[Highlight] Grammarly's Evolution into an AI Agent Platform with Shishir Mehrotra

Grammarly didn't build the world's most successful grammar checker. According to Shishir Mehrotra, the company's former CEO who now runs Coda, Grammarly actually built something far more valuable: the first AI agent platform that works everywhere you do.

This reframe changes everything about how we should think about the current AI agent race. While everyone fixates on ChatGPT's chat interface or dreams of autonomous agents that work in isolation, Grammarly quietly solved the hardest technical problem in AI deployment: getting AI to work seamlessly across every application a person uses.

Mehrotra argues that "Grammarly built the first agent, the original agent" because of what the technology actually does under the hood. The company created a technical architecture that works in "about 500,000 or so different applications" where "Grammarly can read your screen, annotate it in a way that is unobtrusive to anything else you're doing, and it can make changes on your behalf anywhere." This isn't just grammar checking. It's a universal interface layer between humans and software that happens to start with writing assistance.

The distinction matters because most AI companies are building for narrow use cases or controlled environments. Grammarly solved cross-platform deployment at massive scale years before "AI agents" became Silicon Valley's obsession. Every web app, desktop app, and mobile app from Slack to Salesforce to obscure performance review tools can host Grammarly's intelligence without breaking existing workflows or requiring new user behaviors.

Now Mehrotra believes Grammarly should evolve this infrastructure into an open platform where anyone can build agents that deploy everywhere. "The idea is to open up the platform to anybody," he explains, comparing the opportunity to YouTube's creator economy. Instead of Google building every video, YouTube provides distribution and monetization tools for millions of creators. Grammarly could do the same for AI agents, offering universal deployment infrastructure while third parties build the intelligence.

This platform play makes sense when you map Mehrotra's framework for horizontal AI companies. He divides the space into three categories: assist, chat, and do. Chat companies like OpenAI focus on conversational interfaces where heavy users might interact "a dozen times in a day." Do companies build autonomous agents that work independently. But assist companies like Grammarly embed intelligence directly into existing workflows where people already spend their time.

The assist category has structural advantages that most investors miss. Chat requires users to context-switch away from their primary tasks. Autonomous agents require users to trust AI with unsupervised execution. Assist tools work within established patterns while gradually expanding their capabilities, creating stickier adoption curves and clearer value propositions.

Mehrotra tested this thesis in real-time during a conversation with Duolingo CEO Luis von Ahn, who initially dismissed agents as irrelevant to app businesses. "That's really cool, probably doesn't apply to us. We build apps. Somebody else will build agents," von Ahn said. But after an hour of brainstorming, they mapped three different agent concepts that could enhance Duolingo's core experience rather than competing with it.

The breakthrough insight is that successful AI agents won't replace existing software. They'll augment it invisibly. Mehrotra notes that Grammarly's grammar checking is "probably not the agent you started with" when imagining AI assistance, but "it turns out to be really, really valuable, especially when your grammar teacher can sit right next to you and help make sure you spell your company's name properly."

This suggests the current AI agent discourse misses the point entirely. The valuable agents won't be general-purpose assistants that handle email and calendar management from scratch. They'll be specialized intelligences that make existing tools slightly better in ways users barely notice until they're gone.

For builders, this means the platform opportunity isn't just about LLM capabilities or conversational interfaces. It's about deployment infrastructure that works everywhere users already spend time. Grammarly's technical moat comes from solving browser compatibility, mobile integration, enterprise security, and application-specific UI rendering across half a million different software environments.

The companies winning the next phase of AI won't necessarily have the best models. They'll have the best distribution and the lowest friction for both users and developers. Grammarly's evolution from grammar tool to agent platform represents a blueprint for how infrastructure companies can leverage existing user bases and technical capabilities to capture value in the AI stack.

Watch for established software companies with broad deployment capabilities to make similar pivots. The race isn't just about building smarter AI. It's about building AI that works everywhere people already are.