Product @ LinkedIn | Author of “Reimagined: Building Products with Generative AI” | “PM Learning Series” Host | Sharing insights about building products and leading innovative teams

👋 Hello! I’m Shyvee—a forward-thinking product lead who combines creativity, human psychology, and AI to build thriving communities and drive impactful product growth.

Previously a Product Lead at LinkedIn and instructor with LinkedIn Learning, I now focus on driving product growth and adoption while activating professional communities on Microsoft Teams, empowering people to connect, collaborate, and future-proof their careers. With a unique passion for community-building and hands-on AI learning, I’ve created a global, multi-disciplinary community that supports individuals while fueling product adoption and growth along the way. Learn more: https://AICommunityLearningProgram.substack.com/about

Throughout my career, I’ve engaged over 100K followers, reaching 40M+ views. My PM Learning Series has featured esteemed guests, including cofounders and CPOs from leading Silicon Valley startups. As President of the Kellogg Alumni Club in San Francisco, I’m a frequent speaker and have influenced digital strategies at organizations like VMware, Disney, Cisco, YMCA, Toyota, HSBC, Telstra, and other Fortune 1000 companies.

My superpowers lie in strategic thinking, innovative problem-solving, and data-driven storytelling, all grounded in a deep understanding of user psychology and enhanced by AI. I leverage AI for rapid prototyping, automating go-to-market workflows, and building high-impact solutions that resonate with users and drive real business outcomes.

I’m also the coauthor of the Amazon bestseller Reimagined: Building Products with Generative AI, a practical guide for integrating AI into product strategy, featuring over 150 examples and 30 case studies. Learn more: https://a.co/d/btmnJfu

Shyvee Shi

If you own €10M+ DTC and migration, ROAS, stack, or AI decisions keep turning into debates, you’re carrying the execution risk.

Most ecommerce directors and CDOs aren’t short on ideas.
They’re short on a shared, evidence-backed picture of what’s actually happening across vendors, platforms, and dependencies.

In complex organisations, the problem isn’t effort.
It’s missing sequence, unclear ownership, and decisions that can’t be defended when things fail.

I’ve done this in fashion and lifestyle environments with brands like Vans, The North Face, Timberland, and Dickies.
Including situations where DTC went from ~€1M to €10–20M over a couple of years by tightening execution, not “rebranding the business”.

The same pattern shows up in €100M+ organisations, just at a larger scale.

How I work:

• Map reality vs perception (KPIs, dependencies, failure points)

• Clarify who does what (in-house, agency, SI) and where accountability breaks

• Prioritise execution — what’s ready now vs what needs foundations first

If you’re leading digital operations and trying to align stakeholders while stopping budget blowouts,
DM me “RISK”.

Marco Lanzi

𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗶𝗻 €𝟭𝟬𝗠+ 𝗗𝗧𝗖:

How many AI tools got added to your stack in the last 12 months?

Now, how many times have you heard this in a meeting:

"Wait… which tool was supposed to handle that?"

Yeah. That’s the problem.

I’m speaking at The Retail Bulletin Ecomm North (Feb 4, Manchester) about execution risk in the AI era, and I keep seeing the same pattern across fashion, lifestyle, and DTC brands:

Phase 1: “We need AI to stay competitive”

Phase 2: “Which AI tools should we buy?”

Phase 3: “Who’s actually responsible when this doesn’t integrate?”

Phase 4: “Why are we still debating this 6 months later?”

The companies avoiding this trap don’t have fewer AI tools.

𝗧𝗵𝗲𝘆 𝗺𝗮𝗽𝗽𝗲𝗱 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗿𝗶𝘀𝗸 𝗯𝗲𝗳𝗼𝗿𝗲 𝗮𝗱𝗱𝗶𝗻𝗴 𝗻𝗲𝘄 𝘃𝗲𝗻𝗱𝗼𝗿𝘀.

They know:
→ Where the stack already overlaps
→ Which dependencies break under load
→ Who owns the outcome when AI gets it wrong
→ How to defend decisions when finance asks for ROI

𝗧𝗵𝗶𝘀 𝗶𝘀 𝘄𝗵𝘆 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗲𝘃𝗲𝗿.

Not to hear vendor pitches.
But to hear operators say: “Here’s where execution actually broke for us.”

Two asks:
• If you’re at Retail Ecom North →  come find me
• If AI has created execution debates in your org → drop the situation below

Let’s map the patterns together.

CDO / Head of Digital in €10M+ DTC → avoid execution mistakes and tech overlaps before they slow you down

"We need to move fast on AI."

I heard this six times last month from different digital leaders.
Then I asked:

"Which AI use case are you implementing?"
Silence.

The problem was never:
"Are we innovative enough?"

The real question was always:
"How do we know this works, before we bet the budget, credibility, and roadmap on it?"

Because in reality:

 • Every agency shows same three logos
 • Every vendor claims their platform scales
 • Every AI demo looks perfect, in a sandbox

Then execution starts.
𝗔𝗻𝗱 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗵𝗶𝘁𝘀:

 • Legacy systems don't integrate
 • Your Legal has 47 questions
 • Data isn't clean enough
 • Teams aren't trained
 • Timelines slip 

And you're the one holding accountability.

𝗔𝗜 𝗱𝗶𝗱𝗻'𝘁 𝗯𝗿𝗲𝗮𝗸 𝗿𝗲𝘁𝗮𝗶𝗹.
𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗱𝗶𝗱.

You don't need more tools.

You need decision confidence inside complexity:

 • Which platform scales beyond the POC?
 • Which partner has delivered this at your scale?
 • Which AI use case survives governance, budget reality, and real data?


𝗧𝗵𝗲 𝗻𝗲𝘄 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗶𝘀𝗻'𝘁 𝘀𝗽𝗲𝗲𝗱.
𝗜𝘁'𝘀 𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆.

Before starting your next initiative, ask:

 1. Who has done this at our scale, and failed?

 2. What dependencies aren't being discussed yet?

 3. What does success look like six months in, not in the demo?


If you can't answer these, you don't have a plan.
𝗬𝗼𝘂 𝗵𝗮𝘃𝗲 𝗵𝗼𝗽𝗲.

PS
For digital leaders accountable for outcomes, not slides.
What's the last project you wish you had validated better before committing?

"Maybe this is just how it is."

That's what a Head of Digital told me after their third failed platform migration.

€180K over budget.
Eight months delayed.
Same vendor they already knew would underdeliver.

Here's what actually drives me crazy:

She saw it coming.

She documented every dependency.
Six months before the deadline, she flagged the risks.
She explained, clearly, why this vendor wasn't built for their scale.

Management went ahead anyway.

Why?

"We don't have time or data to find someone else."
"The vendor seems confident."
"Let's give them a chance."

Three meetings. Zero action.

Then when it collapsed?

"Why didn't you flag this earlier?"

This is the hidden tax of being an accountable digital executive.

Your expertise is trusted, but not acted on.
Your judgment is right, but not validated.
Your reality is accurate, but not shared.

So you spend more time defending decisions than executing them.

If you're constantly fighting uphill battles just to get the basics right, you're missing one thing:

Independent credibility for internal decisions.

Not a consultant who bills €50K and disappears.
Not a yes-person who rubber stamps whatever leadership wants.

But a thinking partner who
- Challenges your assumptions
- Strengthens your conclusions
- Turns intuition into defensible evidence

For digital leaders drowning in justification instead of execution, what's the one thing you wish your stakeholders understood without you having to explain it again?

The board meeting started with a slide I’ll never forget:

“Our competitor just launched same-day delivery.
We’re still on a 3-week release cycle.
What’s our response?”

I had good answers:
	•	“We’re in the middle of a platform migration.”
	•	“The roadmap delivers this in Q3.”

The CEO cut me off.

“Our competitor doesn’t care about our roadmap.
Neither do our customers.
Why should we invest another €2M when we’re already behind?”

𝗧𝗵𝗮𝘁’𝘀 𝘄𝗵𝗲𝗻 𝗶𝘁 𝗰𝗹𝗶𝗰𝗸𝗲𝗱.

You don’t win budget battles with plans.
You win them with proof of velocity.

Here’s the shift I made.

𝗕𝗲𝗳𝗼𝗿𝗲:
“We need €2M to finish the migration so we can start innovating.”

𝗔𝗳𝘁𝗲𝗿:
“Here’s the innovation gap costing us €400k per month.
Here’s how €2M closes that gap in 90 days, 
with measurable milestones every two weeks.”

The difference was simple:

→ I stopped defending sunk costs
→ 𝗜 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝘆𝗶𝗻𝗴 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗰𝗼𝘀𝘁

⸻

The framework that saved my budget

𝟭. 𝗠𝗮𝗽 𝘁𝗵𝗲 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗳𝗶𝗰𝗶𝘁 (𝗮𝗻𝗱 𝗰𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲 𝘁𝗵𝗲 𝗰𝗼𝘀𝘁)
List the capabilities competitors have that you don’t.
Assign revenue impact.
Prioritize ruthlessly.

𝟮. 𝗖𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗲 𝗩𝗲𝗹𝗼𝗰𝗶𝘁𝘆 𝗥𝗢𝗜
Don’t ask for money to “finish the migration.”
Ask for money to “ship capability X in 6 weeks instead of 6 months.”

𝟯. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝟮-𝗪𝗲𝗲𝗸 𝗣𝗿𝗼𝗼𝗳 𝗖𝘆𝗰𝗹𝗲
Ship fast.
Show momentum early.
Make progress visible before asking for more budget.

⸻

The truth:

CFOs don’t fund transformations anymore.
𝗧𝗵𝗲𝘆 𝗳𝘂𝗻𝗱 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲𝘀 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗽𝗿𝗼𝘃𝗲.

So ask yourself:

When your competitor launches the feature your customers want, 
will you have data that justifies fighting back?

Or a roadmap that explains why you can’t?

Agentic AI won’t replace you.
It will expose you.

And that’s not a threat.
It’s a mirror.

I spent years leading digital transformations.
Watched smart, capable leaders make decisions based on:
	•	“Industry best practice”
	•	“We’ll figure it out”
	•	Vendor confidence

Myself included.

Sometimes it worked.
Sometimes we got lucky.
Sometimes complexity gave us cover.

𝗕𝘂𝘁 𝗵𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗜 𝗿𝗲𝗮𝗹𝗶𝘀𝗲𝗱:
Agentic AI removes the cover.
	•	It doesn’t give you six months to course-correct
	•	It doesn’t let complexity hide weak decisions
	•	It doesn’t allow quiet pivots when vendors underdeliver

𝗜𝘁 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲𝘀 𝗰𝗼𝗻𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲𝘀.

As an accountable executive, you already know:
	•	Tools don’t fail, decisions do
	•	AI just makes bad ones visible faster
	•	You can’t explain your way out at AI speed

What used to fail slowly
𝗻𝗼𝘄 𝗳𝗮𝗶𝗹𝘀 𝗶𝗻 𝗿𝗲𝗮𝗹 𝘁𝗶𝗺𝗲.

The vendor that would quietly miss deadlines?
Exposed immediately.

The platform that “seemed to scale”?
Breaks visibly. Publicly. Fast.

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝘄𝗼𝗻’𝘁 𝗿𝗲𝗺𝗼𝘃𝗲 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆.
𝗜𝘁 𝘄𝗶𝗹𝗹 𝘀𝘂𝗿𝗳𝗮𝗰𝗲 𝘄𝗲𝗮𝗸 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗲𝗮𝗿𝗹𝗶𝗲𝗿.

The winners won’t be those with the most AI.
They’ll be the ones who can answer before execution:
	•	What breaks first, and when?
	•	Why this decision, based on evidence?
	•	Who has done this before, and what actually happened?

Because when AI accelerates your timeline,
you can’t afford to be wrong.

PS.
That realization hit me hard in my last role, and changed what I chose to build next.
Accountability is the scarcest skill in digital leadership.

What’s the one decision you’re making right now that you’d want to defend with evidence, not hope?

I stopped chasing "𝗯𝗲𝘀𝘁-𝗶𝗻-𝗰𝗹𝗮𝘀𝘀" vendors.

Here's why:
"𝗕𝗲𝘀𝘁-𝗶𝗻-𝗰𝗹𝗮𝘀𝘀" 𝗶𝘀 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝗽𝗵𝗿𝗮𝘀𝗲 𝗶𝗻 𝗿𝗲𝘁𝗮𝗶𝗹.

Every pitch sounds the same:

• "We work with [big logo]"
• "Best-in-class AI"
• "Proven ROI"

Then you sign.
𝗔𝗻𝗱 𝗿𝗲𝗮𝗹𝗶𝘁𝘆 𝗵𝗶𝘁𝘀:

• Their Fortune 500 client? Different stack. Different scale. Different problems.
• Their "proven results"? Not in your category. Not with your constraints.
• Their "best-in-class" solution? Breaks when it meets your legacy systems.

€200K later, you're explaining to the board why the project is six months behind.

I've been there.
More than once.

𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗳𝗶𝗻𝗮𝗹𝗹𝘆 𝗰𝗹𝗶𝗰𝗸𝗲𝗱:

The problem isn't the vendors.
𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 𝗶𝘀 𝘁𝗵𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻.

We keep asking: "Who's best-in-class?"
We should be asking:

• Who has done this at our scale—and what broke?
• Can I speak to the person who actually ran it?
• What did they underestimate going in?


Accountable leaders don't need more innovation theater.
They need:

1. Proof under pressure
2. Context, not case studies
3. References who ran the same race, not just sponsored it

𝗜𝗻 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗼𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀, 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗰𝗿𝗲𝗱𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗯𝗲𝗮𝘁𝘀 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗲𝘃𝗲𝗿𝘆 𝘁𝗶𝗺𝗲.

Three questions before your next vendor decision:

1. Can I speak to the day-to-day operator (not the C-suite sponsor)?
2. Who delivered this at our scale, and what failed first?
3. What took 3× longer than promised, and why?

If they can't answer these, you're not buying a solution.

𝗬𝗼𝘂'𝗿𝗲 𝗯𝘂𝘆𝗶𝗻𝗴 𝗮 𝘀𝗮𝗹𝗲𝘀 𝗱𝗲𝗰𝗸.

PS
That realization came from expensive mistakes inside retail, and changed how I think about trust at scale.

The future of eCommerce won't be won by hype.
𝗜𝘁'𝗹𝗹 𝗯𝗲 𝘄𝗼𝗻 𝗯𝘆 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗲𝗱 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻.

How many "best-in-class" vendors didn't deliver what they promised?

I watched a €2M digital transformation crash in 6 months.

The CIO had the budget.
The CFO gave the green light.
A “top-tier” agency was on retainer.

Six months later, the room went cold.

The CFO asked:
“Why are we €500k over budget and still using spreadsheets to track inventory?”

There was no good answer.

Because they bought a solution
and ignored the Shadow Monsters living in their tech debt.

Here’s the real lesson:

Digital transformation isn’t a tech problem.
𝗜𝘁’𝘀 𝗮𝗻 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗴𝗮𝗽.

You can’t lead a transformation if you’re flying blind through:
	•	political silos
	•	undocumented integrations
	•	duct-tape code no one wants to touch

The leaders who actually ship ROI do three things differently:

→ 𝗠𝗮𝗽 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗿𝗶𝘀𝗸 𝗲𝗮𝗿𝗹𝘆
They don’t ask “Will it work?”
They ask “What will break first?”

→ 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗽𝗼𝗹𝗶𝘁𝗶𝗰𝗮𝗹 𝘀𝗵𝗶𝗲𝗹𝗱
They use data to protect their reputation before the CFO starts asking questions.

→ 𝗘𝘅𝗽𝗼𝘀𝗲 𝘁𝗵𝗲 𝗦𝗵𝗮𝗱𝗼𝘄 𝗠𝗼𝗻𝘀𝘁𝗲𝗿𝘀
They name the technical debt others prefer to hide.

Your next project doesn’t need more “innovation.”
It needs more precision.

So I’ll ask you this:
What’s the biggest Shadow Monster hiding in your roadmap right now?

Unpopular opinion:
Your digital transformation didn’t fail because of the technology.

It failed because you bought a solution
and inherited a 𝗦𝗵𝗮𝗱𝗼𝘄 𝗠𝗼𝗻𝘀𝘁𝗲𝗿.

Here’s what actually kills €10M+ digital projects:

❌ It’s NOT the Shopify / Salesforce migration
❌ It’s NOT the agency’s “lack of creativity”
❌ It’s NOT a missing feature set

It’s the 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗥𝗶𝘀𝗸 no one wants to name:

✅ The Invisible Tax
Legacy duct-tape code quietly eating 30–40% of every new feature budget

✅ The Data Silo
Buying AI when customer IDs don’t even match across systems

✅ The Missing Political Shield
Making a €500k decision based on a vendor demo—not your real site latency

I’ve seen companies spend millions on “innovation” while:

→ A 3-second mobile lag leaks €50k/week
→ Teams build shadow workarounds for the new stack is too complex
→ Success is measured by Go-Live, not Value Yield

The companies that win?

They stop managing expectations
and start managing 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗥𝗶𝘀𝗸.

They move from lone fighters to supported operators who track:
→ the true cost of technical debt
→ the net value of every vendor in the stack
→ the data that proves progress—or exposes failure

The truth?

Buying technology is easy.
Making it 𝗖𝗮𝗽𝗮𝗯𝗹 𝗼𝗳 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗶𝗻𝗴 𝗥𝗢𝗜 is the real job.

So ask yourself:
Are you leading a transformation...
or just surviving one?

The most dangerous phrase in digital leadership isn’t “we failed.”

It’s “we’re almost there.”

Because “almost there” hides three dangerous assumptions:

1.  That the remaining 10% is trivial
2.  That staging performance equals production performance
3.  That “works” and “works under load” mean the same thing

I’ve seen “almost there” quietly turn into:
• three more months
• €400k in unplanned costs
• a reputation you spend 6 months rebuilding

Here’s the shift that changes everything:

Stop saying:
“𝗪𝗲’𝗿𝗲 𝗮𝗹𝗺𝗼𝘀𝘁 𝘁𝗵𝗲𝗿𝗲.”

Start saying:
“𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝘀𝘁𝗶𝗹𝗹 𝗯𝗿𝗲𝗮𝗸𝘀 𝘂𝗻𝗱𝗲𝗿 𝗿𝗲𝗮𝗹 𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀.”

The Digital leaders who keep credibility don’t celebrate proximity to done.

They quantify distance from ready.

So ask yourself:

When you say “almost there”,
are you measuring real progress…

or managing expectations?

Uncomfortable truth:

You already know your launch is missing critical capabilities.

You flagged them.
You documented them.
You got overruled.

Now you're two weeks from go-live, hoping you're wrong.

When the CFO asks "Why didn't we know this would break?"
"𝗪𝗲 𝘄𝗲𝗿𝗲 𝗵𝗼𝗽𝗶𝗻𝗴 𝗶𝘁 𝘄𝗼𝘂𝗹𝗱𝗻'𝘁" 𝘄𝗼𝗻'𝘁 𝘀𝗮𝘃𝗲 𝘆𝗼𝘂𝗿 𝗷𝗼𝗯.

Stop hoping. Start proving.

⸻

Here's the Pre-Launch Data Shield I've used to protect 40+ launches:

⸻

1️⃣ Audit the Gaps (T-3 weeks)

𝗟𝗶𝘀𝘁 𝗲𝘃𝗲𝗿𝘆 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗵𝗮𝘁 𝗱𝗶𝗱𝗻'𝘁 𝗺𝗮𝗸𝗲 𝗶𝘁.

For each, answer:
→ % of revenue impacted
→ Performance gap vs. today
→ Adoption risk if it underperforms

𝗡𝗼 𝗼𝗽𝗶𝗻𝗶𝗼𝗻𝘀. 𝗝𝘂𝘀𝘁 𝗲𝘅𝗽𝗼𝘀𝘂𝗿𝗲.

⸻

2️⃣ Model the Impact (T-2 weeks)

𝗗𝗼𝗻'𝘁 𝗴𝘂𝗲𝘀𝘀. 𝗠𝗼𝗱𝗲𝗹.

Example:
Search = 32% of revenue
New platform = 400ms slower
Industry data: 100ms ≈ −1% conversion

Math: 4% conversion loss = €64k/month
90-day impact = €192k

𝗡𝗼𝘄 𝘆𝗼𝘂 𝗵𝗮𝘃𝗲 𝗮 𝗻𝘂𝗺𝗯𝗲𝗿 𝘁𝗼 𝗱𝗲𝗳𝗲𝗻𝗱.
Or a number that forces the delay conversation.

⸻

3️⃣ Present Scenarios (T-1 week)

𝗚𝗶𝘃𝗲 𝗹𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝘁𝗵𝗿𝗲𝗲 𝗼𝗽𝘁𝗶𝗼𝗻𝘀 (𝘄𝗶𝘁𝗵 𝗿𝗲𝗮𝗹 𝗺𝗮𝘁𝗵):

A) Launch as Planned
→ −€320k/month for 90 days
→ Total cost: €960k + reputation damage

B) Delay 4 Weeks, Fix Critical Gaps
→ €200k OpEx, €0 revenue loss
→ Net: €760k protected

C) Hybrid Launch
→ Fix checkout + mobile
→ Accept search lag
→ −€120k/month with mitigations

⸻

The shift?

You're not saying "this will fail."
𝗬𝗼𝘂'𝗿𝗲 𝘀𝗮𝘆𝗶𝗻𝗴 "𝗵𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗰𝗼𝘀𝘁𝘀—𝘆𝗼𝘂 𝗰𝗵𝗼𝗼𝘀𝗲."

𝗡𝗼𝘄 𝘁𝗵𝗲𝘆 𝗼𝘄𝗻 𝘁𝗵𝗲 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻. 𝗡𝗼𝘁 𝘆𝗼𝘂.

That's not fear-mongering.
𝗧𝗵𝗮𝘁'𝘀 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆.

⸻

The leaders who keep their jobs after failed launches?

They don't bet on hope.
𝗧𝗵𝗲𝘆 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝘆 𝗿𝗶𝘀𝗸 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲 𝗖𝗙𝗢 𝗱𝗼𝗲𝘀.

So be honest:

3 weeks from launch, can you prove what breaks?

Because when Black Friday crashes at 9 AM—
"We were hoping it would be fine" won't save you.

taplio

The Battle

Shyvee Shi

Marco Lanzi

Followers

Posts

Engagements

Likes

Performance ScoreMarco Lanzi's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Shyvee Shi

Marco Lanzi

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);}Marco Lanzi's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreMarco Lanzi's LinkedIn Performance