the AI era won’t abandon strategy.
 
They’ll redesign it around a new constraint.

Has AI changed your positioning, or just your productivity?

10X Your Leadership Impact | Satya Nadella’s Former Head Innovation Coach | AI Strategy & Transformation | Executive Leadership Coach | 25 Years of Microsoft

How AI Bends the Rule of Strategy

At Microsoft, I was known for intellectual horsepower.
 
That’s not a small compliment:
 
Microsoft is a competitive world of high performers.
 
If you can’t think sharply, you don’t last.
 
Early on, I realized something:
 
Raw intelligence isn’t enough.
 
You can be smart. And still miss the point.  
You can be brilliant. And still have blind spots.  
You can win arguments. And still make bad decisions.
 
If I wanted to stay in the game, I had to upgrade how I think.
 
So I became obsessed with thinking itself.
 
I studied:
• Edward de Bono and lateral thinking  
• Disney Imagineers and creative tension  
• Design Thinking and empathy-first framing  
• Lawyers and argumentation maps  
• Decision science and cognitive bias  
• Systems thinking and information modeling
 
I didn’t just read.
 
I battle-tested frameworks against hard platform problems.  
Industry transformations.  
High-stakes decisions.  
Competing visions of the future.
 
It was my “overnight success”:
Thousands of books.  
Brilliant mentors.  
Years of applying models under pressure.  
Filing 9 patents in 6 months before I ran out of patent budget.
 
One of my managers once told me:
“You look left, right, up, down, further than anyone I know.”
 
That stuck with me.
 
Because that’s the real skill.
Not being right.
Seeing more.
 
Most bad decisions don’t come from low intelligence.
 
They come from narrow perspective.
 
We overuse 2–3 ways of thinking.  
We avoid the uncomfortable lenses.  
We rationalize our emotions.  
We default to critique without balancing possibility.
 
In the age of intelligence, where everyone has access to powerful tools and information, the advantage shifts.
 
It’s no longer about who knows more.
 
It’s about who can see more.
 
If you can think better, you can decide better.  
If you decide better, you execute better.  
If you execute better, you win more often.
 
That’s why I created Think360.
 
A simple 8-lens system to:
• Surface blind spots  
• Balance critique with possibility  
• Bring feelings into the open instead of rationalizing them  
• Expand cognitive range before commitment
 
It’s not about using every lens every time.
 
It’s about noticing where you tend to lean.  
And expanding into the gap.
 
Intelligence without perspective creates dangerous blind spots.
 
Perspective is power.
 
That’s Think360.

Which lens do you overuse, and which one do you avoid?

You're adding AI to your business.

But can you see how it all connects?

Most leaders can't.
They're deep in the pieces: a pilot here, a tool there, without the full picture.

When I was leading digital transformation efforts at Microsoft, one of my favorite tools was the Strategy Wheel by Cynthia Montgomery.

It helped me see the whole system of a business.
Kind of like seeing the cover of a puzzle box.

So much of transformation is putting a puzzle together.
And it's easy to get lost in the pieces.

The Strategy Wheel made it easy to zoom in and out, from the big picture to any single function and back.

So I created the AI Strategy Wheel to help leaders see what AI augmentation looks like across their entire organization.

Driving digital transformation got a lot easier once I could actually see it.

Here's how it works.

At the center of the AI Strategy Wheel is your purpose.
Along with the competitive advantage you're building toward.

Around it sit 8 business functions:
Design. Products. 
Marketing & Service. 
Sales & Distribution. 
Human Resources. 
Operations. 
Finance. 
Info Systems.

Each one is a potential value multiplier with AI.

Not a place to "add a chatbot".  
A place to fundamentally rethink how value gets created.

The power isn't in any single function.
It's in how they connect.

When your AI-augmented demand forecasting in Products feeds your supply chain in Operations, which feeds your dynamic pricing in Finance, that's a system, not a feature.

That's where exponential value comes from.

One leader I worked with was stuck in pilot mode:
AI experiments scattered across the org, no coherent picture.

When we mapped everything onto the Strategy Wheel, she saw it immediately.
Sales and Marketing were getting all the AI investment.  
That's where 70% of the budget was going.

Meanwhile, Operations, Finance, and HR were practically untouched.

And the biggest bottleneck wasn't technology.
It was the gap between functions that weren't connected. 
AI-powered demand signals in Marketing that never reached Supply Chain. 
Customer insights that never made it to Product.

She wasn't missing AI tools. She was missing the system.

Within weeks, her team shifted from "where should we add AI next?" to "how do we connect what we already have?"

That's the shift.

From AI as a tool → to AI as a system.
From adding intelligence → to leading with it.

I built the AI Strategy Wheel so you can see it too.

↓ Grab the framework below.

AI Strategy Wheel 3

I've been thinking about what actually changes when a leader gets good at AI.
 
It's not the tools. It's not the prompts. 

It's not even the strategy.
 
It's how they think.
 
I keep seeing the same 7 attributes show up in the leaders who are making the biggest moves.
 
𝗙𝘂𝘁𝘂𝗿𝗲-𝗕𝗮𝗰𝗸 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝘀𝘁 — They start from the future and reverse-engineer the path back. Not "what's next" but "what must be true in 1 year, and what do we do now?"
 
𝟭𝟬𝗫 𝗟𝗲𝘃𝗲𝗿𝗮𝗴𝗲 𝗟𝗲𝗮𝗱𝗲𝗿 — They have a nose for where small moves create disproportionate results. They're not working harder, they're finding the hidden 10X play.
 
𝗣𝗮𝘁𝘁𝗲𝗿𝗻 𝗛𝘂𝗻𝘁𝗲𝗿 — AI gives you superhuman pattern recognition, but only if you're actively hunting. These leaders connect weak signals before anyone else sees the picture.
 
𝗝𝘂𝗱𝗴𝗺𝗲𝗻𝘁 𝗔𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗿 — They use AI to think better, not to stop thinking. That distinction matters more than any tool.
 
𝗛𝘂𝗺𝗮𝗻 𝗠𝘂𝗹𝘁𝗶𝗽𝗹𝗶𝗲𝗿 — They use AI to make their people extraordinary. Not to replace them. To amplify what they're already great at.
 
𝗢𝘂𝘁𝗰𝗼𝗺𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 — They design outcomes instead of managing activities. Different game entirely.
 
𝗦𝗶𝗴𝗻𝗮𝗹-𝘁𝗼-𝗔𝗰𝘁𝗶𝗼𝗻 𝗟𝗲𝗮𝗱𝗲𝗿 — They collapse the gap between knowing and doing. No analysis paralysis, no shooting from the hip. Signal, decision, action.
 
What I find interesting is that most executives I work with are strong in 2-3 of these and not so much with the rest.
 
Which one came easiest to you, and which one made you uncomfortable?

How to identify transformation opportunities with AI?

You need a map:

Without a shared map, it's hard to know where to actually invest with AI.

This is true for any disruptive technology.

I learned this at Microsoft when we were trying to figure out how to leverage a disruptive technology.  We needed a wide angle lens on where and how the technology would augment the business.

We assembled 5 leaders in a room.
The problem was we had no idea where to start.

I suggested we pull up a Business Capability Map so we could all "see" the business.
We could both scan across the capabilities or drill into a category.

As we walked the map, we asked simple questions:

• 𝘏𝘰𝘸 𝘮𝘪𝘨𝘩𝘵 𝘈𝘐 𝘤𝘩𝘢𝘯𝘨𝘦 𝘩𝘰𝘸 𝘸𝘦 𝘥𝘦𝘵𝘦𝘤𝘵 𝘴𝘩𝘪𝘧𝘵𝘴 𝘪𝘯 𝘥𝘦𝘮𝘢𝘯𝘥?
• 𝘏𝘰𝘸 𝘮𝘪𝘨𝘩𝘵 𝘈𝘐 𝘤𝘩𝘢𝘯𝘨𝘦 𝘩𝘰𝘸 𝘸𝘦 𝘱𝘳𝘪𝘰𝘳𝘪𝘵𝘪𝘻𝘦 𝘢𝘯𝘥 𝘢𝘭𝘭𝘰𝘤𝘢𝘵𝘦 𝘴𝘱𝘦𝘯𝘥?
• 𝘏𝘰𝘸 𝘮𝘪𝘨𝘩𝘵 𝘈𝘐 𝘤𝘩𝘢𝘯𝘨𝘦 𝘩𝘰𝘸 𝘸𝘦 𝘳𝘦𝘵𝘢𝘪𝘯 𝘢𝘯𝘥 𝘨𝘳𝘰𝘸 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴?

As you can imagine, this simple process gets leaders in the game.
Suddenly, people start sharing stories of possibility.

Depending on how mature your business is, you might just start with a simple value chain.

But when you create a Business Capability Map, you have one of the best lenses on your business.

It also makes it much easier to find hidden opportunities.

If you never mapped out a business visually before, it's your game changer.

taplio

The Battle

Phillip R. Kennedy

J.D. Meier

Followers

Posts

Engagements

Likes

Performance ScorePhillip R. Kennedy's LinkedIn Performance

Performance ScoreJ.D. Meier's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Phillip R. Kennedy

J.D. Meier

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Phillip R. Kennedy's LinkedIn Performance

Performance ScoreJ.D. Meier's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScorePhillip R. Kennedy's LinkedIn Performance