Deep tech startups are fundamentally different from typical software or consumer ventures. Their operational playbooks must account for scientific risk, long development cycles, regulatory hurdles, and capital intensity. While many operational “best practices” are borrowed from SaaS or consumer tech, most simply don’t translate to deep tech. Here’s a data-driven look at what works and what doesn’t across the critical operational pillars: GTM, hiring, finance, legal, and partnerships.
1. Go-to-Market (GTM): Beyond MVPs and Blitzscaling
What Doesn’t Work: The classic “iterate fast, launch MVP, pivot” approach is often incompatible with deep tech. As Celine Halioua, founder of Loyal, notes, “For Loyal, due to the extensive regulation, the final product, the drug is locked years before it launches. If the drug doesn’t work, there’s no iterating. If you want to modify the product, you need to restart the entire process over again”. In deep tech, product-market fit is not a quick feedback loop. What Works:
- Evidence-Driven Validation: Early validation comes from technical milestones, proof-of-concept pilots, and letters of intent (LOIs) from potential enterprise customers not just user signups.
- Milestone-Based GTM: Successful ventures use staged GTM strategies, aligning funding and hiring with technical de-risking. For example, in medical devices or advanced materials, pilot projects with strategic partners can validate both the tech and the market before a full-scale launch.
- Customer Co-Development: Engaging early adopters as co-development partners can secure both feedback and credibility.
2. Hiring: Domain Depth Over Generalist Agility
What Doesn’t Work: Hiring for “startup hustle” alone is insufficient. Deep tech requires domain expertise, not just drive. A study of successful deep tech teams found that 80% of founding teams included at least one PhD or equivalent technical expert. What Works:
- Cross-Disciplinary Teams: Teams that combine scientific, engineering, and commercial talent outperform those that are siloed. Patrick Griss, in his Deep Tech PlayBook, recommends structuring teams around four key workstreams: product management, product development, marketing/sales, and strategy.
- Board and Advisor Diversity: Building a board that spans domains science, business, regulatory helps anticipate blind spots and accelerates problem-solving.
3. Finance: Portfolio Thinking and Milestone-Based Funding
What Doesn’t Work: The “single bet” mentality placing all resources on one moonshot can be fatal. Deep tech’s inherent risk profile means many projects will fail, regardless of execution. What Works:
- Portfolio Approach: Successful founders, like those at Loyal, develop multiple products in parallel even with scarce resources. “We’d be dead today if we hadn’t,” says Halioua
- Milestone Funding: Investors and founders align capital deployment with technical and commercial milestones, reducing risk and increasing capital efficiency.
- Non-Dilutive Funding: Grants, government programs, and strategic partnerships are critical sources of early capital, especially before VC appetite kicks in.
4. Legal: IP as a Strategic Asset
What Doesn’t Work: Treating intellectual property (IP) as an afterthought can undermine a venture’s value and negotiating power. What Works:
- Early IP Strategy: Strong IP positions, patents, trade secrets, exclusive licenses are central to both valuation and investor interest. In negotiations, IP and LOIs can be leveraged to secure better terms and attract strategic investors.
- Regulatory Foresight: In sectors like biotech, medtech, and AI, regulatory pathways must be mapped from day one. Delays or missteps here can be existential.
5. Partnerships: From Validation to Scale
What Doesn’t Work: Transactional or opportunistic partnerships rarely deliver sustained value in deep tech. One-off pilots without strategic alignment often lead no where. What Works:
- Strategic Alignment: The most successful ventures secure anchor partners large corporates, research institutions, or government agencies that provide not just validation but also resources, credibility, and market access.
- Negotiation Playbook: Founders must master milestone-based, evidence-driven negotiation. “The difference between securing the right deal and getting stuck in the wrong one isn’t just about capital it’s about knowing how to play at the highest level,” notes The Scenarionist’s Deep Tech Negotiation Playbook.
What’s Different About Deep Tech Playbooks?
- Objective Truths: As Halioua puts it, “When you’re attempting something scientifically challenging, there’s an objective truth that’s already predetermined in the universe and it’s your job as a founder to figure out that truth as quickly as possible”.
- Business Readiness Levels: Patrick Griss’ framework assesses startups across four stages, Business Idea, Prototypes Tested, Ready to Launch, Ready to Scale each with distinct operational priorities.
- Redundancy and Resilience: Building in technical and business redundancies is not wasteful, it’s essential.
Operational excellence in early-stage deep tech is about systematic validation, cross-disciplinary teams, milestone-based execution, and strategic partnerships. What works in SaaS or consumer tech rarely translates directly. The best deep tech founders build playbooks that are as rigorous and evidence-driven as their science turning objective truths into operational advantage
References:
- MIT Sloan Management Review, "The Incumbent’s Deep Tech Strategy Playbook," 2023.
- First Round Review, "Building a Deep Tech Company? Most Startup Advice Doesn’t Apply,"2025.
- The Scenarionist, "The Deep Tech Negotiation Playbook," 2025.
- Startupticker.ch, "Book review: Deep Tech PlayBook by Patrick Griss," 2024.