Founder, former Simployer CTO, and angel investor Peder Nordvaller on building &frankly, the emotional math of selling a startup, the 100x AI developer, and why tech leaders need to get their hands dirty.
Few tech leaders have navigated the space between deep, hands-on engineering and high-level corporate strategy quite like Peder Nordvaller. Starting his career tinkering with web services in his bedroom, Peder’s trajectory has been a continuous cycle of building from scratch, rising to the boardroom, and inevitably returning to the tech trenches.
Alongside co-founder Caroline Fjellner, he built the employee engagement platform &frankly- an early Luminar Ventures portfolio company- and successfully steered it through a strategic acquisition. That exit landed him in a massive CTO role at Simployer, managing over 100 people and a complex portfolio of software products. Now, driven by the unprecedented paradigm shift brought on by AI, Peder has handed over the reins to his successor, David Rejdemyhr, to get his hands dirty once again. We spoke with him about the reality of market timing, what makes a great angel investment, and why the real challenge with AI isn't the technology-it's the mindset.
You’ve described yourself as a tech nerd disguised in a suit doing digital strategy. How did that dynamic evolve in your career?
I’ve always felt pulled in varying directions. I started as a software developer, tinkering with my own hobby projects from my bedroom. As I became an engineer and eventually took on a consulting job, I was forced to expose that tech to larger organizations. I realized that while I have a savviness for technology, I can also manage people and present to boards.
As you advance in your career, organizations tend to treat you like a cork floating upward- you get dragged into leadership roles. You do more governance and make more PowerPoints, but eventually, doing PowerPoints just becomes too fluffy. My entire career has circled around this cycle: starting concretely, bubbling up to leadership, feeling disconnected from the actual building, and restarting. That’s exactly what is happening to me again right now with AI.
Looking back at the origins of &frankly, what did you get right from the very beginning?
Caroline and I started at the right end: the customer pain point. Too many founders in both startups and large corporations have an idea, spend a year researching and building it in-house, and only then try to see if the market actually wants it. The market always has the answer.
With &frankly, we wanted to build something we knew people would pay for based on the pain points we experienced ourselves working in larger companies. We didn’t build it with the primary intention of just "starting a startup" and raising money. We built a product, pushed it to the market early to validate the need, bootstrapped it with initial customer contracts, and only looked to scale when we saw the traction.
When you did decide to scale, you partnered with Luminar Ventures. Why were they the right fit?
Once we had traction, we quickly realized we weren't alone. Competitors were moving fast and raising capital. We met Luminar at the exact right moment. We had a validated product, but we needed both capital and scaling expertise.
Luminar was in the sweet spot for us. Other VCs were a bit later-stage and wanted us to immediately move to the US and scale aggressively, but we felt we needed to first validate our home market. Luminar was comfortable with our early stage, and they had a portfolio of companies in similar phases that we could learn from. And ultimately, it was a highly successful partnership. When we sold the company, it was a true win-win: everyone involved-our founders, Luminar, and the acquiring company-made good business out of it. No one sank money and had to sell at a discount, which isn't always the case when market dynamics shift.
Eventually, you made that pivotal decision to sell the company. How did you know it was the right time?
Selling what you’ve built is an incredibly heavy decision-both financially and emotionally. You are handing over the reins, the product, and your team to someone else.
But you have to be market-savvy. After COVID, the venture climate changed, and VCs became more hesitant to finance startups without clear profitability. Simultaneously, we saw massive consolidation happening in the HR tech space; larger vendors were bundling services. We were approached by Simployer, a growing Norwegian HR tech group backed by a PE firm, who were building a consolidated offering. If we had stuck our heads in the sand and tried to raise money to compete standalone, we might have burned the cash and succumbed to market pressure. Instead, we swallowed our pride and aligned with the market. Within Simployer's portfolio, our standalone offering eventually doubled to almost 60 million ARR and has grown even larger than that as part of a larger bundle.
That acquisition led to you becoming the CTO of Simployer, managing over 100 people. What are the pillars of designing a tech organization at that scale?
It requires completely different organizational models depending on the lifecycle of the applications. If you have a mature, stable product still serving thousands of customers, you shouldn't constantly modernize it-you contain it, maintain it with deep domain experts, and focus on stability.
Conversely, for greenfield development, you need high-velocity product engineers who are comfortable experimenting and changing requirements quickly. You also have to balance development capacity with the homogenization that comes from acquiring companies. When I stepped in, we had on-prem VMs, AWS, Azure, GCP-every tech stack imaginable. You have to rationalize that and move things to a unified cloud architecture to actually gain efficiency, but you have to do that while still executing on product roadmap - this is a tricky balance in larger, mature and heterogeneous environments (like those driven by M&A).
You recently stepped down from that CTO role to dive back into AI. What are you seeing on the ground that made you make that leap?
AI is changing the fundamentals of how we do software development. The spread in developer productivity is widening drastically. Previously, you might have had a 10x developer. Now, the gap is widening to where you have 1x developers and 100x developers.
The developers in my organization who dove head-first into AI are experiencing 10x to 50x productivity gains. They are building mind-blowing side projects and becoming extremely attractive to the market. But the laggards-the ones who don't want to change-have to be pushed. I felt I couldn't stay on the sidelines managing operations; there are so many inherent opportunities right now that I needed to get my hands dirty to understand what is truly possible.
How does that 100x productivity shift change the way we build companies?
Historically, we talked about the "two-pizza team." Now, that’s becoming a "one-pizza team." Ten people go down to five. And the skill sets are evolving rapidly. We are moving toward specification-driven development. If you can build a source of truth for what your application should do and define the guardrails, the AI will code it. It requires engineers who understand how to specify an application and define edge cases, rather than just knowing how to code it.
As you’ve moved into angel investing, what are your green and red flags when looking at a pitch?
To be a true angel investor, you must actively solicit a deal flow. If you are passive, you will only see two types of deals: the founders who couldn't find money anywhere else (a last resort), or those coming through strong, trusted personal relationships.
The biggest green flag is always market traction. If a founder hasn’t taken their product to the market because they are being too careful or precious with their idea, that’s a red flag. It shows how the team operates under pressure and hints that they might not be willing to be challenged by the market. The most successful investments I’ve made are in early-stage teams tackling a specific, painful problem where someone is already willing to pull out their credit card to solve it.
You mentioned that leaders often fail when implementing AI. Why is that?
A lot of leaders say, "Okay, we need to do AI! Everyone needs to do AI!" but they don't do anything with AI themselves. They’ve never configured anything in the cloud or truly tinkered with the tools. That is a massive red flag.
If you are a leader, you are supposed to show the way. If you don't actually understand what AI can accomplish hands-on, you won't get your organization to follow you. Getting your hands dirty builds incredible trust with your developers because they know you understand their everyday reality and are capable of challenging their technical decisions.
What is the most underappreciated opportunity in company building right now?
The competency shift. We are moving from executing workflows to instructing an AI to execute workflows. Everyone talks about "learning AI," but it isn’t just about learning how a new tool works-it is a completely different structural mindset.
You are potentially taking a five-person team and replacing it with one person who knows how to structure an AI output mechanism. No one is currently helping companies figure out how to recruit for this mindset, or how to shift their existing organizations toward it. Interestingly, I think highly structured, systems-thinking tech developers are going to be uniquely suited to cross over and run commercial operations-like customer support-simply because they know how to define the guardrails for agentic AI better than a traditional line manager. The companies that master this structural mindset shift first will be the ones that succeed.
When founders combine deep technical savviness with an unrelenting focus on market realities, the path to scale becomes much clearer. Peder’s journey highlights why remaining close to the product and the customer is a non-negotiable trait for modern tech leaders. Continue to follow the Angel Access interviews for more insights from operators and angels across the ecosystem.