Strategy & Portfolio
Technology Risk
The possibility that a company's core technology will fail or be overtaken.
Technology risk refers to the possibility that a startup's core technology will fail to perform as expected, prove impossible to scale, become obsolete, or be surpassed by a competing approach. It is one of the fundamental risk categories that venture investors evaluate during diligence, alongside market risk, execution risk, and business model risk.
Technology risk manifests in several forms. There is feasibility risk — the chance that the technology simply cannot be built as envisioned. There is scalability risk — the technology works in a lab or with a small user base but breaks down at scale. There is obsolescence risk — a new paradigm, platform shift, or breakthrough renders the existing approach irrelevant. And there is dependency risk — reliance on third-party APIs, platforms, or open-source projects that could change terms or disappear.
The level of acceptable technology risk varies by stage. At seed stage, investors expect significant technology risk and evaluate it through the lens of team capability and technical vision. By Series B, investors expect the core technology to be proven and are primarily evaluating scaling and integration risks.
Technology risk is particularly acute in deep tech, biotech, and frontier AI, where the gap between a working prototype and a commercially viable product can span years and hundreds of millions of dollars.
In Practice
Quantum Dynamics, a quantum computing startup, raised a $30M Series A based on a novel qubit architecture that showed promising results in laboratory conditions. Their technology risk was multifaceted: could they maintain qubit coherence at scale? Could they reduce error rates enough for commercial applications? Would a competing approach (such as topological qubits) leapfrog their method entirely?
Eighteen months later, a major research university published a paper demonstrating a fundamentally different approach that achieved similar results at a fraction of the cost. Quantum Dynamics found themselves facing obsolescence risk on top of their existing feasibility challenges. They pivoted to a hybrid approach, but the pivot cost them a year of progress and required a significant down round to fund the new direction.
Why It Matters
Technology risk is a first-order concern because it directly determines whether a startup's product can exist at all. Unlike market risk (which can be mitigated through positioning) or execution risk (which can be addressed with better hires), technology risk can be binary — the thing either works or it doesn't. This makes it both the most dangerous and the most rewarding type of risk to underwrite.
For founders, managing technology risk means being brutally honest about what is proven versus what is assumed. The most effective founders de-risk their technology incrementally, demonstrating feasibility milestones that progressively build investor confidence. For investors, properly evaluating technology risk — especially in deep tech — requires genuine technical expertise, which is why the best deep tech investors often have PhD-level backgrounds in relevant fields.
VC Beast Take
Technology risk is the one risk category that founders are most likely to dismiss and investors are most likely to misjudge. Founders tend to conflate 'technically possible' with 'technically feasible at scale and commercially viable cost,' which are very different things. A demo that works in controlled conditions is not the same as a product that performs reliably for thousands of paying customers.
The venture industry's relationship with technology risk has shifted dramatically. During the ZIRP era, investors became surprisingly tolerant of technology risk, funding moonshots with decades-long timelines. The correction has swung the pendulum hard: many investors now want technology risk fully de-risked before they'll write a check, which paradoxically makes it harder for genuinely breakthrough technologies to get funded. The best opportunities often live in the gap between what the market perceives as too risky and what is actually achievable — but evaluating that gap requires technical depth that most generalist investors lack.
Further Reading
How to Evaluate a Startup as an Angel Investor
A practical framework for assessing pre-seed and seed startups — covering team, market, traction, business model, and terms. Plus the red flags that experienced angels never ignore.
What Is a Venture Partner and What Do They Actually Do?
Part-time vs full-time, sourcing vs investing, carry allocation—demystifying one of the most misunderstood roles in venture capital and how to become one.
How VCs Evaluate Startups: Inside the Due Diligence Process
Market analysis, founder assessment, reference checks, financial modeling, IC memos—a detailed look at how venture capital firms actually decide which startups to fund.
How to Build a Pitch Deck VCs Actually Read
VCs spend 3 minutes on your deck. Most of that on two slides. Here's the 12-slide framework that gets meetings, what investors skip, and the storytelling mistakes that kill deals.
How to Break Into Venture Capital: A Realistic Guide
Forget the LinkedIn fantasy. Here are the actual paths people take to land VC roles—from operator-to-investor transitions to starting your own fund from scratch.
The Venture Capital Power Law Explained: Why Most Returns Come From a Few Deals
Understanding the power law that drives venture capital returns — why a small number of investments generate the vast majority of profits and what this means for founders and investors.
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