Will AI Make Open Source Obsolete?
What happens to open source when software can be fully written by machines? A thought experiment.
AI is changing how we build software. With AI tools like GitHub Copilot or Cursor, coding has become faster, easier, and more accessible. These tools help generate boilerplate code, suggest fixes, write documentation, and even debug. According to GitHub, developers who use AI tools like Copilot are 55% faster in completing their tasks. But this is just the beginning.
If we assume that we will achieve artificial general intelligence (AGI), meaning automated systems can perform any intellectual task better than the average human being, an interesting question emerges: what happens to open source when software can be fully written by machines?
Will AI supercharge open source communities, enabling faster, more inclusive development and empowering contributors of all backgrounds? Or will open source become irrelevant, as AI generates software on demand, bypassing the need for reusable libraries and human collaboration?
I've been discussing this question a couple of times lately - with founders, developers, and investors. In this thought experiment, I describe two opposing scenarios I can imagine.
The Bear Case: AI Undermines Open Source
In the pessimistic scenario, AI - or better AGI - diminishes the role and relevance of open source communities.
As AI becomes capable of generating production-grade code on demand, developers no longer turn to shared libraries or community-maintained packages. Instead, they prompt an AI to generate a tailored solution instantly. Why contribute to a shared tool when you can generate a custom one in seconds?
Open source contributions decrease. Newcomers skip the learning process of reading and writing code, opting instead to interact with AI. Seasoned developers shift away from community work, experimenting with private AI agents instead. Community energy fades.
AI-generated code floods open source projects - poorly vetted, license-ambiguous, and insecure. Maintainers struggle to keep up. Reviewing machine-generated pull requests becomes a chore. Legal uncertainty grows. Is this AI-written code violating a license? Can we even verify where it came from?
Trust collapses. Some projects try to ban AI-generated contributions altogether, while others struggle to define policies. A handful of high-profile legal disputes or security breaches cause organizations to retreat from relying on open source.
Meanwhile, the best AI tools are locked behind proprietary APIs. AGI is controlled by a few major corporations. Open source developers no longer have access to the most powerful tools. Innovation consolidates in closed ecosystems.
The balance of power shifts. Open source no longer drives progress - it trails behind. Communities fracture or disappear. The ethos of sharing gives way to convenience and efficiency. Open source doesn’t vanish entirely, but it becomes niche - relevant in specific domains, no longer a mainstream force.
The Bull Case: AI Supercharges Open Source
In the optimistic scenario, AI becomes the biggest amplifier of the open source movement.
AI automates the tedious tasks: triaging bug reports, writing unit tests, updating dependencies, and refactoring code. Human contributors can now focus on architecture, innovation, and collaboration. Maintainers find their load lighter - AI assistants propose changes, summarize issues, and write documentation drafts. These intelligent agents don’t replace people; they enable them to do more impactful work.
Barriers to entry shrink dramatically. New developers can contribute confidently with AI guidance. Non-coders like scientists or designers can co-create with developers using natural language. Suddenly, anyone with an idea and an internet connection can meaningfully contribute to an open source project.
Open source becomes more diverse, more inclusive, and more productive. Contributor pools expand. Burnout drops. Innovation accelerates.
AGI, if open-sourced or governed collaboratively, levels the playing field. Every developer, team, or project - regardless of budget - can access top-tier development intelligence. Community-driven AGI projects become a reality. Developers build not just with AI but alongside AI, treating it as a collaborator in open ecosystems.
The nature of contribution evolves. We see new roles emerge: AI trainers, prompt engineers, and ethical reviewers. AI-generated contributions are flagged, reviewed, and curated like any other. Communities develop norms to guide quality and transparency.
Open source projects thrive as a result. Governments adopt open tools with confidence. Enterprises invest in community-driven alternatives. High-quality open source software powers health care, climate tech, education, and AI itself.
Open source enters a new golden age - one where human creativity, global collaboration, and machine intelligence push the boundaries of technology forward.
The Future Is Not Set
AI presents both a threat and an opportunity for open source.
The direction we take depends on the choices we make now: about access, governance, education, and community standards. AI could either deepen open collaboration or completely centralize software creation.
Naturally, I’m an optimist, and strongly believe in the resilience and power of open source. I think we already see indicators that the future could look more like my bull case:
Productivity is increasing: AI tools have demonstrably increased the productivity of open source projects by 6.5%, with individual efficiency rising by 5.5% and participation by 5.4%. [arXiv]
Barriers to entry are being lowered: According to Stack Overflow, 76% of developers are using AI tools, indicating a trend towards more accessible development processes. Additionally, millions of new developers are currently getting onboarded through tools like Lovable.
AI is getting commoditized: Open source is leading the way in AI, and we can witness intelligence becoming more accessible by the day. See my post about “The State of Open Source LLMs”.
It’s important to remember that the future isn’t set.
We have to build it.
And if we get it right, open source and AI together could unlock a new era of abundance.
New & Hot Open Source Projects 🔥
WhatsApp MCP Server: A Model Context Protocol (MCP) server for WhatsApp. Search you personal Whatsapp messages, search your contacts and send messages to either individuals or groups. GitHub
No Ghibli Chrome Extension: Tired of Ghibli style posts? This simple Chrome extension helps you identify and filter out Studio Ghibli-related content from X. GitHub
II-Researcher: A powerful deep search agent that uses BAML functions to perform intelligent web searches and generate comprehensive answers to questions. GitHub
Open Source Jobs 💼
🔥 Senior Software Engineer (remote) at Linux Foundation - This position is in my team! Join us and help building out the world’s best dataset for open source.
Developer Relations (Berlin/Freiburg, Germany) at Prior Labs, a startup building foundational models for data scientists - see 9 more open roles at Prior Labs
Product Manager, IRM (Remote, Sweden) at Grafana Labs, an open observability platform - see many more open roles at Grafana
Open Source Funding Rounds 💸
Wundergraph, an open source GraphQL federation, raised $7.5M from eBay and others. Link
Until next week,
Jonathan (@jonathimer)
Also last week lots of n8n funding