🚀 How to plan your runway

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• Kevin Weil | Chief Product Officer, OpenAI

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• Mark Settle | 7X CIO (including Okta)

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💻 Demo your product to investors including:

• Barry Eggers | Founding Partner, Lightspeed Venture Partners

• David Jen | MD of Finance at X, Alphabet's Moonshot Factory 

• Joy Chen | Senior Advisor, GSV Ventures

• Nicole Baer | Chief Marketing Officer, Carta; Limited Partner, GTMfund

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3 tactics to plan your runway

🔎 Identify key uncertainties

• Focus on 6-10 uncertainties with the biggest business impact for you; everyone’s list will be different

• Cover both macroeconomic and assumptions you want to test around the market, customers, and other stakeholders 

• Example for a ridesharing platform in a high interest rate environment:

  • Will higher borrowing costs reduce consumers’ discretionary spending on ride-hailing versus cheaper alternatives like public transit?

  • Will drivers face tighter access to auto loans or higher financing costs, reducing supply on the platform?

  • Will corporate travel budgets shrink as companies cut costs, lowering premium rides demand?

  • Will higher rates erode driver and platform margins due to rising costs?

  • Will a tougher fundraising environment constrain expansion into adjacent bets (e.g. delivery, freight, autonomy)?

🪣 Bucket into scenarios and craft responses

• Create 3 or more scenarios(eg. worst case, middle case, best case) using combinations of outcomes from the list of uncertainties created

• Ensure each scenario includes a plausible combination of outcomes and captures a useful business case

• Outline how business strategy will change scenario-by-scenario:

  • Break down steps you will take in terms of product direction, revenue targets and headcount

  • Calculate the runway and burn rate you will see as a result

• Continued example for the ridesharing platform:

  

⏰ Set trigger points to signal scenarios

• Identify macro and internal signals that tell when each scenarios is happening

• Monitor signals -> determine the relevant scenario -> execute the corresponding responses

• Archive old uncertainties, scenarios and responses every 2-4 weeks

• Assess what's changed, whether scenarios are still realistic, whether to alter course of action, and rewrite new ones 

• Continued example for the ridesharing platform:

  

2 traps to avoid

🚨 Extending runway by cutting costs without a plan

• Undoing cuts and restarting product development or go-to-market might take longer than the additional runway from cutting costs

• ​​Budget cuts should lead to a clear path forward and should be more than just ‘X more months of burn’

🚨 Mistaking scenarios and increasing burn because revenue increased

• Revenue from the wrong customers = false traction and signal that lead you to the wrong scenario

• Be skeptical and check if customers use the product for the same core reason

• If usage isn’t aligned, pause spending; burning cash won’t fix the misalignment

1 tool to leverage

📖 Best practice on planning runway

• Typical pre-product-market-fit team size tends to be 5-9 full-time employees with the bulk being engineers

• Leverage this simple matrix from Sequoia to plan your scenarios

Bonus: 1 trend to spark startup ideas

📈   Manual fraud defense systems are costing financial institutions millions

• Financial crime compliance costs surged to $274B globally, and financial institutions are losing $98.5M annually to fraud, cyber threats, and operational inefficiencies 

• Every dollar lost to fraud now costs $5 in total impact (up 25% from $4 just four years ago)

• 44% of financial institutions rely primarily on manual fraud processes while only 20% are mostly automated 

• Manual reviews create bottlenecks that delay legitimate transactions, sour customer experiences, and leave critical alerts unresolved

• Opportunities to transform financial security:

  • Real-time fraud detection: Machine learning algorithms that analyze transaction patterns instantly, cutting false positives to manageable levels while catching sophisticated attacks that slip past rule-based systems

  • Automated compliance orchestration: AI-driven AML and KYC processes that eliminate manual reviews for cases, reducing compliance costs while improving detection accuracy through multi-layered analysis

  • Behavioral biometrics: Continuous authentication that tracks user patterns in real-time, stopping account takeovers before damage occurs while maintaining seamless customer experiences