vas natarajan

partner @ Accel. board @ gamma, lovable, radar, ironclad, transcend, permitflow. formerly: frame (ADBE), spoke (OKTA), segment (TWLO), deepmap (NVDA)

[Casey Aylward @caseyaylward]

https://t.co/fk5GOhXkPy

[vas natarajan @vas]

Cloudflare x @voidzerodev!

Agents loop alongside AI to produce more and better software -- arguably the most important capability to emerge in the last few years. Vite is the build tool beneath it all. Big congrats to Evan and the team

In other news @caseyaylward @Accel is on a tear. I'm a very proud Indian uncle.

https://t.co/WJalzEp7eb

[vas natarajan @vas]

Two interesting and (converging?) paths in applied AI land.

1. Land with an AI-as-intelligence product that maps to use cases in deep knowledge work domains, where reasoning about primary sources can be challenging. Fast time-to-value, good ACVs. Rapid growth.

2. Decompose a business process and re-encode via AI. Grind through change management to automate workflow. Lots of multi-step processes and presuming there's low error tolerance, startups can differentiate on verifiable or traceable work. Not quite the growth rates of bucket 1, more "deliberate" growth -- but potentially long-term stickier.

Former are moving in the direction of the latter (whether explicitly or not) -- JVs, acquiring customers or building pseudo-BPOs. Latter are building the operational IP to help customers "get to outcomes".

Ultimate question is where equity value accrues. The pie chart near term may heavily favor type 1 companies. But may rotate over to type 2 in the medium-to-long term.

Fun reality is the pie itself appears so large that both can win. But the slices themselves are changing texture real-time.

[vas natarajan @vas]

@caseyaylward Even if you concede technical distinctiveness / superiority, still the ongoing ops question of getting the raw materials in place and sustaining those channels. Maybe not surprising - but just a different layer of risk we old SaaS peeps aren’t used to.

[vas natarajan @vas]

Decompose most AI infra startups and the moat resolves to supply-chain mastery — not just access to components, but combining or operating them. From a cold start that's a difficult layer to accurately underwrite. Pull the thread and diligence runs into fairly opaque corners of the market.

[vas natarajan @vas]

Watching the memory trade go parabolic -- curious how the market resolves some key questions. How does demand adjust to current lead times? What's the "phantom" backlog? To what extent is backlog serviced by cheaper substitutes if delivery slips?

Pushing delivery out a year or two isn't the issue -- it's the risk demand evaporates before it can be fulfilled.

Markets seem to be pricing near permanent, inelastic demand for high-bandwidth options. But memory has always been a cyclical semi.

[vas natarajan @vas]

Definitely a model in flux. Observed a few dynamics so far:

1. AI transformation of the target is harder than most financial sponsors care to admit. Transmuting ops logic into AI is cost-intensive with ongoing maintenance. Less challenging for engineering of course where the workflow maps more cleanly to AI and is verifiable (code has to compile). Ops involves more expertise and often-brittle chained prompts. The efficiency may (?) foot in the end but I’d guess most AI cost savings undershoot the analyst’s LBO model in the near term.

2. Downside to gross retention rates and new bookings. Combination of customers over-buying in the ‘21 period + chilling effect of “can AI do this for me over time?” Hard to underwrite especially if debt covenants tied to SaaS metrics.

3. Talent concept is spot on. Difficult to find great people willing to “reinvent” an older software name versus spending these transformative years at a lab or hyperscaler.

I’d guess more firms look inward versus net-new names. Recaps of known entities with baseline asset value i.e. data and a mission critical interface — and (importantly) maintain some founder DNA.

[vas natarajan @vas]

@Accel Lots of focus on AI building new software. Increasingly white-hot market is how AI operates atop or between existing software.

[vas natarajan @vas]

We see massive spend attached to modernizing/maintaining/migrating existing software -- an ideal problem for AI to reason about. Real value if you can help enterprises manage what they already have versus selling them on something new.

You'll see this more in the @Accel portfolio -- @nova_ai , @Code_Metal_AI , Agave and others.... startups that run toward domain-specific complexity to help customers traverse their sunk cost fallacy from prior builds.

[Ivan Zhou @ivzhou]

We @Accel are excited to have led the seed round in @getnova_ai, and deepen our partnership with @EmmaQian_, @samuely4ng, and @dr_zeier as they announce their $31.5M Series A (and $40M in total funding), led by our friends at @chemistry (@kshenster).

Nova is building the leading AI development platform that enables enterprises to generate and transform complex software using natural language - starting with SAP. Instead of writing code line by line, teams can describe problems, workflows, and business logic directly, and Nova instantly translates it into working implementations. This also means everybody on the team can now engage with code, from engineers to functional analysts, resulting in faster development cycles, lower costs, and a fundamentally more scalable approach to enterprise software adoption. We believe this is the beginning of a much larger shift. As AI moves deeper into the enterprise, the opportunity is not just to accelerate coding, but to redefine how business systems are built, customized, and maintained.

Hear more about the vision directly from @EmmaQian_ and @samuely4ng

[Ivan Zhou @ivzhou]

We @Accel are excited to be leading @RadixArk’s $100M seed round alongside our friends at @sparkcapital. It’s been a privilege to partner with @ying11231 and @BanghuaZ since inception and to support the incredible @lmsysorg community.

Intelligence is no longer the bottleneck! Developers are now constrained by their ability to control, adapt, and reliably serve a growing diversity of AI models across hardware, environments, and use cases at scale. This shift creates an opportunity to build new foundational infrastructure for training and inference.

RadixArk’s mission is to build that open infrastructure, and we’re excited to be their partners on the journey.

[Ceci Stallsmith @CeciStalls]

Lovable is in the Forbes AI 50 this year.

We’re honored by the recognition. It’s motivation to keep building.

Now, back to work.

[Fabian Hedin @FabianHedin]

Lovable is now the easiest place on the internet to create something and then make money from it.

It can cover any use case. For example you can create an ecommerce store selling physical products, or sell software with a subscription.

You can do this with an existing company, or fully seamlessly using a merchant of record setup, where all complexities such as global tax is handled for you.

[NASA @NASA]

Hello, Moon. It’s great to be back.

Here’s a taste of what the Artemis II astronauts photographed during their flight around the Moon. Check out more photos from the mission: https://t.co/rzM1P0QbOl

[vas natarajan @vas]

Huge congrats to the Astral team! What an incredible group of builders and humans bringing deep thought and care to the Python tooling world. @charliermarsh

And my partner @caseyaylward who saw it before anyone and led our Seed and Series A. “Python is the language of AI, and Astral can become a major Python company”.

[Accel @Accel]

@OpenAI announced today that it’s acquiring @astral_sh.

This is a testament to @charliermarsh and the entire Astral team’s craft, dedication, and skill for building tools that developers love.

Thank you to Charlie and to everyone at Astral for welcoming us as partners on this journey. We’re cheering you on in this next chapter.

Read more from @caseyaylward about what Astral has accomplished and where they’re headed next. ⬇️

https://t.co/fTsC3yYmv2

[vas natarajan @vas]

Team @GammaApp takes every step behind how a company creatively shares and compresses it ever-so-perfectly into their product.

When you stack together releases like this, you see a new default creative system being built before our eyes.

Think about where this all goes. And run, don't walk to our careers page, 🙏!

[Grant Lee @thisisgrantlee]

There's a hidden tax on every knowledge worker in the world, and nobody talks about it:

The design tax.

You're a strategist, a sales lead, a marketer. You were hired for what you know. But every meeting, every pitch, every proposal expects you to show up with something that looks like a designer made it.

I lived this. Before Gamma, I spent time in consulting and investment banking. I spent more hours formatting slides than the analysis that went into them.

When my cofounders and I started Gamma, we asked: what if you never had to be a designer in the first place?

Five years and nearly 100 million users later, we've refunded billions of hours of the design tax.

Today, we're eliminating it for good with our biggest launch ever.

Gamma Imagine — a powerful, AI-native visual creation tool directly in Gamma. Posters, logos, infographics, visuals from a single prompt. On brand, every time.

AI-Native Templates. Templates were supposed to save you from design work. Instead you spent the time filling them in. So we completely rebuilt the template experience. Modify a whole deck with a single prompt, with your brand and style intact every time.

Gamma Connectors. You're already thinking in ChatGPT and Claude. Now Gamma sits inside the most popular work apps in the world. No more context-switching.

You were hired for your ideas, not to resize text boxes. Let Gamma pay the design tax.

[vas natarajan @vas]

When every person at a company has an insanely high standard for themself, the standards for the company take care of themselves. Incredible people x right mission @Lovable

[TechCrunch @TechCrunch]

Lovable says it added $100M in revenue last month alone, with just 146 employees https://t.co/9OXwPdOa0L

[vas natarajan @vas]

@Niparko Fantastic Ian Malcolm quote.