I’m Head of Growth at Assurix, where I own go-to-market strategy and pipeline growth for a vertical B2B SaaS platform serving MSPs.

My focus is building predictable growth engines, turning marketing from a set of activities into a system that leadership can forecast, trust, and invest behind.

I specialise in:

- Go-to-market strategy and positioning in complex B2B markets
- Full-funnel design, from first touch through to pipeline and revenue
- Growth analytics, forecasting, and board-level reporting

Aligning marketing, sales, and product around shared commercial outcomes

Previously, I’ve led growth and performance across global agencies and in-house SaaS teams, managed £1m+ in annual ad spend, and rebuilt inbound funnels to materially increase pipeline contribution and conversion quality.

I’m most effective in businesses that care about evidence over vanity metrics, value long-term commercial thinking, and want growth to be something the whole leadership team can rely on - not just a marketing function.

Robert Dodds

The decisions that compound fastest are the ones that change who you learn from, what problems you’re close to, and how high the bar is.

I’ve seen a lot of MSPs do the hard work, then lose out because the market can’t tell who’s actually better.

Assurix is changing that, turning security and operational maturity into something that’s visible and provable, not just promised.

Looking forward to building.

Head of Growth at Assurix | Turning Marketing into Predictable B2B SaaS Revenue

Founder & CEO @ Assurix | Proof Not Promises

Your first 10 hires will hire the next 50.

Not on paper.
In behaviour.

They set the defaults:
What "good" looks like. What gets a pass. What gets fixed without drama.

Robert Dodds ran marketing at Netstar when I was there. He's seen what buyers say, what they do, and what they punish MSPs for.

He's now joined Assurix as Head of Growth.

That's the kind of early hire that sets the standard.

This isn't an announcement post.
It's a culture post.

Founders love saying "culture matters"…
then delegate hiring early because they're busy.

You can outsource the admin of hiring.
You can't outsource the consequences.

Who was your best early hire?
And what did everyone else start copying from them?

Engineering Director at Deloitte | I help Tech people step up as Leaders

I drive strategic growth and technology-enabled transformation for tech-enabled companies and scale-ups, building organizations that thrive in complexity.

With 17+ years of experience leading large-scale technology initiatives and cross-functional teams, I combine deep technical expertise with strategic business leadership.

Currently serving as CTO / Tax Technology Director at Deloitte, I partner with executive teams to align technology innovation with business goals, streamline operations, and unlock new value through digital transformation.

My leadership journey started early — from leading engineering teams at 24 to delivering multi-million-euro projects across Automotive, Telecom, and now Tax & Legal industries. Throughout, my focus has remained constant: driving impact through strategy, technology, and people.

Beyond my corporate role, I'm passionate about building future-ready leaders and organizations through my newsletter and personal coaching. I believe that technology is not just a tool — it's a catalyst for strategic advantage and sustainable growth.

PS: I am always open to connecting with forward-thinking leaders, founders, and organizations focused on innovation, growth, and technology-driven transformation.

Leonard Alexandru

My goal for 2026 is clear:

Becoming a top voice in AI.

Not because it is fashionable.
And not because the tools are impressive.

But because most AI conversations miss the real problem.

AI rarely fails because of technology.

It fails because of leadership.

Because of decisions.

Because of how organizations actually work.

What I keep seeing:

• Leaders chasing tools, not clarity
• Teams overwhelmed, not empowered
• Automation added on top of broken processes

And most of all:
AI treated as an IT issue, not a business one

So my focus for the next year is simple.

I will write, teach, and build around one question:

How to adopt AI in a way that makes organizations stronger, not more fragile?

That means:

• Less hype
• More thinking
• Better decisions
• AI as leverage, not dependency

I am not trying to be loud. I’m trying to be useful. 

This is me claiming the direction.

Now comes the work.

Follow me along.

Head of Tax Technology & Innovation at Deloitte | AI Strategy & Adoption for Leaders

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Conduc echipe de IT de 15 ani.

Și dacă ar fi să spun un lucru pe care l-am văzut de nenumărate ori, ar fi acesta:
problemele din proiectele IT nu sunt tehnice.

Sunt de claritate.
De așteptări.
De cine decide ce, când și de ce.

Am văzut proiecte cu oameni foarte buni care s-au blocat pentru că:

- backlog-ul era o listă de dorințe, nu un plan
- nimeni nu a definit clar ce înseamnă „done”
- „Agile” însemna de fapt improvizație

Și, foarte des, am văzut oameni ajungând PM în IT fără să-i fi învățat cineva cum arată un proiect dus până la capăt.

Cursul acesta a pornit din frustrarea asta.

L-am construit exact așa cum mi-ar fi plăcut mie să fie un curs când făceam tranziția de la tehnic la leadership:

- mai puțină teorie
- mai puține buzzword-uri
- mai mult „să facem un proiect ca în viața reală”

Pe parcursul cursului:

Simulezi un proiect IT real, nu exerciții abstracte.

Treci prin backlog, sprinturi, riscuri, stakeholderi și livrare.

Pleci cu lucruri concrete pe care le poți pune în CV și pe LinkedIn, fără să te simți impostor

Dacă vrei să intri în IT project management sau ești deja acolo și simți că „te descurci, dar nu stăpânești jocul”, probabil o să-ți fie util.

Nu este un curs ușor.
Dar este unul onest.

Dacă vrei detalii, scrie-mi in privat.
Vedem dacă e potrivit pentru tine.

https://lnkd.in/dwBi9VJQ

Practice what you preach!

I've started my year-long journey of becoming a top voice in AI by completing an introductory course, Elements of AI: Introduction to AI from University of Helsinki!

It's one of the best beginner resources out there, if you want to start somewhere. 

It has some math and statistics in it, but nothing to be scared of. 

On to the next one!

Stop Looking for AI Use Cases. 

Start Looking for Bad Processes.

Here's what I see happening in organizations:

Leadership gets excited about AI.

They form an innovation team.

They ask, "What can we do with AI?"

Then they start layering ChatGPT, automation, and machine learning on top of their existing mess.

The result?
- Automated chaos.
- Faster bad decisions.
- Expensive disappointment.

The conclusion is always the same:

→ You can't AI your way out of a broken process.

I've watched this play out dozens of times in enterprise environments.

A team wants to use AI to speed up compliance reviews.

Sounds great.

Except their data lives in 14 different systems.
Their approval workflow requires 9 signatures.
And nobody can explain why half the steps exist.

So what happens?

They build an AI tool that makes recommendations nobody trusts because the underlying process is still garbage.

Here's the better approach:

Before you ask "Where can we use AI?"

Ask this instead:
- "Where do we waste the most time?"
- "What processes are currently killing us?"
- "What makes our best people want to quit?"

Fix the process FIRST.

Simplify it.
Document it.
Make it actually work for humans.

Only then ask if AI can make it 10x better.

AI is a performance multiplier.

It multiplies whatever you feed it.

Feed it chaos → get expensive chaos.
Feed it a clean, smart process → get magic.

The unsexy truth:
Most organizations need boring process fixes more than they need bleeding-edge AI.

But process improvement doesn't get budget.
AI does.

So we keep building fancy solutions to problems we don't understand.

If you can't explain your process to a new hire in under 10 minutes, you're not ready for AI.

Full stop.

Developers resist AI the most, and it’s not because the tech is bad. 

I was surprised to see that the people most reluctant to AI are the ones who should have embraced it first.

But then it clicked.

For years, developers built their identity on scarcity. On being the gatekeepers.

On being irreplaceable. 

AI breaks that illusion.

When code becomes easier to generate,
when execution gets faster,
when more people can “do the thing"

Being the one who knows stops being a moat.

That hits ego. That hits status.
That hits self-worth.

So the pushback hides behind respectable arguments:

“AI lowers quality”
“AI produces bad code”
“AI is dangerous in production”

Sometimes true. Often exaggerated.

Because the real fear is simpler and harder to admit:

If anyone can write decent code, what makes me special?

AI doesn’t make developers less valuable.
But it forces a shift in where value comes from.

From writing code to deciding what should be built, why, and how it fits into a system.

Some will adapt and become force multipliers.

Others will spend years fighting a tool instead of redefining their value.

And in fast-moving systems like this, resistance can be a career choice.

Agentii AI au ajuns sa vorbeasca intre ei pe retele de socializare si noi punem intrebari de genul "Ce număr la loto iese săptămâna asta?” pe ChatGPT.

Young professionals simply don’t want to learn anymore.

They avoid training.
They are disengaged.
They do the minimum.

It’s easy to stop the analysis there.

But I don’t think that’s the real story.

What I’m seeing has less to do with laziness and a lot more to do with trust, uncertainty, and how learning used to help versus how careers actually work today.

And a deeper question about whether learning still feels like protection or just effort without guarantees.

I unpacked all of this in the latest edition of my newsletter.

If you’re leading people, building a career, or trying to stay relevant in a messy world. 

This one might resonate.

Why do you think professionals resist learning today?

Link in comments

A goal without a plan is just a dream. 

I talked the other day about my goal of becoming a top voice in AI.

Not as a tool collector.
Not as a prompt engineer.
Not as someone who chases every new release.

But as a leader and a strategist.

AI is already changing how decisions are made.

How work is structured.

How power moves inside organizations.

This matters more than knowing the latest tool.

So I built a 12-month AI learning roadmap.

Structured in 3-month blocks, with a clear focus:

• Understanding what AI really is (and isn’t)
• Why adoption fails and how to design for it
• Governance, risk, and decision ownership
• How AI reshapes work and leadership

The goal isn’t to become more technical.

It’s to become useful in conversations with leaders.

To help make better decisions.

To design organizations that don’t break under new technology.

I’ll share parts of this journey publicly as I go.

Because clarity comes from learning, building mental models, and reflecting in the open.

If you’re a leader trying to make sense of AI beyond hype and fear, you’re not alone.

This is the work I’m committing to.

PS: Am I missing anything?

The career ladder is gone.

Entry-level hiring at major tech companies? 

Down 50%+ since 2019.

It's not a hiring freeze. It's a new paradigm.

The "task rungs" that trained juniors:
- first drafts
- data cleanup
- meeting summaries

All done by AI now. 

You can't wait for the next step to appear. 

You have to build it yourself.

The new success pattern:

1. Everything is a skill issue

Don't know how to code? Skill issue.

Don't know how to analyze data? Skill issue.

AI is your accelerator. Use it to bridge gaps fast.

2. Collapse your "say-do" gap

Most people plan for weeks.

High-performers move from idea to outcome in days.

Stop looking for the perfect plan. 

Ship, learn, iterate.

Titles no longer mean anything. 

Outcomes mean everything.

Your ability to spot problems and drive them to resolution? 

That's the only currency that compounds.

The ladder is gone. 

But the ceiling has never been higher.

Stop waiting for permission.

"Of course, everyone in the company uses AI."

Every company deck shows this. 

Every strategy slide.

Every interview. 

But then you look at data like this.

According to Eurostat, the percentage of people actually using generative AI tools for work is still surprisingly low across Europe. 

In many countries, it is not even in double digits yet. 

Romania is dead last in the EU with 5%. 

That gap matters.

Because what we often call “AI adoption” today is mostly about licenses bought “just in case” or a few power users carrying the narrative

Not transformation.

This doesn’t mean AI is a bubble.
But it does mean expectations are running far ahead of capabilities.

Real adoption is boring. 

New habits.
New decisions.
Managers who actually understand what these tools do and what they don’t.

Most organizations skipped that part.
They went straight to tools.

So no, AI is not replacing everyone.
(Though it will replace many, unfortunately)

But it is exposing something uncomfortable.

How shallow many transformations really are.

The companies that will win are not the loudest.

They are the ones quietly building capability, literacy, and trust around it.

Hype fades.
Capabilities compound.

Is AI in your company still a slide in a deck?

Most people use AI wrong.

They paste a prompt, get generic output, and wonder why it sounds like everyone else.

Here's the shift that changed everything for me:

Stop using AI to write.
Start using AI to think.

I've been using a 5-step framework to go from messy idea to structured content in ~20 minutes:

→ Brain dump (no filter)
→ Extract the core
→ Build the scaffold  
→ Stress-test it
→ Make the decision yourself

The last step is where most people bail.

But that's exactly where your voice lives.

Full breakdown with a practical example in my latest newsletter edition (link in comments) ↓

Save this for the next time you're staring at a blank doc.

Brain Dump to Brilliance: The AI Way

The good news: AI will not take over in 2027.

The bad news: it's just a delay. 

We've all seen this prediction from ai-2027.com

Earlier this year, the authors revised their views.

The new date for the super intelligence is the early 2030s. 

Less certainty. More nuance. More humility.

Not because AI stopped progressing.
But because reality is messier than timelines.

Models improve faster than organizations.

Adoption, capabilities, culture, and leadership.
These are the real bottlenecks.

And I don't believe in the doomsday scenario. 

I believe we can work with AI to create a better future. 

A future that belongs to those who built the right foundations.

Are you doing it?

E ok, nu o sa fie niciun programator impactat.

One of the most impactful projects I'm a part of. 

Lucian Popovici helped put together some of the brightest people in the tech industry.

La creme de la creme :)

So, if you want the opportunity to work with them, sign up for the next cohort of mentees.

It's free, but you have to put in the effort.

2 days left to register for high-impact pro-bono mentoring & coaching from our Bridging Gaps mentors!

We’re excited to see so much interest already, for our first 2026 cohort! And looking forward to support tech professionals going through transitions in our #ProBono Mentoring Program!

Our community includes 80+ senior leaders from technology, consultancy, and services companies, based across Europe, Asia, and the US - sharing their knowledge and experience pro-bono.

Given our extensive experience, we can support through pro-bono mentoring and coaching senior SMEs, first-time, middle and senior managers in IT companies in Romania who want more from their career but they have difficulties in finding ways forward.

In 2025 we collectively supported over 200 professionals because we believe in the power of community, giving back and contributing to growth!

Have a look at the testimonials below, for inspiration:

Real stories, in mentees’ own words.
Real impact & growth, in an industry undergoing significant transformation.

So: if you want clarity, better decisions, advancing your career, and a thinking partner who understands the reality of complex roles in the evolving tech industry, look for the sign-up link in the first comment.

Registrations open until tomorrow EOD.
Let’s do this! ⚡ 

#GrowTogether #ProBono #Mentoring #Coaching #Community #CareerGrowth

Real impact. Stories from our Mentees

I will be more blunt than this. 

Tax technology will be the ONLY career path for tax professionals. 

Maybe not next year or the one after, but eventually. 

90% of the work is already subject to AI and automation. 

Time will tell.

US & European Indirect Tax, Tax Technology, & Tax Leadership recruiter 🇺🇸🇪🇺

Tax Software is the Third Career Path 

If you trained at a Big 4 / Top 10 and are now at Assistant Manager or Manager level, your profile is in demand for a reason.

You have built a strong technical base. You know how to manage stakeholders. You can translate complex tax rules into something commercial and usable. And you are still early enough in your career to shape what comes next.

Most people at this stage assume there are only two logical moves. Stay in practice and push on. Or step in house.

What often gets overlooked is tax software.

Unless you have already worked in transformation or technology, software roles rarely appear on the radar. Yet many Big 4 trained professionals reach this level and realise they no longer want a traditional client service career. Practice was the training ground, not the destination.

Tax software firms offer a genuine third path. They are growing, creating new roles every year across product, implementation, advisory, and go to market functions. The work is still technical and impactful, but with far broader exposure to how tax actually operates at scale.

Crucially, moving into tax software does not shut the door on an eventual in house role. In many cases, it strengthens your profile by giving you systems exposure, commercial insight, and a deeper understanding of how tax functions really run.

For tax and tax tech professionals who want options, not a straight line, tax software is worth serious consideration.

taplio

The Battle

Robert Dodds

Leonard Alexandru

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taplio

The Battle

Robert Dodds

Leonard Alexandru

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);}Robert Dodds's LinkedIn Performance

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