In 2024, code was the single most constrained resource for startups.
🧭 Coding capacity dictated how fast customers could be onboarded.
🧭 It determined how quickly problems could be resolved post-onboarding.
🧭 It controlled how fast channel partnerships and APIs could be rolled out.
🧭 Naturally, coding capacity also shaped burn rate, valuation, revenue generation, and profitability.
But now, that’s all changing.
With AI augmentation reshaping how startups build, the bottleneck is no longer coding capacity. The smartest founders are no longer limited by developer bandwidth alone—they are leveraging AI to multiply productivity, accelerate go-to-market strategies, and redefine what’s possible.
At Valor VC, we’re seeing firsthand how founders are navigating this shift.
Let’s start by getting to the root of your startup–cash flow–and see some of the new choices smart founders are making.
Venture rounds are stretching longer than ever. According to Carta’s latest data, the median time between Seed and Series A has hit 2.1 years, and Series A to B is trending toward 2.4 years.
That means the capital you raise today needs to last longer than founders planned for just a few years ago.
Burn rates are under the microscope, bridge rounds are expensive, and survival is about efficiency. So in this situation, are you managing cash flow, or is cash flow managing you?
Code was once the “constrained resource” for a startup that burned through cash reserves fast–but those days are over for those who can best utilize AI.
Now, it’s human ingenuity, design thinking, and AI as a domain expertise that is the scarce resource. This is good news for design forward, product obsessed, AI familiar teams who use AI every day in every way. By building with AI you can reduce burn, optimize operations, and extend your runway—without compromising growth.
A Founder’s Emerging Playbook for AI-Augmented Efficiency
Startups that integrate AI strategically are seeing a direct impact on burn rate without sacrificing momentum. Some of the highest-impact AI applications we’re seeing across our portfolio include:
✅ Automating customer interactions – AI chat and service tools cut response times and reduce headcount needs.
✅ Turbocharging support resolution – AI-assisted debugging, troubleshooting, and ticket management streamline engineering cycles.
✅ Onboarding at scale – AI-driven playbooks reduce human touchpoints and ramp up new customers faster.
✅ Accelerating product development – AI copilots allow leaner teams to ship code faster, replacing the need for extra junior engineers.
✅ Sharpening insights & strategy – AI-powered analytics crunch data at a fraction of the cost of a traditional research team.
The goal? AI doesn’t replace great teams—it unlocks their best work by shifting resources from repetitive tasks to high-value innovation. AI is not for developers–it is for every facet of your organization.
As CEO, you’ll need to set the tone and adopt the same mindset, starting with a strong eye to eye with your CTO.
The New CTO Mindset Shift: From Code to Resource Allocation
Jean Luc Van Hulst, operating partner at Valor and an experienced developer and AI architect, calls this the “Allocation Economy” shift—where startups move beyond “code as the scarce resource” and optimize intelligent resource allocation instead. (Read more about that here on his blog.)
What does that look like in practice?
🚀 Move beyond lines of code as a core metric. Measure impact in
- speed,
- problems-solved, and
- customers onboarded successfully.
🚀 Train teams in AI meta-skills. Strong product thinking, problem decomposition, and AI orchestration are more valuable than ever. In the “old startup world” of 2024, startups thought about hiring first, and then the tools to support those hires. When you’ve got the right people in your seats, set the expectation that they turn to AI first, then after AI is doing all it can, look for leading thinkers who can shape it tastefully, ethically and with even more intelligence to hire as you scale. Thinking about process, data moats, and advantaged access to information or APIs is the new supercode stack.
🚀 Dogfood your AI tools. The best teams don’t just build AI—they use it daily to ship faster and learn what actually works. People who use AI every day in several ways develop a sense about what it can handle and what it can’t that comes from experience–you need that on your team in every role.
🚀 Think like a product leader, not just an engineer. AI-first thinking isn’t about adding features; it’s about unlocking new business models with intelligence running in advantaged structures.
AI-First Teams Win in This Market
For years, startups treated things like headcount growth and lines of code as a success metric. We are seeing the smartest founders today are flipping the script—leaning into AI, extending runway, and out-executing the competition with fewer full-time hires. With venture timelines shifting, your best strategy is to plan for efficiency from Day 1. Start building like the next round isn’t guaranteed—because in this market, it isn’t. If you can build a more capital-efficient company that scales smarter you’re well on your way to building the company of your dreams–and that’s very likely to be a dream company for investors too.
Time to execute. 💡
-Lisa Calhoun