I'm the Managing Director and co-founder of Filament, a digital agency specialising in Go-to-Market strategy and partner marketing for B2B tech companies and vendor channel programs.

Over the last 17 years, I've worked with diverse companies to build and expand marketing frameworks, deploy demand gen and lead gen programs, enter new markets, unlock support from tech vendors, and increase market share. 

Tech companies and vendor channel programs I’ve supported include VMware, Microsoft, Dell, Cisco, HPE, AWS, Google, IBM, NetApp, Veeam, Tata, Zerto, Dropbox, Nutanix, Symantec and Splunk.

This has meant I’m experienced in working with a variety of B2B tech company and channel partner types, including:

👉 Independent Software Vendors (ISVs)
👉 Managed Service Providers (MSPs), Value-Added Resellers (VARs) and System Integrators (SIs)
👉 Cloud-based service providers, including IaaS, PaaS and SaaS companies
👉 Cybersecurity and Managed Security Service Providers (MSSPs)
👉 Edge infrastructure and IoT providers
👉 Virtualization and application deployment specialists
👉 Data centres, and
👉 Distributors and Aggregators.

Prior to leading agencies I was primarily leading marketing and communications programs in the finance and investment sector.

Key career highlights I’m proud of include:

✅ Articulating the state of mobile marketing for Google SE Asia, in partnership with Capitalis
✅ Supporting Australian tech companies to enter and expand in the US
✅ Significantly growing a channel program by 4x in 12 months
✅ Leading the corporate communications on a $47.1 million off-market transaction of an investment firm with $3 billion FUM
✅ Expanding a SaaS multinational's footprint in SE Asia

Jeremy Balius

Many tech companies think they have a growth problem, when they actually have a visibility problem.

A common theme so far this year in conversations I'm having with tech execs is operational efficiency. 

Not in terms of cost-cutting, but rather, in terms of clarity.

When they talk about “GTM efficiency" or even "GTM focus", what they’re really trying to get to the bottom of is:

What’s meaningful GTM investment… and what’s waste?

It's tricky to write about in general terms but here’s where I see some hidden waste creeping in.

❗️ Multiple campaigns targeting overlapping audiences and creating confusion, or worse, all getting ignored
❗️ Successive campaigns not retargeting audiences to create meaningful moments over longer periods of time 
❗️ Different teams telling slightly different stories
❗️ Vendor-funded activity that doesn’t align with core positioning or serves vendor sales cadence rather enabling Partner sales nurture rhythm
❗️ Sales enablement assets that don't enable, i.e. never get used, because GTM or marketing doesn't understand the complexities sales professionals face

None of these look dramatic on their own. But together, they create drag.

That’s waste.

GTM investment, on the other hand, feels expensive upfront.

✅ Tightening positioning and meaningful differentiation before scaling campaigns, ensuring you lead with value rather than "Always Be Closing"
✅ Retargeting, nurturing, trust building over uncomfortably-long periods of time
✅ Taking control over going-to-market together with vendor alliance partners, rather than following their lead
✅ Aligning sales and marketing around one narrative and mutually-agreed lead definitions
✅ Reworking partner motions instead of layering on more tactics

These decisions don’t create instantly attributable return - especially when analysed on their own.

But the coherence and focus this creates compounds.

Right now tech executives aren’t asking me, “How do we spend less?”

They’re asking, “Where is effort being diluted so we can double down on what is working?”

There’s a big difference and that's been the main theme in January.

What feels like real meaningful GTM investment for you… and what feels like a drag?

#GTM #gotomarket

I help B2B tech companies go to market faster. Founder with 1 exit.

GTM waste vs efficiency

"You should embrace AI” has been a real common GTM push (wrapped up as strategic advice) by Partners to their end user clients.

Very few leaders know how to visualise success or measure if it’s working. 

I was reminded of this clip from Episode 26 of Go-To-Market Playmakers in discussion with Dave Boyce from Winning by Design. 

If AI is reshaping go-to-market…

How do you evaluate success when you don’t even know what the final model looks like yet? And what if there are no traditional guide posts along the way?

There's a practical concern here:

How do we know if this is actually improving performance when the landscape changes so fast within even a quarterly cycle?

One idea that resonated strongly with me in the discussion was this: If you can’t measure the experiment, why are you running it?

The way Dave frames the concept of Minimum Viable Signal Loop was a gamechanger for me.

That AI adoption in GTM isn’t about tools, it’s about signal.

It's a real mindset shift.

Full episode is down there 👇

Strategy has never looked better on the slide deck. But momentum hasn't felt this hard inside the organisation in a long time.

In conversations with tech execs across cyber, IaaS and hardware manufacturers over the past week, a theme kept surfacing:

The strategy is clear. The goals are dialled in. It's been impressive to see! 

But the execution feels scattered. 

Teams are super busy, but they're stretched. Everyone is moving… but not always in the same direction.

That gap between strategy and execution is widening. And this isn't a clarity problem.

There's potentially three quieter forces at play here.

First, strategy shifts faster than operating rhythm.
By the time teams galvanise around one direction, the next adjustment comes through. Momentum resets before it compounds. Staying afloat and keeping up becomes the unspoken priority.

Second, too many things qualify as “strategic.”
When everything is a priority, focus fragments. Individually, each initiative makes sense. Collectively, they create drag. It seems like common sense but this one quietly becomes the norm.

Third, incentives rarely align perfectly with stated intent.
Leadership may emphasise long-term positioning. Teams are often measured on short-term output. Monthly and quarterly cycles shape behaviour. Whether we admit it or not. 

What I’m noticing is this:

The organisations that feel stuck aren’t lacking intelligence or effort. It's the coherence that turns strategy into momentum.

Are you seeing this as well?

The widening gap between GTM strategy and execution

A weak value proposition shows up as a growth problem. But does that mean it's a messaging problem?

In a lot of tech companies I speak with, there is a strong internal belief in their positioning.

The feature comparison is strong. The deck is polished. Sales can explain what the service or product does.

They'll even talk about how they have the best tech, the best service and the best people.

But when you zoom out, something's not landing.

Whether that's visible in demand, pipeline, deals dragging or inconsistent win rates, it's usually not a sales capability issue. It starts much earlier in the causation chain.

It’s usually a positioning issue.

When the value proposition is similar or same with other competitors, the consequences ripple.

There's no cut-through to reach net new prospects. Sales teams start customising the story deal by deal. Each rep frames the product slightly differently. Consistency erodes. 

Partner sales team or distie sales teams struggle even more. If your own team can’t articulate sharp differentiation, how do you expect an external team to do it?

They also default to features. Or worse, they deprioritise your offer because it doesn't land as easily or quickly as other offers in their stable.

None of this breaks the business overnight. And none of this can be clearly pointed to as a direct cause for any of the issues. 

That’s what makes it so tough to navigate.

The cost compounds quietly:
➞ Lower quality pipeline.
➞ Longer sales cycles.
➞ Increased discounting.
➞ Fragmented brand perception.

And by the time leadership notices, it looks like a demand problem.

Differentiation isn’t a marketing exercise.

It’s a strategic control point. It's the very core of your Go-to-Market as a company.

Clear differentiation that means something to your target buyers or ICP buying committee members? 

That's what separates momentum from drag.

I've seen this pattern countless times: GTM strategy doesn't lead to sales momentum.

The leadership team invests time and effort into a brilliant go-to-market strategy. The positioning is sharp. The differentiation is clear. The pricing tiers make sense.

Then sales has to translate it. And then the GTM fragments.

Reps default to features. Objections get handled inconsistently. New offers launch without playbooks. 

By the time the strategy reaches the end user prospect, it's unrecognisable.

The problem isn't the strategy. It's the execution layer between strategy and sales conversations.

I just recorded an on-demand webinar that shows how B2B tech companies solve this with high-impact GTM enablement. (and I'm trialling long-form uploads here on LinkedIn!) 

It covers:
→ Why great strategies fragment at the sales level 
→ The 4-phase framework we use to build structured enablement systems 
→ How to standardise value conversations across your entire team 
→ A real case study from FUJIFILM CodeBlue NZ

This isn't about creating more collateral. 

𝐈𝐭'𝐬 𝐚𝐛𝐨𝐮𝐭 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐜𝐡𝐚𝐧𝐠𝐞 𝐡𝐨𝐰 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐬 𝐡𝐚𝐩𝐩𝐞𝐧.

If you're a tech leader watching your sales reps improvise your carefully crafted positioning, this one's for you.

Watch the full webinar below. 👇

“Security is not an option anymore. It’s part of the infrastructure.”

Storage used to be a capacity discussion, but it's become so much more.

Jeff Hyunshik Park, Country Manager Australia at Seagate Technology, shares in this edition of Tech Exec Insights how Seagate is increasing enterprise capacity without increasing footprint or power consumption.

That matters because AI growth is not slowing down.

He also made it clear that hardware encryption and embedded security are now baseline requirements, not premium add-ons.

The bigger shift? In 2026, infrastructure decisions are being shaped by:
• AI workload pressure
• Data sovereignty concerns
• Cyber resilience expectations

Are your infrastructure conversations evolving fast enough?

It's not that GTM strategy fails. It's the 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 that fragments.

After years of working with B2B tech companies, we see the same patterns repeat:

➞ Leadership decks are crystal clear. Sales conversations are less clear.
➞ Reps pitch features. Customers need value.
➞ Objection handling varies wildly across your team.
➞ New offers launch with excitement, but no playbook leverages the attention.
➞ Sales tools are scattered across folders, formats, and individual laptops.

The gap may not be your strategy. 

It's the system that translates strategy into sales conversations.

Watch this quick breakdown from our recent sales enablement webinar. 👇

#SalesEnablement #B2BSales #GTMStrategy

Storage decisions are no longer made by IT alone. 

Security wants risk clarity. Finance wants lifecycle visibility. Executives want continuity and AI readiness.

In this clip from Tech Exec Insights, Jeff Hyunshik Park from Seagate Technology explains why partners must shift from product-centric pitches to outcome-based conversations.

If your sales narrative still focuses on technical features only, you’re missing half the room.

He also shared something that really stood out to me:

Partners should bring vendors like Seagate Technology into architecture conversations early.

Why?

Because security, scalability, and lifecycle decisions are being shaped before procurement ever happens. By the time RFPs land, strategy is already set.

To me, this aligns with the mindset of "going to market together".

Are you strategically getting upstream in deals? Or are you still responding to requirements someone else defined?

Cosmo Tech | The Decision Twin Platform for Supply Chain, Finance & Asset Leaders at Fortune 500 Scale | Simulate Tomorrow. Decide Today.

I specialize in the messy middle of B2B SaaS scaling—taking companies from erratic growth to a disciplined, high-performance revenue engine.

Most sales teams don’t fail because they lack talent; they fail because of ambiguity.
When forecasts can’t be trusted, pipelines move only through founder heroics, and managers report activity instead of owning outcomes, you don’t need another playbook—you need an operating system.

My operating philosophy: Cadence | Ownership | Process

I install a repeatable flywheel of operational excellence:

Cadence
A rigorous Rhythm of Business—daily, weekly, and monthly operating cadence that surfaces execution risk early, before it becomes a board-level surprise.

Ownership
Managers own outcomes, not just activity. Forecasts are built bottom-up so leadership can commit without caveats.

Process
Qualification and execution are standardized before adding headcount, ensuring hiring is tied to capacity and real revenue impact—not hope.

The proof (Ekahau — SVP, Global Sales, 2019–2024)
	•	Revenue: Scaled $25M → $65M ARR in five years
	•	EBITDA: Increased $7M → $32M (margins ~20% → ~50%)
	•	Team: Built a 130-person global organization while reducing per-employee cost 25%

Selected wins
	•	Healthentic: Doubled ACV ($5M → $10M) and drove 10× pipeline growth through GTM transformation
	•	ControlCase: Delivered 34% YoY growth and 300% expansion revenue growth

Currently

Available for VP of Sales or Fractional GTM leadership with B2B SaaS companies $5M–$30M ARR. I also lead SalesGSS (revenue operating frameworks) and DigitalRegIntel (regulatory intelligence for AI/fintech).

The Senator perspective

Two terms as a Washington State Senator taught me the value of high-stakes negotiation and public accountability. I bring that same discipline to sales: clear ownership and execution when the pressure is real.

“Steve is ‘Instant Offense’ for sales—rare and valuable. World-class at creating strategic, data-driven sales teams.”
— Jeff O’Mara, CEO (Healthentic) / GM (Ekahau)

Steve Litzow

If revenue per employee is flat while headcount rises, you’re not scaling. You’re diluting.

Most $10M–$50M ARR teams are measuring the wrong thing.
They celebrate hiring.

Elite teams watch revenue per employee.

Here’s what 2026 is quietly proving:
Growth doesn’t stall because opportunity disappeared.

It stalls because attention fragmented.
New ICP.
New vertical.
New pricing model.
New feature set.
New partnership.
All rational.
All defensible.

Collectively? Expensive.

Revenue per employee isn’t a finance metric.
It’s a focus metric.

Bootstrapped SaaS companies at $1M–$3M ARR average ~$110K per employee.

Equity-backed peers average ~$94K.

Capital didn’t create the gap.

Discipline did.

Fragmentation increases decision latency.

Decision latency expands Signal-to-Action Time.

And once SAT expands, velocity stops compounding.
You don’t lose because you’re wrong.

You lose because complexity expands faster than discipline.

Pressure test your system:
• If you asked three reps to define your ICP, would they say the same thing?
• Do your top 20 deals look similar — or random?
• Has revenue per employee improved in the last two quarters — or are you hiring into flat output?
• When was the last time you killed an initiative?

Elite teams don’t run more plays.
They run fewer — with intensity.

Focus multiplies revenue per employee.
Complexity multiplies meetings.

Week 7 of the 2026 Operating Series.

Link in comments.

VP of Sales | Scaled $25M → $65M ARR | Operating Discipline for Growth & Scrutiny

The roadmap slide used to be the closer.
In 2026, shipping is.

Buyers don’t evaluate products by vision anymore.
They evaluate them by momentum.

Before they ever talk to your sales team:
• They’ve checked G2 for recent updates
• They’ve Googled what you shipped last quarter
• They’ve asked their network if you’re still actively building

They’re not asking “Where is this going?”
They’re asking “What have you shipped lately?”

Here’s what most teams miss:

Products that can’t show visible momentum during evaluation are assumed incapable of delivering value fast after purchase.

If buyers can’t see progress now, they won’t believe you can produce results in their first 60 days.

The strongest teams in 2026 aren’t winning on features.
They’re winning because buyers can see execution before the first call.

This is Week 4 of the SalesGSS 2026 Operating Series.

Next week: Why waiting for clean data is now officially malpractice.

FinCEN just made compliance easier.

That’s exactly why your documentation burden increased.

On February 13, FinCEN eliminated beneficial ownership verification at every account opening.

The same day, SEC Chairman Atkins testified that current crypto guidance isn’t “future-proof” without legislation.

That’s not regulatory confusion.

It’s the new supervisory model.

Fewer procedural checkboxes.
Higher expectations for documented judgment.

When regulators give you discretion, they’re not giving you a pass.

They’re giving you a decision to defend.

24–36 months from now, no one will ask:

“Did you follow the rule that no longer exists?”

They’ll ask:

• Why did you reduce controls?
• What risk assessment supported that?
• Who reviewed it?
• Where is the record?

Relief does not eliminate supervisory liability.

It reallocates it.

This week’s DRI Supervisory Brief covers:

→ FinCEN CDD relief and the judgment gap it creates
→ SEC-CFTC coordination that lacks statutory permanence
→ FinCEN’s data-driven enforcement model
→ EU AI Act entering pre-enforcement phase

Link in comments.

This week, nothing happened in digital asset and AI regulation.

That’s the problem.

No new rule.
No major enforcement.
No legislative breakthrough.

But across SEC–CFTC coordination, EU AI Act implementation, and AML oversight, expectations continued hardening—through guidance cadence, staff remarks, and enforcement posture.

When a bank diligence memo reconstructs this period in 2028, it won’t ask whether a rule changed.

It will ask whether your team noticed the shift and documented it while expectations were forming.

Silence during coordination phases is now reconstructable negligence.

This week’s Supervisory Brief: https://lnkd.in/gBbeuTQS

— DigitalRegIntel

Most teams don’t fail regulatory reviews because they ignored the rules.

They fail because they can’t prove what they knew, when they knew it, or what they did next.

By the time the question comes - 

Context is gone
Slack threads are incomplete
Intent has to be reconstructed
And hindsight becomes the standard

Briefs show awareness.
Explanations show intent.

Neither holds up in review.

What holds up is a time-stamped system of record.

Because when the question comes, explanations don’t count. Records do.

No new rule last week.

That’s the risk.

On Feb 13, FinCEN quietly operationalized its whistleblower portal.

Now AML, AI governance, and digital asset supervision gaps can be reported directly to enforcement — before an exam ever starts.

This changes the timeline.

Enforcement is no longer tied to regulatory cycles.

It’s tied to internal observation.

An email.
A Slack message.
A deferred monitoring upgrade.

Those can now become time-stamped federal evidence.

The real shift isn’t rulemaking.

It’s attribution infrastructure.

When regulators look back 24–36 months from now, the question won’t be:

“Did you know the rule?”

It will be:

“Can you prove you supervised in real time?”

Documentation is no longer defensive.

It’s existential.

Full breakdown in this week’s Brief. (Link in comments.)

"Our data isn't clean yet."

In 30 years of B2B sales, I've never seen a sentence cost more quarters than this one.

Last week, I watched a $28M ARR company delay territory planning for the third consecutive month. The reason? "CRM data isn't standardized yet."

Meanwhile, their top competitor just reassigned 40 accounts they thought they owned.
Here's what's breaking teams at $10M-$50M ARR right now:
They're treating perfect data as a prerequisite for decisions. Clean first, act second.

That logic worked in 2020. It's malpractice in 2026.

Not because data quality doesn't matter—it does. But because waiting for perfect data guarantees you'll be too late.

The teams winning aren't the ones with pristine systems. They're the ones extracting signal from noise fast enough to act while the opportunity still exists.

They deploy AI on messy data. They build decision triggers, not dashboards. They validate through small bets, not analysis paralysis.

They've accepted something most teams won't: Perfect data is a luxury you can't afford if speed determines survival.

The numbers tell the story:
AI high performers are 3x more likely to be scaling AI across business functions (Bain, 2025).
 Not because their data is cleaner. Because they learned to act on 70% confidence while others waited for 95% certainty.

78% of organizations now use AI in at least one function—up from 55% last year (McKinsey, 2025). But only 11% have achieved scale.

The barrier isn't technology. It's organizational willingness to act before everything is "ready."

Every quarter you delay pipeline, territory, or pricing decisions waiting for clean data is a quarter competitors use to steal accounts you already "own" on paper.

Your data will never be perfect.
Your window to act is closing.

Full breakdown: "Waiting for Clean Data Is Officially Malpractice" — Week 5 of the SalesGSS 2026 Operating Series (link in first comment)

What decision are you deferring until your data is "ready"?

#B2BSales #SalesLeadership #RevenueGrowth #SalesOperations #AIinSales

US enforcement is accelerating through whistleblower infrastructure.

EU regulation is accelerating through statutory documentation and logging requirements.

Different systems.

Same burden.

You must be able to prove:

• What management knew
• When it knew it
• How it assessed applicability
• What action (or deferral) followed

Frameworks don’t fail companies.

Missing chronology does.

Slow teams don’t catch up.
They fall permanently behind.

Here’s the math nobody wants to say out loud:

Every week your team debates,
a faster competitor runs three experiments,
kills two,
and scales one.

That gap compounds.

By Q2, it’s structural.

The assumption killing most $10M–$50M teams:

“We’ll move faster once we have more resources.”

It’s backwards.

Speed isn’t the result of scale.
Speed is the cause of it.

I call this Signal-to-Action Time (SAT) —
the gap between seeing a problem and doing something about it.

Elite teams compress SAT.
Average teams debate it.

And debate feels productive.

But it’s just delayed learning.

The cost of being wrong fast
is almost always lower
than the cost of being right slow.

Your competitors aren’t smarter.

They’re just running more learning cycles than you are.

And speed can’t be bought later.

It has to be installed.

Week 6 of the SalesGSS 2026 Operating Series.
Full breakdown (with data + operator discipline) in this week’s newsletter — link in comments.

Your deal didn’t lose to a competitor.

It died in a conference room.

40–60% of B2B deals end in “no decision.”

Not lost.

Just never aligned.

At $10M–$50M ARR, most teams still sell to a champion.

But the real sale is to the committee.

If a deal is single-threaded beyond day 45, your forecast isn’t aggressive.

It’s structurally optimistic.

This week’s issue breaks down how elite teams prevent ghost pipeline.

Comment PLAYBOOK and I’ll send it.

Marc Andreessen said at Cisco's AI Summit that "the regulatory landscape is fairly scary right now."

He's right about the acceleration.

But "scary" is usually what complexity looks like without infrastructure.
Here's what's actually happening:
- Over 1,000 AI-related bills introduced at the state level
- The EU AI Act creating obligations for U.S. companies selling into Europe

Enforcement posture evolving faster than most scaling teams can track

The giants will manage it. They have policy teams, in-house counsel, and lobbying capacity.

The exposed companies are in the $10M–$50M range — growing fast enough to attract regulatory attention, not yet resourced enough to track it systematically.

This isn't a political debate. It's an operational capability gap.

The companies that build regulatory tracking into their operating model now won't be scrambling later.

The companies that treat regulatory awareness as infrastructure will compound advantage.

The ones that treat it as background noise will compound risk.

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