Reflections of a founder/operator turned venture capitalist (VC)
The hardest part about moving from Latin-based languages to a language like Mandarin is understanding that meaning lives in the spaces between sounds. It’s not lost on me that memorising thousands of characters is a hard thing to do. But recognising the rise and fall of tones or the subtle shifts of pitch that can transform a single syllable into entirely different worlds is much more difficult. A native English speaker must first unlearn the certainty that meaning is fixed to words themselves.
In Mandarin, context transforms everything. The same syllable can mean mother or horse depending on tone.
This truth revealed itself to me in an unexpected way. When I joined Blackbird (Australia and New Zealand’s largest venture capital fund by AUM) last year, I realised that reading startups through VC-coloured glasses requires this same tonal flexibility.
In 12 months, I’ve met ~200 founders, sourced my first investment, run point on others, upped the cadence of Foundry (our frontier tech program), and reset my priors on what actually predicts outlier companies in Australia and New Zealand.
Before this, I was on the other side: founder, operator, with a detour through biomedical research. I’ve written this because people often ask what “moving to the dark side” felt like.
The short answer is that the economics of conviction are different on this side of the table. And, like tonal languages, the same startup metrics I obsessed over as a founder carry completely different weight.
As a founder I worshipped specific product and commercial milestones but in venture, I underwrite risk retired in sequence. The shape I’m usually looking for is interest → paid pilot with clear success metrics → production with renewals baked in → a process that hits yield and cost targets. To get to this point, the founder has successfully named the known unknowns, fenced the unknown unknowns off the critical path and turned an earned insight into a product on the tight cash and calendar they have.
Technical milestones still do matter but as inflection points in a larger story. A breakthrough in protein folding prediction isn’t valuable for clever modelling but because it makes in silico the default and compresses drug discovery cycles. A first-of-its-kind quantum algorithm isn’t interesting because it’s novel but because it accelerates the pathway to fault tolerant quantum computing.
Ultimately, the metrics haven’t changed but their meaning has shifted entirely. Same syllables, different tone, carrying an entirely new world of possibility.
Here’s what I know now that I wish I knew as a founder.
Narrative is an operating system
An exceptional business and technology can’t outrun poor communication or lousy storytelling. At seed you are selling a theory of inevitability. Story is how you allocate scarce external resources: talent, customers, and investors. If you don’t set the frame, the market will improvise a smaller one for you. Great technical teams often overlook this and ship truth in the footnotes. I’ve been guilty of it too but the reality is the world doesn’t read footnotes. My fastest predictor of downstream momentum is a two-sentence test: (1) what changes for the user or market? (2) how big is that delta? Clarity on these things reduces friction everywhere, whether it’s in recruiting, sales or follow-on capital. Lousy storytelling is a tax on all of it.
Ambition is efficiency, not bravado
A common misconception is that ambition is something you start with. More often than not, it’s something you grow into; a reaction to the first proof that what you’re building might matter more than you originally thought. Niki, co-founder of Blackbird, has long written about ambition as a magnet for people, capital and belief towards genuinely important problems, which I agree with. After a year at Blackbird, I’ve come to believe that it is also an efficiency. The personal effort required to build a timid or towering company are the same. But big ambitions make each unit of effort travel further. A-players self-select into consequential work and fewer hiring conversations lead to a higher hit rate for talent. Bold ambitions provoke sharper, faster signals from customers, partners and regulators ultimately accelerating the learning loop of the team. The same pitch prep for capital, distribution or data access unlock larger and earlier commitments. Larger visions intersect more actors, from media, ecosystem champions or standards bodies, increasing the surface area for luck to strike serendipitiously and without extra outreach. Ambition turns identical effort into non-linear results.
Look for off-the-charts learning rates
Learning velocity is an underrated signal of founder success. After 200 founder conversations, I’ve noticed that raw technical talent is table stakes. What separates exceptional teams is their ability to evolve at the speed of capricious market feedback. I watched one founder rise to every challenge we set her. Each conversation became a provocation to get clearer on her ambition. Where other founders would nod and schedule follow-ups, she made leaps between our meetings. Product pivots happened in weeks, not quarters. She treated market hypotheses with the same rigour as technical experiments. The strongest founders are aggressive learners who ship to learn, not just to prove.
Choose good quests
The most dangerous trap for founders (especially deep tech founders) is the siren sound of interesting problems. Like ancient mariners drawn to beautiful melodies, brilliant minds are naturally pulled towards elegant technical challenges or hard research problems. But I’ve watched countless founders pour years into perfecting solutions, only to discover their assumed market was a mirage. The hard truth I’ve learned from the other side of the table is that technical difficulty and market value rarely correlate. The best founders I meet choose valuable hard problems. I wish I had known this test when I was a founder but ask yourself, if you remove all technical constraints tomorrow, would customers still deeply care about your solution? Would it fundamentally change how they work, live or create value? The most compelling pitches marry urgent market needs that feel inevitable once you hear them.