Peter Wagner

@Gong_io is the template for what an enterprise AI application company should look like. Stunning performance gong.io/press/gong-gro…

Major step forward for enterprise agents!

@pinecone buckle up. this is a big deal

Something's coming. Launch week May 4.

It's been so fun to work on the ET30 research project these past 7 years, and see all the progress the ET30 companies have made since their initial inclusion in the list. So much long term value in this group!

@Wing_VC @Nasdaq This year's group of companies is especially strong. Lots of long term value in this class!

Congrats to the ET30 Class of 2026 who just rang the @Nasdaq Closing Bell. 🔔

Great time talking #ET30 on Substack Live with ⁦@EricNewcomer⁩

Fantastic set of companies on this year's list. Very revealing of what's going on today in enterprise AI, and what is coming next

@Wing_VC @EricNewcomer @NewcomerMedia Incredibly strong list this year!

The 2026 Enterprise Tech 30 is live! 🚀 60 companies shaping the future of enterprise. In partnership with @EricNewcomer at @NewcomerMedia See the full list: wing.vc/et30 #ET30

@eoghan Congrats on a great turnaround! But - "we are now on our way to being the fastest growing, large software company (per our knowledge), private or public, in the world." There are larger, faster growing software companies. I suspect you know this.

@Wing_VC Superb work! Those of you interested in this kind of ground truth analysis should also check out @Wing_VC's study of the State of AI in the Enterprise. Our research team gets to the heart of the matters that matter!

What do healthcare leaders actually expect from AI over the next decade? At Wing at JPM, we surveyed 100+ executives on everything from drug approvals to personalized care and system-wide access. Read the 'Healthcare’s 2026 Inflection Point: Predictions from Leaders at Wing at JPM' Survey from @sarachoi_ and @Satpathology wing.vc/content/health… #JPM26 #JPM2026

Incredible data from @Wing_VC's Healthcare Leadership network. Many of you are already familiar with the analysis we do with Wing's Enterprise Technology Leadership network. This is a related "vertical" project with the attendees of Wing's Healthcare Summit at JPM. Dig in!

@Wing_VC just released our State of AI in the Enterprise study, which taps the expertise of hundreds of C-level technology executives. Momentum is building: 56% of large enterprises are in production with AI agents. More insights here: wing.vc/content/the-st…

This is a big f*ing deal. First ever Gartner Magic Quadrant for Revenue AI. @Gong_io is the unquestioned leader. In the original 1851 America's Cup, a young officer told Queen Victoria "There is no second"; so it is in Revenue AI gong.io/resources/guid…

A big step forward in the world of GPU computational capacity. With the value and operational complexity of these resources, the @sfcompute model is an inevitability. Great to be working with you @evanjconrad and your elite team

@intology Amazing! huge step forward

Introducing Locus: the first AI system to outperform human experts at AI R&D Locus conducts research autonomously over multiple days and achieves superhuman results on RE-Bench given the same resources as humans, as well as SOTA performance on GPU kernel & ML engineering tasks. RE-Bench is a collection of several frontier AI research tasks that typically take human experts (e.g., top ML PhDs and frontier lab researchers) several days. By scaling experimentation to far longer time horizons than previous systems, Locus represents a step change in AI scientist capabilities. 🧵

When I worked in HPC we used to describe computational capacity in FLOPS. More recently that has shifted to GigaWatts. And now people talk about it in $AUM. I find this shifting vocabulary supremely interesting and quite telling of the underlying drivers and scarcities

@yishan I've observed the opposite amongst business applications. Reason being, success requires not only technology but also keen understanding of the business process and user that we are trying to enable/optimize/automate. Hard to "know it all"

My AI investment thesis is that every AI application startup is likely to be crushed by rapid expansion of the foundational model providers. App functionality will be added to the foundational models' offerings, because the big players aren't slow incumbents (it is wrong to apply the analogy of "fast startup, slow incumbent" here), they are just big. Far more so than with any other prior new technology, there is a massive and fast-moving wave that obsoletes every new app almost as fast as it can be invented. There is almost no time to build a company and scale it. There are two ways AI application startup founders can make money: - Make a flash-in-the-pan app that generates a ton of cash and bank the cash (my estimate is that you have about 12-18 months cashflow generation) - Make a good enough app that you get acquired by one of the big players for sufficient equity The situation is highly unstable - we don't know if it's going to crash or go to the moon but both scenarios make it very unlikely that any AI application startup will independently become a generational supercompany (baseline odds are low to begin with). The best odds are finding an application niche in a highly specialized field with extremely unique and specific data barriers, ideally ones relating to real atoms (hardware or world-related) data and not software/finance.

@bgurley massive admiration! congrats on a superb tour of duty

Masterful CEO run. World class.

@Wing_VC is thrilled to be working with @AmandaKahlow and @1Mind. I tried to team up with Amanda over a decade ago when 6sense was new. It's great to have the opportunity this time! 1mind.com/announcements

Simply fantastic to be working with @sunilpotti!