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If you’re coming from accounting/controlling, this one might sting: nobody cares about the P&L. At least not in the way you’re used to. In early-stage startups, your job is of course to make sure the P&L is correct. But for the most part, nobody else will care. They might nod (sleepily) when you talk through budget vs. actuals, but their minds will be elsewhere..

What really matters

In a high-growth early-stage company, the P&L is full of background noise. It’s useful internally for finance, but management, investors, and the board are not making decisions based on a clean revenue recognition schedule. They care about something much simpler: survival and growth.

Here’s what actually matters early on (in order of importance):

• Cash & burn: How much do we have? What’s runway and spend for the next 3, 6, 12, 24 months?

• Unit economics: LTV:CAC, CAC Payback, Margins, GRR, NRR

• Warning signs: Can we sustain growth? Are we building pipeline? Are we investing too much / too little?

• Levers: If growth stalls, can we cut spend & reach profitability? How does the underlying business perform?

The board doesn’t care if your variance to budget is 2% or 5%; they care about growth. Can you deploy more capital to grow faster? Are your unit economics holding? Can you pivot to profitability and extend runway if needed?

Real startup finance - in practice

When you’re in hyper-growth mode, you should be building like water flows; following the path of least resistance. Instead of trying to get the perfect SaaS P&L or build the perfect data warehouse, find ways achieving your goal.

I’ve worked with early stage startups where we built the reporting stack based on:

• CRM data (tracking sales-led growth & ARR as north star metric)

• Payroll data (for CAC spend)

• Marketing data (directly from marketing team)

Using those data sources, we created our reports within days after month end. The P&L still took about 10-12 days to close (outsourced to external bookkeepers), but we didn’t need that; we just needed enough data to get our directional CAC and ARR metrics.

Of course the finance team reviewed the P&L, made sure to align if we were directionally going off budget or shifting spend; but our north star was growing ARR and monitoring the CAC, so we found ways to surface that and create common language across GTM and finance functions.

Your job as CFO at this stage

As CFO, your job is of course to monitor cash movements; and always have a solid liquidity model in place. Keep it as simple as possible; if you’re getting annual payments, model in your ARR for your cash flow, don’t focus too much on revenue recognition. That of course has to be done (at least annually for smaller companies), and later you’ll start reporting a more extensive P&L. But when you’re small, lean and in hyper-growth, simplicity and focus matters more than a full blown P&L that nobody cares about.

Once the company matures and you can justify insourcing more functions and building out a finance team, start adding more complexity. At that point, spending more time on revenue recognition, accruals and accounting principles is going to make more sense. Just don’t invest here too early; keep narrowing down your focus to what really matters for the business until you can afford the overhead.

Yes, the P&L will matter - eventually

As your company scales, board, auditors and future investors/acquirers will care deeply about true & complete financial statements. But if you’re joining an early stage startup, be careful you don’t fall into the rabbit holes. Focus on the fundamentals; business drivers and cash, unit economics and growth. Everything else is noise at the early stage.

This post is a reflection on that skill. Not a guide or framework on “how to become an expert” - just what’s worked for me so far. I’ll go through how I approach new topics, how I absorb fast, and how I go from zero to useful in very little time.

And spoiler: it’s not discipline or some grand productivity system. It’s obsession. I get curious, I get obsessed, and then I go deep until I get it.

The ability to keep learning fast is probably the single biggest multiplier I’ve had in my career so far.

🔥 Start with obsession, not discipline

Once I become curious about something, it’s generally like an obsession kicks in and I start vacuuming knowledge. Very quickly I become “dangerous” on a topic: understand enough to ask the right questions and have above-average knowledge. Not an expert, by any means - and often making mistakes and being proved wrong. But I grasp the fundamentals quickly enough to build; and that’s the strongest skill you can have when you’re in startup/scale-up mode.

People often talk about discipline. Show up, train 10,000 hours, all the regular “10 steps to success” type of instagram inspiration. And while that’s probably true, it doesn’t work that way for me. I’m more driven by curiosity, and an obsession of understanding things. I have to understand something when it doesn’t make sense to me: it’s like an itch I can’t ignore.

If a Sales rep tells me a customer asked for something odd in a contract, my brain goes: why? Is it a local regulation? A tax rule we don’t know about? Something we should be aware of and adapt to? And before you know it, I’m deep into double-tax treaties and different interpretations of royalties and services leading to different applications of withholding tax.

But the most useful part of this skill is probably when starting a new role, or evaluating a new opportunity. First question I ask myself is: what’s the first principles here? What’s the direction required? Then I go looking for people who have done something similar, or had a similar journey; to go uncover all of the wisdom already built up.

📚 The learning stack: My approach

Here’s my approach, that has worked really well for me. Since leaving banking in 2020, I’ve been absorbing knowledge around how to scale companies. It started out very generally, and then in recent years my focus narrowed as I went down the path of becoming CFO of a B2B SaaS scale-up, which required more domain-specific knowledge.

🤔 It starts with an obsession of curiosity

For me, it started with this question: How do you actually scale a company?

The curiosity became my anchor, and it was the thread that kickstarted my entire career change. I’ve always enjoyed biographies, so I started reading books about journeys to build great companies and it just snowballed from there.

🦸 Find the experts

Find people who have done something similar and are sharing publicly. Then go down the rabbit hole of following them, but also consider who they follow and learn from. For me, it was people like Molly Graham (on building organisations), Dave Kellogg (on metrics and SaaS efficiency) and CJ Gustafson (on startup finance). And many of those came up, because I kept exploring and talking to people; reading articles and posts, networking with others asking them about their experiences and how they learned in their roles.

🧶 Pull the threads

One blog post leads to another. A podcast quote sends you into a rabbit hole. I started treating learning like research: dig, cross-reference, bookmark, repeat. I chased every thread until I understood the first principles behind it.

An added benefit? It gives you multiple views and angles. Bullets for when debating, and also different views - when building, there’s never just one correct answer. It’s always a balance of trade-offs and viewpoints depending on what you want to achieve.

🙋 Join the right communities

Glue Club was a game-changer for me. Suddenly I had access to other operators scaling fast, sharing real playbooks and experiences behind. I also joined Slack groups like CFO Connect, The SaaSiest Executive Network, and some smaller local CFO forums. Through these communities, I was able to expand my approach to problem-solving and checking with peers who had similar experiences.

Sometimes, I was dealing with problems specifically to our company; so I’d use my local CFO community, who also had been dealing with similar stakeholders and limitations.

Other times I was wrestling classic growth problems; those where it doesn’t matter whether you’re building in Europe or US, whether you’re B2C og B2B. For that type of problems, I leaned heavily on my international and broader networks, built through communities like the Glue Club.

🔂 Build a system for recalling information & repeating knowledge

I created a “Knowledge Library” in Notion where I saved down most things I read and found inspirational. Articles, blog posts, podcasts, etc. - it helped me stay a bit more organized.

Another helpful system for me is using Readwise. It was a game-changer especially when it comes to retaining knowledge from the books I read. I highlight phrases on my Kindle that I want to remember, and through Readwise I get 5 quotes each morning. It’s like that inspiration newsletter, curated with quotes I personally found inspirational.

🤖 What AI changed: Research assistant on steroids

Let’s be real: it’s 2025 and it’s hard to have any conversation without AI coming up. So let me just touch on what has changed as I’ve started adapting AI:

⚡ Turbocharged research: instead of getting stuck filtering through shitty Google results and unreadable lawyer- or tax-accountant-lingo, AI helps me extract and digest.

It’s not perfect. AI will hallucinate trying to give you an answer. And just like humans, I’ve noticed it too can interpret things wrong, or will skip things until you specifically ask in your prompt. I don’t trust it with the final answer before verifying; BUT, it turbocharges access and explains concepts in ways that I find helpful.

✍️ Writing! No, this post is not purely AI written (although I do think the GPT versions often ends up better 🤣). But for a long time I was struggling getting started - it took me almost a year from buying the domain name (the easy part!) to writing the first post here. Lots of ideas, but I got stuck with a blank page each time. AI prompting helps me structure, ideate and come up with the base. Then I keep expanding, iterating, re-writing and deleting. And the final post ends up being some weird mix of my inner voice and the AI’s way of writing.

On the flip side, it’s a fine balance. I’m starting to get tired of reading the same AI-generated posts and points everywhere; regurgitating best-practice with zero context, personality or actual lived experience. So I’m doubling down on being AI-enabled, but still giving you my raw, semi-unfiltered brain dumps of learnings.

🧑‍🏫 Reframing the output

The real flywheel comes once you get to test, practice and try out the things you learn. It sounds obvious but this point is actually hard. I read a lot, but experience just trumps a lot of it. The learning gives me the foundation, but it’s when I get to practice it becomes magic.

There’s lots of ways to reframe:

• Write internal documentation

• Summarize learnings and share with your team in Slack

• Build templates and tools

• Mentor others

• Discuss with peers and networking groups

When forced to explain and teach, you’re forced to rethink. I noticed that it really turbocharged my own learnings, when I had to explain to others. Whether it was taking time to sit down with the sales team and teaching them about VAT rules and how they apply, or having sessions with the finance team discussing different solutions - the mere process for reframing the learnings helped solidify them.

And yes, eventually you’ll probably want to start a Substack to share the learnings with even more people! ;)

⚡ TLDR: Learning speed is a real advantage for startup operators and CFOs

I’m definitely not the smartest person (in the room or in general 🤣); but I’m often the one who learns fastest. Learning speed is a multiplier - and fast learning is a skill.

Here’s what I would recommend:

• Get obsessed. The curiosity to really understand how the world works.

• Ask questions. To yourself, peers, networking groups.

• Steal from the best. There’s always someone who has done it before. Find them and learn from their journey.

• Surround yourself with experienced people. When I got my first CFO role, I went and talked to every other CFO that I could find.

• Use AI wisely. Learn how to work with it, but make damn sure you understand its limitation. (AI unfortunately breeds laziness which is a whole other topic)

What’s your learning stack - and how do you climb the learning curves when changing roles, pivoting or going into new fields?

📌 Bonus: My CFO learning stack

Here’s a list of resources that I used in my recent journey to CFO. It’s a curated list of the sources that have stuck with me, and been most helpful to me in my journey. Shout out to all the amazing people creating content and sharing knowledge.

📫 Newsletters for CFOs

Yes, these were also my inspiration to start writing this Substack!

• CJ Gustafson: Mostly Metrics

• Dave Kellog: Kellblog

• OnlyCFO

• SecretCFO

• Ben Murray aka. The SaaS CFO

💬 Communities for operators & CFOs

• The Glue Club

• CFO Connect

• The SaaSiest Community

• Startup CFO

📚 Books worth reading

• The Hard Thing About Hard Things

• The Great CEO Within

• High Growth Handbook

• No Rules Rules

• Working Backwards

As the first finance hire in an early-stage SaaS startup, one of the first metrics to check is how the company defines ARR: Annual Recurring Revenue. It’s the foundation for everything else you steer the company with (CAC ratios, burn ratios, etc.) and the first number investors will scrutinize. You’ll often discover that many companies actually report Committed ARR (CARR) instead of true ARR. So what’s the difference - and does it matter?

Short answer: yes, it matters a lot. Not just for cleaner spreadsheets, but for how to interpret your growth, investments and cash flow.

🚧 Note: there’s a lot of discussion around “is ARR dead” as a lot of AI solutions are moving towards usage/consumption and outcome based pricing. I won’t go into that discussion at this point, but be aware that this post is mainly for traditional subscription based SaaS companies.

🤔 First, consider what you use ARR for

Your ARR numbers (or MRR if you bill monthly) isn’t meant to impress - it’s mean to be a simple, reliable baseline for understanding your recurring revenue run-rate. When defined properly, it helps answer questions like:

• What is the true recurring cash flow of the business?

• Is the GTM investment paying off (LTV:CAC) and how long does it take to recover (CAC Payback)?

• Are we building an efficient sustainable business? (Net burn, ARR per FTE / $ payroll)

ARR is one of those few metrics that is both backwards-looking (confirms what we’ve sold & billed), and forward looking (implies how much cash we expect to generate).

CARR vs. ARR - timing matters, but so does discipline

It’s easy to confuse the two, especially as some definitions of CARR include future step-ups (could be multi-year contracts with incremental commitments).

In theory, the difference is relatively simple and should mostly be a matter of timing:

CARR = what you contractually closed, regardless of whether you’ve billed it yet

ARR = what’s actually live in the system and invoiced

My default is always to use ARR for core reporting - board decks, investor updates and QBRs. It’s a closer proxy to cash flow, which is what investors want to understand. They’ll also run their own due diligence to verify it bridges to your accounting revenue (GAAP/IFRS).

In addition, there’s been a lot of abuse of CARR (especially when companies just call it ARR) to overstate momentum and growth; think booking deals long before contracts start (3+ months out), or inflating commitments that never turn into cash (your customer might have signed a contract committing to incremental spend in year 2 and year 3 - but it’s so far out that it very well could change, and signed contracts are not a guarantee that a company will pay).

❓ So why use CARR?

When navigating high-growth environments, optimizing for immediate cash flow might not always be the right thing (bet you didn’t expect a CFO to say that!). But reasoning here is that you want to optimize parts of the organisation - mainly Sales and Marketing - for momentum.

CARR makes sense as an internal metric for Sales-led organisations, where the driver is closing the revenue. Your job as the finance lead then becomes even more important, because you need to monitor and track the CARR → ARR → Cash bridge closely, to ensure liquidity and cash flows during the scaling phase.

⚖️ Consistency is key - and always bridge to Cash & Revenue

Your definitions should always follow the logic of the business, and eventually bridge to cash flow and revenue. If you’re finding large gaps between CARR and ARR, you likely have some GTM challenges to solve (i.e. selling large future promises).

Likewise, if your actual ARR doesn’t bridge to your cash flow and revenue recognition, you’ll have a hard time using ARR as a metric to steer the business because you’re simply not optimizing for cash flow.

⚠️ A caution on recognizing discounts & step-ups

One classic trap is handling discounts and multi-year step-ups.

• Should you book the discounted first year, or the higher future renewal price as ARR?

• Do you include step-ups in years 2 and 3 of a multi-year contract if the customer commits, even though the ARR isn’t realized yet?

There’s no single right answer to this, but pick what best represents your true recurring cash flow and be transparent about it.

Examples of different discount recognition methodologies:

• In one case we had smaller ACVs and 95%+ GRR. Customers auto-renewed at list price with no pushback, and our one-time discounts represented < 5% of new ARR, so we opted for showing ARR including discounts, but then transparently showing them in the P&L.

• For another case the deals had larger ACVs and deep discounts to incentivize urgency in getting customers to sign up for a new product. Combined with the lack of renewal history, the choice here was to take a more conservative approach and only recognize ARR net of discounts; but then record the incremental ARR as NRR at renewal.

The key takeaway is to make a choice based on what you’re optimizing for, and how you’re planning to use your metrics to drive behaviour.

Example: Customer signs a 12-months contract on January 15th. The subscription starts on February 1st, and they pay for the full year up front. Your standard payment terms are net 30.

To incentivize them to sign, the Sales rep gives them a $20 discount the first year.

🎓 Takeaways on ARR

Remember, your job as a CFO is not to find the biggest number (though you might get some push from the CEO/Founders in that direction 🤣), it’s to find the right metric for the job.

Most often, that’s the metric closest to real, recurring cash flow - and you have to build trust around that, especially with your board and investors.

When in doubt, consider your audience:

• Sales need to measure momentum → CARR is fine, but keep it tight and avoid “promises”.

• Boards, lenders, and your future self care about what hits the bank → that’s where clean ARR is the best proxy for cash flow and revenue.

If they don’t align - fix the root cause, not just the slide.

👉 What’s your approach? Do you handle discounts or multi-year deals differently? Hit reply or comment, I’d love to hear how others keep ARR honest.

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My path has been all but direct, but today’s reflection is about how making some trade-offs significantly increased the velocity of my career, and my journey towards learning how to lead a company as CFO. In hindsight, the two sacrifices that catapulted my trajectory? (1) Going earlier-stage, and (2) sacrificing location (temporarily).

The cost of an operator’s education

When I left banking back in 2020, I was drawn to the idea of becoming “an operator” in a hyper-growth startup. I wanted to build, not just manage or contribute. Learn first hand how to really scale and create impact. So I started devouring podcasts, books, newsletters and anything I could get my hands on from experienced operators around the world.

But like most pivots, it was a humbling experience. 6 months with applications and interviews taught me some hard truths: everyone wanted “proven talent” for growth stage roles. But it was hard to find someone willing to take the risk unless you had on your CV that you’d done it before.

I realized that I had to go earlier-stage, even if that meant making sacrifices around compensation and risk of failure. And that’s how I ended up with my first role, a fuzzy title (Chief of Staff) with no clear job description at a pre-revenue Berlin-based startup.

It was a true operational crash course, where I built skills with hands-on leadership. But not the growth rocket I had imagined, and while I learned a lot, it was a few years with negative cash flow and a feeling of being “stuck”.

The small pond advantage

My real breakthrough came when I jumped into an even smaller pond. I hadn’t imagined moving back to Denmark - let alone a smaller city (Aarhus) - but it ended up being the accelerator to my career.

The jump proved a good match; I found an ambitious team of founders who had raised a Seed round and found traction in the market already. For them, my background was rare - mix of entrepreneurial and big corporate experience. And for me, it gave a chance to land a role with a scope that would be hard to get in larger cities with more developed startup/scaleup communities.

In the years that followed, I scaled with the company and had more learnings in a short amount of time than any textbook could have taught me. From building and leading multiple operational teams, to raising multiple rounds of financing and growing the company 10x, the journey has brought me so many learnings that have accelerated the speed of my career.

The lessons from the smaller pond

What swimming in a “smaller pond” really meant for me, was that I could accelerate my access to learnings and networks dramatically, getting “years of experience” in a very short timeframe. I got into local CFO and leadership networks, and got access to learn from really smart and experienced people - all while combining it with “hands-on practice” building as fast as I could.

But perhaps the biggest hack was leveraging my experiences, title and responsibilities to then get into more senior and larger networks. It allowed me to build a lot of creditability that would be harder to gain in the larger markets with a narrower role.

Small ponds doesn’t last (if your ambition is larger) - but they can significantly compress your learning, and grant opportunities that are harder to get in bigger places. The catch? Finding the balance between sacrifice, for how long to stay and how to give back. If you get it right, you’ll outgrow the pond quickly and can bring all that experience & knowledge on to the next and bigger pond.

What’s your smaller pond?

I’d love to hear stories from others, who have traded in or sacrificed “the big pond” with a smaller one. What was your experiences, and what trade-offs did you make to accelerate your career & learnings?

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