{"slug": "matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and", "title": "Matan Grinberg: Value accrual in tech is time-dependent, the US lacks frontier open models, and outsourcing AI development can enhance efficiency | 20VC", "summary": "Matan Grinberg, founder and CEO of Factory, said value accrual in tech is time-dependent and that the US lacks frontier open models, which he called embarrassing. He argued that outsourcing AI development can enhance efficiency for companies where AI is not a core competency.", "body_md": "# Matan Grinberg: Value accrual in tech is time-dependent, the US lacks frontier open models, and outsourcing AI development can enhance efficiency | 20VC\n\nAI's rapid evolution challenges businesses to balance cost-effective open-source models with expensive frontier solutions.\n\n## Key takeaways\n\n- Value accrual in tech is influenced by time, affecting market trends and dynamics.\n- The lack of frontier open models in the US tech landscape is seen as a significant gap.\n- AI tools promise productivity gains, but businesses need time to adjust resources.\n- Focusing on core competencies is crucial for effective resource allocation.\n- Organizations often become inefficient by focusing on intermediate metrics.\n- Many firms should consider outsourcing AI development if it’s not a core competency.\n- Value capture in tech fluctuates, with different players gaining at different times.\n- The pace of AI model development is accelerating, especially in open-source.\n- Open-source models offer a cost-effective alternative to frontier models.\n- Enterprises might reduce the use of frontier AI models due to cost and ROI concerns.\n- Strategic resource allocation should prioritize business outcomes over headcount.\n- The rapid release of AI models presents both opportunities and challenges for businesses.\n- Outsourcing non-core AI development can enhance efficiency and focus.\n- Understanding value accrual dynamics is key to navigating the tech ecosystem.\n- Balancing open-source and frontier models is essential for enterprise optimization.\n\n## Guest intro\n\nMatan Grinberg is the Founder and CEO of Factory, an AI research lab building autonomy for software engineering. He has raised more than $220 million for the company from investors including Sequoia, Khosla, NEA, Evantic, and 20VC, and previously studied physics before becoming a founder.\n\n## The time-dependent nature of value accrual in tech\n\n-\nValue accrual is a time-dependent phenomenon so many of the tasks that we’re doing we don’t need the very frontier to do it\n\n— Matan Grinberg\n\n- Different players capture value at different times, influencing competitive dynamics.\n- Understanding these dynamics is crucial for navigating the tech ecosystem.\n-\nThe reality is value accrual is a time-dependent phenomenon\n\n— Matan Grinberg\n\n- Value capture is not static; it shifts over time among different companies.\n- Companies need to adapt to these shifts to maintain competitive advantage.\n-\nIt’s maybe for this next year this person is who has the pricing power\n\n— Matan Grinberg\n\n- Recognizing the fluctuating nature of value capture can guide strategic decisions.\n\n## The US tech landscape and open models\n\n-\nIt’s pretty embarrassing that we don’t have frontier open models in the United States\n\n— Matan Grinberg\n\n- The US lags in developing frontier open models, highlighting a significant gap.\n- Open models are crucial for driving innovation and maintaining competitiveness.\n- The lack of open models may hinder the US’s ability to lead in tech innovation.\n- Addressing this gap could enhance the US’s position in the global tech landscape.\n-\nWe need to improve in open model development\n\n— Matan Grinberg\n\n- Developing open models can foster collaboration and accelerate tech advancements.\n- The current state of open models in the US reflects broader tech ecosystem challenges.\n\n## AI tools and productivity gains\n\n- AI tools promise significant productivity gains for businesses.\n-\nWe will see tremendous growth from these tools\n\n— Matan Grinberg\n\n- Businesses need time to adjust their resource allocation to leverage AI.\n- The integration of AI tools can transform business operations and efficiency.\n-\nA lot of businesses will have to ask do we want to solve more problems now\n\n— Matan Grinberg\n\n- Strategic resource allocation is essential to maximize AI’s potential.\n- The transition to AI-driven productivity requires careful planning and adaptation.\n- AI tools can enable businesses to solve problems more efficiently.\n\n## Strategic resource allocation and core competencies\n\n- Focusing on core competencies is crucial for effective resource allocation.\n-\nWhat is the core competency for our business\n\n— Matan Grinberg\n\n- Aligning resources with core competencies enhances business outcomes.\n- Organizations should prioritize business outcomes over increasing headcount.\n-\nHow do we allocate resources accordingly\n\n— Matan Grinberg\n\n- Strategic resource allocation can drive efficiency and competitiveness.\n- Companies need to shift focus from intermediate metrics to meaningful outcomes.\n-\nOrganizations got bloated by focusing on intermediate metrics\n\n— Matan Grinberg\n\n## Outsourcing AI development\n\n- Building AI technology is not a core competency for many firms.\n-\nJust because you can build a lot of these things does not mean you should\n\n— Matan Grinberg\n\n- Firms should consider outsourcing AI development if it’s not core to their business.\n- Outsourcing can enhance efficiency and allow firms to focus on core areas.\n-\nIf it’s not relevant to your core business, outsource it\n\n— Matan Grinberg\n\n- Strategic outsourcing can optimize resource allocation and business focus.\n- Understanding the challenges of AI development is crucial for strategic decisions.\n- Outsourcing non-core AI development can drive business success.\n\n## The pace of AI model development\n\n- The rate of model development is accelerating, especially in open-source.\n-\nEvery few days yes especially when we look at Chinese open source\n\n— Matan Grinberg\n\n- Rapid AI model releases present both opportunities and challenges for businesses.\n- The competitive landscape in AI model development is intensifying.\n-\nIt’s like three or four a week\n\n— Matan Grinberg\n\n- Businesses need to stay informed about the latest AI model developments.\n- The pace of development requires agile adaptation and strategic planning.\n- Understanding the implications of rapid model development is crucial for success.\n\n## The role of open-source models in enterprise\n\n- Open-source models serve as a counterbalance to frontier models.\n-\nIt’s a really important counterbalance\n\n— Matan Grinberg\n\n- Enterprises can optimize resource allocation by leveraging open-source models.\n- Open-source models offer cost-effective alternatives for many tasks.\n-\nWe can do it much faster much cheaper with these open models\n\n— Matan Grinberg\n\n- The rise of open-source models is reshaping enterprise AI strategies.\n- Balancing open-source and frontier models is key to enterprise success.\n- Enterprises need to evaluate the trade-offs between different AI models.\n\n## Short-term contraction in frontier AI model usage\n\n- Enterprises may experience a short-term contraction in frontier AI model usage.\n-\nWe might see a short-term contraction of usage of the very frontier\n\n— Matan Grinberg\n\n- Cost concerns and unclear ROI are driving this contraction.\n- Evaluating the financial implications of AI models is crucial for enterprises.\n- The contraction reflects broader trends in enterprise AI adoption.\n- Strategic evaluation of AI model usage can enhance business outcomes.\n- Understanding the reasons for contraction can guide future AI investments.\n- Enterprises need to balance cost and innovation in their AI strategies.\n\n**Disclosure:** This article was edited by Editorial Team. For more information on how we create and review content, see our\n\n[Editorial Policy](https://cryptobriefing.com/editorial-policy/).", "url": "https://wpnews.pro/news/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and", "canonical_source": "https://cryptobriefing.com/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-open-models-and-outsourcing-ai-development-can-enhance-efficiency-20vc/", "published_at": "2026-06-13 18:44:27+00:00", "updated_at": "2026-06-13 18:49:20.344246+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-research", "ai-startups", "ai-tools"], "entities": ["Matan Grinberg", "Factory", "Sequoia", "Khosla", "NEA", "Evantic", "20VC"], "alternates": {"html": "https://wpnews.pro/news/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and", "markdown": "https://wpnews.pro/news/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and.md", "text": "https://wpnews.pro/news/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and.txt", "jsonld": "https://wpnews.pro/news/matan-grinberg-value-accrual-in-tech-is-time-dependent-the-us-lacks-frontier-and.jsonld"}}