Inside GitHub: The $7.5B Company Still Runs on Rails and Believes Junior Engineers Beat AI Agents

GitHub CEO Thomas Dohmke reveals why the world's largest code hosting platform still operates primarily as a Ruby on Rails monolith, how they maintain remote-first culture within Microsoft, and why they're doubling down on hiring junior engineers despite industry AI fears. From bootstrapped startup handling 120,000 API requests per second to Microsoft subsidiary generating $2B+ revenue, GitHub's evolution challenges conventional wisdom about scaling, technology choices, and the future of software engineering in an AI-dominated world.

Key Takeaways

• GitHub remains primarily a Ruby on Rails monolith with 700 engineers contributing to it, challenging assumptions about when companies must adopt microservices architecture
• The company processes 10 billion API requests daily (120,000 per second) while maintaining remote-first culture that predates the pandemic by over a decade
• GitHub's "dark period" from 2015-2020 saw minimal feature releases due to scaling fears and cultural paralysis, despite having beloved brand recognition
• Copilot emerged from 2020 experiments with GPT-3, initially focusing on text-to-code completion rather than conversational coding or code explanation features
• Microsoft's $7.5B acquisition multiplied GitHub's revenue 10x from $200M to $2B+ run rate while maintaining platform independence and open source commitment
• Thomas advocates hiring junior engineers because they bring fresh AI-native perspectives rather than resistance to new tools and workflows
• GitHub's security-first culture treats every employee as part of the security team, enabling early detection of threats across their massive developer ecosystem

Timeline Overview

• 00:00–08:30 — Technical Architecture Deep Dive: Why GitHub maintains Rails monolith, hybrid cloud strategy, and managing 700 engineers in single codebase
• 08:30–15:45 — Remote-First Culture Evolution: How GitHub pioneered async work, uses GitHub for everything internally, and differs from Microsoft's email-heavy communication
• 15:45–23:20 — Internal Tools and Innovation: Historic passion projects like Haystack, GitHub.tv, and Halp that shaped internal culture before external focus
• 23:20–32:10 — Security Philosophy and Approach: "Security as priority zero" culture, 150-person security team, and early threat detection across developer ecosystem
• 32:10–38:40 — Junior Developer Hiring Strategy: Why GitHub actively hires early-career engineers despite AI tools, bringing fresh perspectives and Gen Alpha mindset
• 38:40–48:30 — GitHub's Origin Story and Early Growth: From 2007 git hosting to rapid adoption by Reddit, Yahoo, Twitter, and Facebook within first year
• 48:30–58:15 — Microsoft Acquisition Context: How 2018 deal aligned with Satya Nadella's cloud-first strategy and developer ecosystem investment needs
• 58:15–68:45 — The Dark Period (2015-2020): Why beloved platform stopped shipping features due to scaling anxiety and organizational culture challenges
• 68:45–78:20 — Copilot Development Journey: From August 2020 GPT-3 experiments to June 2021 public preview, beating ChatGPT launch by 18 months
• 78:20–85:30 — Open Source Strategy Evolution: Why GitHub open sourced Copilot extensions despite competitive advantages, following VS Code precedent

The Rails Monolith That Powers the World's Code

• GitHub operates primarily as a Ruby on Rails monolith with approximately 700 engineers contributing to the codebase at different times throughout the year, challenging industry assumptions about when scaling requires microservices architecture
• The platform has surpassed 2 million git commits into the monolith with tens of thousands of pull requests, demonstrating that monolithic architecture can scale to massive developer teams when properly managed
• Strategic architectural decisions favor team velocity over technical purity—when GitHub started with four founders, a single codebase enabled rapid movement and feature development without coordination overhead between services
• Newer components like Copilot API use Go for high-performance inference requirements, while GitHub Actions inherited .NET architecture from Azure DevOps acquisition, creating a hybrid technical ecosystem
• The company processes 10 billion API requests daily (120,000 per second average), ranging from simple repository listings to complex GraphQL queries that demonstrate Rails can handle massive scale with proper optimization
• Modern GitHub combines owned servers in commercial data centers with Azure cloud services, maintaining cost optimization lessons learned from bootstrapped early days while leveraging Microsoft's infrastructure for newer AI-powered features

Remote-First Culture That Predates the Pandemic

• GitHub pioneered remote-first development culture over a decade before COVID-19 by hiring passionate community members worldwide rather than focusing on geographic proximity to San Francisco headquarters
• The company operates with minimal email usage—Thomas receives dozens of Slack messages but only handful of emails on GitHub side, contrasting sharply with traditional Microsoft communication patterns
• All company functions use GitHub for work, not just engineering—HR, communications, finance, and legal teams maintain repositories, submit pull requests for policy changes, and publish announcements through GitHub Pages
• Internal communication follows open source collaboration patterns with asynchronous pull request workflows, public issue tracking, and transparent decision-making processes that mirror external developer experience
• Company announcements avoid traditional email blasts, instead publishing to internal GitHub Pages sites with Slack notifications, enabling threaded discussions and version-controlled communication history
• Global time zone coordination requires strategic meeting scheduling, with "Git Together" town halls rotating between APAC-friendly and US/Europe-friendly times to ensure inclusive participation across distributed workforce

The Security-First Philosophy That Detects Industry Threats

• GitHub maintains "security as priority zero" culture where every employee considers themselves part of the security team, institutionalized through training and decision-making processes across all functions
• The company employs approximately 150 security professionals across threat intelligence, vulnerability research, and AI security teams, representing roughly 10% of their engineering organization
• Holistic threat detection leverages Microsoft's global intelligence to identify suspicious patterns like individual developers accessing competing automotive company repositories, indicating potential security compromises
• GitHub's security lab actively hunts vulnerabilities using CodeQL query language, responsibly disclosing findings to open source maintainers before public vulnerability announcements
• Real-world threat detection enabled early warning systems for incidents like the 2022 Heroku breach, where GitHub identified suspicious patterns and alerted Heroku security teams before internal detection
• The platform blocks credential pushes and maintains secrets scanning across repositories, preventing accidental exposure of API keys, passwords, and other sensitive information through automated detection systems

Why GitHub Believes in Hiring Junior Engineers Over AI Agents

• GitHub actively recruits early-career developers through structured internship programs despite industry discussions about AI tools replacing junior-level work, believing fresh perspectives outweigh experience advantages
• Thomas argues younger engineers bring natural AI adoption mindset without "this is how we've always done it" resistance, making them more effective at integrating new tools into development workflows
• Junior developers contribute diverse backgrounds and energy from recent university experiences, often bringing latest academic learning and different problem-solving approaches to established engineering teams
• The company sees hiring balance between early-career and senior engineers as crucial for innovation, with younger team members questioning established practices and suggesting alternative approaches
• Internship programs serve dual purposes of bringing fresh ideas into GitHub while giving back to the educational community, creating future GitHub customers who understand modern development practices
• Rather than viewing AI as replacement for junior developers, GitHub positions AI tools as amplifiers that enable less experienced engineers to contribute more effectively to complex software systems

The Untold Story of GitHub's Five-Year Innovation Drought

• Between 2015-2020, GitHub struggled to ship major features despite having beloved brand recognition and passionate developer community, creating perception of stagnation during critical growth period
• The platform's success created paralysis where engineers feared breaking beloved tools, leading to internal "staff shipping" culture where features remained internal rather than reaching public users
• High user expectations amplified fear of shipping changes because passionate developers would loudly criticize modifications to familiar workflows, while satisfied users remained silent about improvements
• Leadership transition challenges during CEO search period combined with cultural issues around shipping anxiety created organizational dysfunction that prevented public feature releases
• Microsoft acquisition catalyzed cultural transformation with new leadership encouraging measured risk-taking and establishing processes for safely shipping changes to massive developer audience
• The period ended with private repositories becoming free in early 2019, GitHub Actions launching (after complete rebuild), and eventual Copilot development that restored GitHub's innovation reputation

Building Copilot Before the World Knew About ChatGPT

• GitHub began Copilot development in August 2020 following Kevin Scott and Sam Altman's Microsoft Build presentation about transformers, gaining early access to GPT-3 through OpenAI partnership
• The team initially explored three scenarios: text-to-code, code-to-text (description), and conversational coding, with only text-to-code completion working well enough for production release
• OpenAI fine-tuned a specialized "Codex" model for coding scenarios that could maintain syntax consistency across programming languages without built-in compiler validation
• Internal GitHub adoption reached 25% code generation in enabled files early on, climbing to 46% by early 2023 as the model improved and developers integrated it into workflows
• Public preview launched June 2021, growing to one million users within months and generating positive social media feedback from initially skeptical developers
• The product achieved general availability in June 2022 with individual pricing starting August 2022, beating ChatGPT's November 2022 launch by over a year in market

Microsoft's Strategic Vision for Developer Ecosystem Dominance

• The $7.5B GitHub acquisition aligned with Satya Nadella's cloud-first strategy and Microsoft's transformation from Windows-centric to multi-platform developer services company
• Microsoft's reputation had evolved significantly by 2018 through open source commitments like VS Code, .NET Core, and embracing competitor platforms rather than fighting them
• Three acquisition principles guided the deal: developers first, accelerate GitHub innovation, and eventually have GitHub accelerate Microsoft through revenue and product integration
• The acquisition enabled 10x revenue growth from $200M run rate in 2017 to over $2B today, while maintaining GitHub's independent brand and platform neutrality
• Microsoft provided infrastructure and AI capabilities through Azure AI Foundry for Copilot development and global cloud infrastructure for enterprise data residency requirements
• Integration follows successful precedents from LinkedIn and Minecraft acquisitions, maintaining separate brand identity while leveraging Microsoft's enterprise relationships and technical resources

Open Source Strategy in the Age of Commercial AI

• GitHub open sourced Copilot extensions following VS Code precedent despite competitive advantages, believing platform value lies in inference, security, and collaboration layers rather than client code
• The decision acknowledges that community members had already reverse-engineered the JavaScript-based VS Code extension, making the source code effectively available for learning and modification
• Open sourcing enables broader ecosystem integration allowing developers to embed Copilot functionality in custom tools, interview platforms, and educational environments beyond traditional IDEs
• Revenue protection comes through platform services—compute infrastructure, enterprise security controls, compliance features, and human-to-agent collaboration tools rather than client-side intellectual property
• The strategy reflects industry role reversal where Microsoft embraces open source principles while some startups fork open source projects into proprietary commercial offerings
• GitHub maintains Copilot extensions across multiple IDEs including Xcode, JetBrains family, and Eclipse, requiring open source approach to serve enterprise customers with diverse tooling requirements

The Future of Software Engineering in an AI-Powered World

• Thomas rejects "autonomous" AI terminology, arguing that current agents require human direction for task assignment and operate within constrained permissions rather than self-directed problem-solving
• AI agents excel at tasks developers dislike—writing test cases, documentation, security vulnerability detection, and pull request descriptions—while humans retain architectural and business logic responsibilities
• Engineering skills remain essential for complex system design requiring decomposition of large problems into smaller components, understanding of scalability patterns, and business requirement translation
• The role evolution resembles historical abstractions like compilers replacing assembly language—AI becomes another tool in the developer toolkit rather than a replacement for engineering thinking
• Confirmation bias reduction represents unexpected AI value where generated pull request descriptions can reveal unintended behavior changes that authors might miss in their own code reviews
• Future software engineers will direct multiple AI agents while maintaining responsibility for code quality, system architecture, and business problem solving rather than becoming obsolete or purely managerial

Common Questions

Q: Why does GitHub still use a Rails monolith instead of microservices?
A: With 700 engineers contributing, the monolith enables faster feature development and easier codebase learning, while newer high-performance components like Copilot API use specialized technologies like Go.

Q: How does GitHub maintain remote-first culture within Microsoft?
A: GitHub uses Slack-heavy async communication, GitHub workflows for all functions, and minimal email, contrasting with Microsoft's traditional email-centric approach while maintaining operational independence.

Q: Why did GitHub stop shipping features between 2015-2020?
A: Beloved brand status created shipping anxiety where engineers feared breaking popular tools, leading to internal-only feature releases and organizational paralysis during leadership transitions.

Q: How did GitHub build Copilot before ChatGPT launched?
A: Access to GPT-3 through Microsoft-OpenAI partnership in 2020 enabled experimentation with coding scenarios, focusing on text-to-code completion rather than conversational features.

Q: Will AI agents replace software engineers?
A: AI agents will handle tasks developers dislike while humans retain responsibility for system architecture, business logic, and complex problem decomposition that requires engineering judgment.

GitHub's journey from bootstrapped startup to Microsoft subsidiary demonstrates that successful scaling depends more on cultural decisions and strategic focus than pure technical architecture choices. Thomas Dohmke's leadership philosophy embraces both the platform's open source roots and its commercial responsibilities, creating an environment where 120,000 API requests per second coexist with a Rails monolith, where junior engineers work alongside AI agents, and where a $2B+ revenue business maintains the collaborative spirit that originally attracted developers to git hosting. The company's evolution reveals that sustainable growth requires balancing innovation with stability, technical debt with feature velocity, and commercial success with community values—lessons that extend far beyond GitHub's specific circumstances to any technology company navigating rapid change.

Practical Implications

• Consider monolithic architectures for early-stage and mid-stage companies where team coordination overhead outweighs technical scaling benefits, following GitHub's successful model
• Implement security-first culture where every team member takes ownership of threat detection rather than delegating responsibility to dedicated security teams
• Hire junior engineers strategically for fresh perspectives on AI tool adoption and modern development practices rather than avoiding early-career talent due to automation fears
• Design remote-first communication systems using async workflows and version-controlled processes rather than defaulting to email and synchronous meetings
• Plan AI agent integration as developer productivity amplifiers for mundane tasks while maintaining human responsibility for architecture and business logic decisions
• Open source client-side code strategically while protecting platform value through infrastructure, security, and collaboration services rather than proprietary user interfaces
• Invest in internal tooling and developer experience improvements that enable confident shipping at scale rather than allowing beloved products to create innovation paralysis
• Balance technical debt management with feature velocity by making incremental architectural improvements rather than requiring complete rewrites for scaling challenges