GitHub wasn't built for this
It's a hard repo life
At its annual Universe ’26 conference in San Francisco this week, GitHub took to the question of the platform’s stability head-on.
The code-hosting company spent a significant part of the event’s keynote to talk about the investments it is making. That includes adding 4 million cores and 160 petabytes of storage, along with a full rearchitecting of its backend infrastructure.
But at a press conference and in interviews with The New Stack after the keynote, the leadership team of Jay Parikh, the executive VP of CoreAI at Microsoft who now leads GitHub, and GitHub COO Kyle Daigle also answered questions about what GitHub’s role is in this changing developer landscape — and how they feel about some of the competition that is now popping up in response to these changes.
It’s a timely question, since former GitHub CEO Thomas Dohmke launched a GitHub alternative just a few days before GitHub’s conference.
More fresh reads from TNS:
▹“Urgency is an inherently subjective call”: Anthropic tells TNS how it grades Claude Duet
▹Google just handed its rivals the keys to Android
▹GitHub saw 7.4B commits in September, adding 4M CPU cores and 160 PB of storage to keep up
Who's testing the code your AI agents write?
AI assistants have sped up how fast teams ship code, but test writing still moves at human speed, and every redesign breaks the suite. Join us for a free webinar on November 4 to learn:
- How an agent explores your app to find the user flows worth testing, including ones nobody listed
- How to generate tests from a plain-language prompt, no test code required
- How goal-based tests keep passing when workflows change
- How to test AI features that answer differently every time without flaky failures
TOP OF THE STACK
Mistral’s Large 4 open weights arrive with a 1-point coding lead over GLM-5.3: "There’s nothing you can’t do with this model that you can do with competitors."
The French AI company calls Le Chonk “the best open agentic coding model in the world" — and says it is cheaper than anyone else.
On Thursday, Mistral released the weights for its frontier open model, Mistral Large 4 (ML4), on Hugging Face. Made available for preview just three weeks ago, the French AI company says ML4 has significantly improved since then, thanks to reinforcement learning and testing with customers and partners....
WHAT ELSE IS NEW?
Up to 80% savings and increased reliability in 30 days. Guaranteed.
Most Kubernetes optimization tools stop at recommendations. StormForge by CloudBolt guarantees results.
- Up to 80% infrastructure savings
- Increase application reliability
- Try it risk free for 30 days
FLOW STATE
"Not that they will build models but take models and post-train and post-tune them the last 20% with their own data...In a way, they’re going to become mini frontier labs." -- Kong CEO
MFT admins can lose up to 160 hours a year chasing root causes after a failed transfer. On November 19, learn how AI-guided diagnostics, anomaly detection, and automated documentation can find the likely cause faster, live, using a real failure scenario.
Kubernetes won the orchestration wars, but dev and ops teams still pull in opposite directions. HPE's David Estes thinks AI may ease the strain.
ALSO FROM THE IMG FAMILY
More communities worth exploring
Community-powered role and skill-based roadmaps to guide your learning journey in tech.
Insights from the brightest minds in data science, machine learning and AI.
A modestly upbeat breakdown of what's happening with tech, business and power.
The New Stack is a media platform for the people who build and manage software the world relies on.
© 2026 The New Stack. All rights reserved.
The New Stack 1111 6th Ave Ste 550 PMB 50938 San Diego, CA 92101-5211