Matt Asay

Contributor

Matt Asay runs developer relations at MongoDB. Previously. Asay was a Principal at Amazon Web Services and Head of Developer Ecosystem for Adobe. Prior to Adobe, Asay held a range of roles at open source companies: VP of business development, marketing, and community at MongoDB; VP of business development at real-time analytics company Nodeable (acquired by Appcelerator); VP of business development and interim CEO at mobile HTML5 start-up Strobe (acquired by Facebook); COO at Canonical, the Ubuntu Linux company; and head of the Americas at Alfresco, a content management startup. Asay is an emeritus board member of the Open Source Initiative (OSI) and holds a J.D. from Stanford, where he focused on open source and other IP licensing issues.

AI hype isn’t helping anyone

Reining in the BS in AI

Reining in the BS in AI

Large language models trained on questionable stuff online will produce more of the same. Retrieval augmented generation is one way to get closer to truth.

GitHub’s all-in bet on AI may overlook Git

GitHub’s all-in bet on AI may overlook Git

Not everyone wants AI to do everything for them. Will the risk of losing transparency and visibility into code change how GitHub made collaborative coding so powerful?

Open source is still the future of enterprise IT

Open source is still the future of enterprise IT

Open source projects continue to point the way for enterprise infrastructure, with eBPF, Cilium, Tetragon, and OpenTelemetry playing major roles.

The clouds can’t afford to forget developers

The clouds can’t afford to forget developers

In the rush to AI, vendors should remember that developers have a lot of clout with IT spending. Helping developers will translate to growth at the bottom line.

What AI won’t replace in your programming

What AI won’t replace in your programming

Generative AI is great at handling tedium and finding errors, but the expertise and intuition of programmers will always be essential.

Making sure open source doesn’t fail AI

Making sure open source doesn’t fail AI

The lessons learned from cloud are spurring a proactive examination of what it means to be 'open source' in the rapidly evolving world of AI.

Learning from Let’s Encrypt’s 10 years of success

Learning from Let’s Encrypt’s 10 years of success

Yes, having the support of a foundation helps, but more important is a solid technological solution to a recognized problem.

Linux distros need to take more responsibility for security

Linux distros need to take more responsibility for security

Between the rapid release of open source software, and modern OSes preloaded with packages, enterprises are vulnerable to attacks they aren’t even aware of.

People and Python in AI

People and Python in AI

If you want to squeeze the most value from your data, teach your employees Python and Excel instead of specialized programming languages.

Testing the limits of generative AI

Testing the limits of generative AI

As part of the learning curve with AI and LLMs, experiment all you want, but take the results with some skepticism, especially if you’re using it to write your code.

A new way of thinking about open source sustainability

A new way of thinking about open source sustainability

Go beyond paying developers to maintain the software your business depends on. Pay the companies that pay the developers and watch the whole ecosystem thrive.

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