Earlier this year, I had a noble idea.
For my job, I have to remember a lot of AI companies, so I thought I’d draw up a competition map for my desk. I’d divvy a sheet of paper into columns and list major companies based on which part of the AI supply chain they’re in.
There were the labs — OpenAI, Anthropic, Google DeepMind, etc. — that are making models and chatbots. There were the AI coding platforms — Cursor, Cognition, and Replit among them — that build coding assistants powered by those models. Then, there were startups building hyper-specific applications: agents that live in your email, help you execute a marketing strategy, or automate boring tasks like payroll.
I realized that the map would get messy, fast, because AI companies are ruthlessly invading each other’s turf.
Ever-increasing valuations mean companies need to find new sources of revenue. Becoming a full-stack AI company is especially important for revenue when models are commoditizing fast and big-ticket IPOs loom. Here’s how the landscape is evolving, way too fast for my paper map:
More vibe coders
Companies that start with a narrow AI capability — frontier models, AI agents, vibe-coding tools — are quickly expanding into one or more of those other areas.
Last year, Anthropic and OpenAI launched Claude Code and Codex, AI coding platforms that rival Cursor and Cognition. Now, per user screenshots on X — Anthropic won’t confirm it — the company may be working on an app builder for non-techies, putting it squarely in competition with vibe-coding stars Lovable, Replit, and Emergent.
SoftBank and Lightspeed-backed Emergent, for one, says it saw Anthropic coming.
“It’s not a surprise. We’ve been anticipating this for a while and sort of internally thinking and preparing about it,” CEO Mukund Jha told me in an April interview.
Anthropic’s entry into the vibe-coding market is not game over for the year-old startup, he said.
“Coding is relatively like 20%-30% of the work. The hard work is actually taking the application to the last mile,” Jha said.
He added that building secure and production-grade apps, especially for non-technical users, is a tough problem, one that might not be solved by companies that may be “spread thin.”
Claw rush
In the AI turf war, OpenAI is making agentic moves.
In February, the lab announced it was hiring Peter Steinberger, the creator of OpenClaw, an AI assistant builder that skyrocketed in popularity earlier this year.
The move added OpenAI to the list of companies building in the agentic space, such as former Meta tech chief Bret Taylor’s Sierra and Salesforce’s AI agent platform Agentforce. Now, Codex has evolved from a coding assistant to a virtual AI agent that can parse and reply to emails, manage files, and schedule meetings.
Smaller players are excited about this space, too. Last month, Emergent, which started as a vibe-coding platform, expanded into the personal agent space.
Other examples of the growing overlap include Anthropic entering the design market and graphic design giant Canva entering the broader generative AI and productivity suite business.
‘Google wanted to touch everything’
If it sounds like you’ve heard this story before, you have. But instead of OpenAI, Anthropic, and Lovable, the characters were Google, Amazon, and Microsoft.
Michiel Kotting, a partner at European venture firm Northzone, said that there was a time when the FAANG companies were dipping their fingers in all the pies.
Kotting, who cofounded e-commerce platform Shopping.com, said that Google used to be a big source of anxiety.
“I remember 25 years ago when I was building my first company, Google wanted to touch everything,” he told Business Insider in April. “For us at Shopping.com, we had Google launch Froogle, which was exactly what we were doing. And we’re like, “Oh, we’re dead.”
He added: “But then it turned out, it was a side project. They made so much money on their core business, so how hard would they go after it? Well, the answer is they didn’t.”
Tom Sheridan, a vice president at early Lovable investor RTP Global, agreed that a so-called “super app” — one app to rule them all — is unlikely.
“Super app talk is mostly noise that’s going to get resolved by the IPO calendar. Right now we’re seeing the foundational model players in the throes of a game of P&L chicken,” he said. “Once these companies go public, cash burn stops being free and shipping into categories where you’re good-but-not-best stops making sense.”
The “Google Graveyard,” an unofficial online list, tracks 305 projects sunsetted by the search giant over the years.
Apple, too, is famous for “Sherlocking” — introducing a new feature that makes a third-party tool irrelevant — but they don’t always stick around. In 2023, Apple launched Pay Later, a rival to Klarna and Affirm. It discontinued it in 2024.
Kotting said that we may see the same happen with OpenAI and Anthropic, companies feared by founders for the day they might ship an application startups have been working on for months.
It may be more worthwhile for Anthropic to continue building better models so it can charge more for its core service, he said. But if Chinese players or other labs become equally good and models turn into a commodity, Anthropic may go harder on these services.
Besides getting “Sherlocked,” startups face another big risk: dependency.
Startups are building billion-dollar businesses on top of APIs controlled by companies that may eventually compete with them. For example, Cursor depends on Anthropic models to power its features, but the two also compete as coding assistant providers.
Short-term win for customers
More players doling out more freebies is a win for individual builders and small businesses — but only in the short term, said Sheridan.
“Foundation model companies can ship a passable version of almost anything, but if the bundled tool isn’t as good as the specialist tool I already use, I revert back in a single session,” the VC said. “Product sprawl in search of retention bumps risks worsening UX and users know it.”
Big labs like OpenAI and Google sprawling in every direction also means that companies like Reddit or LinkedIn, which host tons of data, shutting out scrapers. That’s bad news for small startups like sales tech tools or meeting summarizers kept from the data they want to build their services.
These changes bring an opportunity for founders who know what users want out of their data.
“Today’s crop of foundational models can see meeting transcripts shared for summarization, but they don’t know which folders they should be filed under, what a team actually cares about or the required follow-up actions,” Sheridan said. “That’s the gap startups can build into.”
The market is also ripe for consolidation.
“I’d expect one of the major consumer AI breakouts to get acquired within the next 24 months, most likely by Google,” he said. “Google has the consumer ads business to absorb the cost and is structurally the most desperate for consumer AI talent.”
Sheridan said that the first company to be bought gets the best price.
“You don’t want to be the last consumer AI play standing when each major buyer probably only takes one shot,” he said.
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