YC S22 startup instantly acquired by OpenAI to enhance AI agent infrastructure

OpenAI has made another big move!

Just now, Instant, a standout startup from YC S22, announced that its entire team is officially joining OpenAI.

About a week ago, Instant launched its 1.0 version, and the cloud hosting service will continue running until August 31. Tens of thousands of customers bid a heartfelt farewell to the platform.

But for OpenAI, the strategic intent behind this acquisition is clear: to add a "memory layer" to Agent.

This acquisition, though seemingly sudden, was actually foretold two years ago.

In 2024, the Instant team announced the completion of a $3.4 million seed funding round, with an impressive lineup of investors—truly a clash of titans:

Investors include Y Combinator and SV Angel, along with several prominent angel investors such as former Firebase CEO James Tamplin, Y Combinator co-founder and former president Paul Graham, OpenAI co-founder and president Greg Brockman, and former Google Chief Scientist Jeff Dean.

At the time, the world was still celebrating every minor update of GPT-4, but OpenAI co-founder Greg Brockman had already bet on AI infrastructure.

To understand why OpenAI is so eager for Instant, we first need to understand what Instant actually does.

Instant is the ultimate tool for building backend infrastructure for AI agents, offering a one-stop solution with database, authentication, real-time synchronization, and offline caching.

In the hardcore developer community, it’s been given a louder, more straightforward name: “Firebase for the AI era.”

Back then, Google acquired Firebase, instantly dominating the backend infrastructure for countless mobile apps, enabling frontend engineers to handle complex database reads, writes, and real-time synchronization with just a few lines of code.

Today, Instant is doing the exact same thing in the AI era—except now, the primary users are not human users, but AI agents.

In the field of AI coding, Instant has delivered an impressive "report card":

• GitHub stars: Just strongly surpassed the 10,000-star milestone;

• Developer base: Official data shows that over 17,000 registered developers worldwide have been served;

• Number of applications: Over 400,000 apps have been built on its platform;

• Trading volume: Over 2.5 billion transactions processed cumulatively.

This is an industrial-grade infrastructure that has been repeatedly validated in high-concurrency, high-load production environments.

OpenAI has the world’s most advanced AI models—why can’t it simply build its own database? Why spend so much money to acquire Instant?

Here lies a critical pain point in the current stage of AI agent development: persistent state management and real-time data consistency.

In simple terms: current AI suffers from severe "amnesia" and "concurrency syndrome."

Currently, the capabilities of AI agents are expanding at an incredible pace.

They are taking over your calendar, automatically coordinating meeting times with dozens of partners.

They can even automatically read issues on GitHub, write code, submit pull requests, and fix bugs on their own.

Platforms like EinsteinArena enable multiple agents to collaborate and compete on public problem sets. By mid-2026, agents had discovered at least 12 new state-of-the-art results surpassing human or prior AI performance, such as raising the lower bound of the 11-dimensional kissing number from 593 to 604.

But when developers deployed the Agent into production, they hit a data wall.

For example: Your agent schedules a meeting for 3 p.m., but your boss’s agent forcibly inserts another appointment, while you personally change the 3 p.m. slot to “break.”

Three operations on the same data, within the same millisecond. The backend can't handle it—the system crashes outright, data becomes corrupted, and schedules are completely ruined.

No matter how intelligent the large model is, it cannot resolve read-write conflicts at the underlying data level. This is purely an engineering issue.

A truly effective agent that can operate in the real world must possess robust "memory" and "multitasking collaboration" capabilities.

It must be able to read and write data in real time, handle massive concurrent operations, cache data during network outages or offline periods, and perfectly resolve merge conflicts the instant connectivity is restored using highly sophisticated algorithms such as CRDT.

And this is precisely the "dirty, tedious work" that the Instant team has been relentlessly focused on for the past four years.

They encapsulated highly complex backend challenges—such as real-time synchronization, conflict resolution, and offline-first functionality—into a "plug-and-play" SDK.

Now, any developer can enable their AI agent with flawless persistent memory and real-time collaboration capabilities by simply adding a few lines of code.

For OpenAI, this requires adding the most critical components to the Agent: the Memory Layer and the State Layer.

Whether it's Codex handling code, native agents in the GPT series, or future continuously running "long-horizon AI workflows," all require a rock-solid backend to persist their state.

OpenAI's acquisition is the final piece needed for agents to truly achieve fully autonomous operation.

The story of Instant began in 2021.

According to the official farewell letter, in 2021, the founding team shared a vision on their blog about "running a database in the browser."

The two core founders of Instant, Joe Averbukh and Stepan Parunashvili, were both senior/director engineers at Facebook and Airbnb.

During their time at Facebook, they witnessed firsthand how a graph-based database supporting complex permission expressions enabled tens of thousands of engineers to maintain an astonishing development speed within an extremely complex system.

Why not bring this experience to developers around the world?

Driven by this geeky fantasy, they founded Instant.

Their goal is extraordinarily ambitious: to create the successor to Firebase’s graph database. Retain Firebase’s addictive out-of-the-box experience, but replace the underlying architecture with a more powerful relational structure (based on AWS Aurora), and natively support “local-first” and “real-time collaboration.”

Initially, it was just a simple idea, but as they developed more and more of their own apps, they deeply realized that managing state, handling synchronization, and resolving data conflicts were a collective nightmare for developers.

In 2022, they joined the top incubator Y Combinator (YC S22), built their first prototype, and released "Version 0."

Turning a prototype into a production-grade product is a long journey.

Instant wrote in the official letter: This journey, though arduous, was filled with the unique romance and exhilaration of a true geek.

Later, to address technical challenges, several experts joined the team: Daniel Woelfel joined very early on and relentlessly tackled and resolved the most difficult synchronization conflicts; when it came to making the TypeScript SDK truly ergonomic and delightful for developers to use, Drew Harris joined the team and accomplished this feat.

(From right to left: Joe Averbukh, Stepan Parunashvili, Daniel Woelfel, Drew Harris)

Open-source contributors in the community, such as Mark Shlick, Nikita Prokopov, and Alex Reichert, have further fueled the momentum.

If you broaden your perspective beyond just the Instant case, you’ll see that by 2026, OpenAI had already entered a疯狂's "buying spree" mode.

Data doesn't lie. Since 2026, the number of M&A transactions involving OpenAI has approached last year's total.

Let’s take a look at what’s on OpenAI’s recent shopping list:

OpenAI bought them—all are companies building developer infrastructure, none are AI model companies!

This is a clear signal: OpenAI is completing an epic transformation—from a company that builds models to a company that builds platforms.

Ultraman knows better than anyone: selling just the engine won’t build an empire. True dominance can only be achieved by controlling the chassis, transmission, infotainment system—and even the entire highway.

Now, OpenAI is gradually buying back these "infrastructure" components piece by piece and putting them together.

Imagine a future scenario: when a developer wants to build an AI application, they open OpenAI Cloud and can not only access the most powerful large models, but also instantly generate an Agent database with Instant, enable A/B testing with Statsig at the click of a button, and deploy with Astral’s toolchain—all with a single click.

This is the "Apple ecosystem" of the AI era! This will be OpenAI's greatest moat.

Reference materials:

https://www.getadb.com/

https://x.com/instant_db/status/2091016138100740394?s=20

This article is from the WeChat public account "New Intelligence Yuan," authored by ASI Revelation, edited by David.