After Claude Code, what will be Anthropic's next hit product?

Video Title: Anthropic's hunt to find the next Claude Code

Video Creator: ACCESS Podcast

Compiled by: Peggy, BlockBeats

Editor's Note: As large language models continue to advance rapidly and AI coding tools become more widespread, industry discussions are shifting from "whether models can complete a task" to "how model capabilities can be organized into products, workflows, and business systems."

Over the past year, products like Claude Code, Codex, and Co-work have entered the domains of developers and knowledge workers. AI is no longer just a chatbot for answering questions; it is becoming a productive interface capable of calling tools, executing tasks, and verifying results. However, as the consensus that "agents will become the next software paradigm" solidifies, a more critical question emerges: who can first translate model capabilities into reusable, distributable, and scalable work systems?

This article is compiled from an interview with Mike Krieger on the ACCESS Podcast. Mike Krieger, co-founder of Instagram and currently Chief Product Officer at Anthropic, leads Anthropic Labs. His goal is to guide the team in exploring Anthropic's next frontier product directions beyond Claude Code.

Alex Heath (left) and Mike Krieger (right)

In this conversation, Mike Krieger doesn't just speculate on Anthropic's next product. Instead, he deconstructs AI product competition into a set of more fundamental structural issues: how model capabilities enter real workflows, how AI companies internally organize innovation, how platform companies manage boundaries with ecosystem clients, and where human judgment will be repositioned in the production chain as AI execution capabilities grow stronger.

First, the product paradigm is shifting from "chat" to "task." Previously, large models primarily existed as dialog boxes where users input prompts and models generate responses. Now, Claude Code, Co-work, and Claude Design represent a different product logic: enabling AI to work continuously towards a goal, calling tools, generating results, and performing verification along the way. This means the key for AI products is no longer just response quality, but task decomposition, contextual continuity, tool invocation, and result verification. Whoever can encapsulate these capabilities into a seamless workflow will be closer to the next productivity gateway.

Second, organizational methods are shifting from "large team planning" to "small team experimentation." Anthropic Labs operates more like a startup unit embedded within a large company: starting with two or three people, holding bi-weekly reviews, and using high-frequency feedback to decide whether to continue a project. In the past, innovation labs in large companies often suffered from long cycles, ambiguous accountability, and delayed "okay" projects. Now, models lower the cost of building, and what's truly scarce is judgment, taste, and decision-making speed. This means organizational efficiency in the AI era depends not just on engineering headcount, but on the ability to validate direction faster with smaller teams.

Third, the boundary between platform and application is being redrawn. The success of Claude Code means Anthropic is no longer just a model provider; it is beginning to define application forms itself. The controversy surrounding Claude Design and Figma shows that when model companies create their own applications, they inevitably touch upon the interests of their clients and ecosystem partners. Previously, foundational model companies primarily provided underlying capabilities, leaving vertical applications like Cursor and Figma to handle the user interface and scenario packaging. Now, model companies also need their own products to showcase an agent-first future. This means AI platform competition is not just an API race, but also a product paradigm race.

Fourth, the stronger AI gets, the more scarce human judgment becomes. Mike repeatedly emphasizes that Claude can write code faster, generate prototypes, and execute tasks, but it cannot replace the most difficult part of the process from 0 to 1: asking the right questions, understanding real users, defining the product's north star, and judging what is "right." In the past, execution capability was the main bottleneck for knowledge work. Now, execution is being accelerated by models, and human value is more concentrated on front-end judgment, creativity, relationship networks, and organizational ability. AI will not automatically eliminate difficult decisions; instead, it will amplify the effects of wrong directions faster.

If we distill this conversation into one judgment, it is this: After Claude Code, what Anthropic is searching for is not a single blockbuster product, but a methodology to transform model capabilities into a production system. In this sense, the subject of this article is no longer just Anthropic's next product roadmap, but a structural turning point for the entire AI industry moving from a "model race" to a "system race."

The following is the original content (edited for readability):

TL;DR

· AI product competition has shifted from "stronger models" to "how capabilities are implemented," essentially meaning large model companies are vying for control of the workflow gateway.

· The significance of Claude Code is not just about writing code; it proves that an agent can persistently execute tasks towards a clear goal, pushing AI from a chat tool to a production system.

· The core value of Anthropic Labs isn't how many products it releases, but in using small teams to quickly validate what capabilities the model should possess next.

· Co-work represents Anthropic's attempt to extend the Claude Code methodology to non-programmers, essentially abstracting "coding ability" into workflow automation skills for ordinary people.

· OpenAI Codex's pursuit means Claude's advantage is no longer just technical leadership; it depends on whether Anthropic can integrate Claude Code, Co-work, and Claude.ai into a unified experience.

· Model companies developing applications themselves will intensify boundary conflicts with clients, but this is also an inevitable path for them to define the next generation of AI product forms.

· The faster AI can execute, the more human value is concentrated on front-end judgment, product taste, and problem definition, because wrong directions will also be amplified faster by AI.

· The impact of AI on employment is not a problem a single company can solve; it will fundamentally force society to re-discuss skills retraining, distribution mechanisms, and irreplaceable human capabilities.

Full Content

Alex Heath (Host): After Claude Code, what will be Anthropic's next big product? On this week's show, we have Mike Krieger. He's the co-founder of Instagram and now leads the team working on "moonshot projects" inside Anthropic.

Mike Krieger (Chief Product Officer, Anthropic):

One of my darkest days at Anthropic was naming it 3.5 v2. I can explain how we ended up with that name.

Alex Heath: Mike and I recorded this conversation in person during Anthropic's recent Claude Code event in San Francisco. At that event, Anthropic announced a major new compute partnership with Elon Musk. So, you guys are going to space with Elon now?

Mike Krieger: Absolutely. Yes, we are looking for new, and perhaps unexpected, sources of compute.

Alex Heath: We talked about what Mike is working on now, the intense competition between Anthropic and OpenAI, and what Mike believes will continue to be important in human work, even as AI becomes more powerful.

This is Access.

Mike, great to see you here in San Francisco at the Claude Code event. I was just thinking back to our last conversation. At that time, you had just taken over Labs, but that was a few months ago, right?

Mike Krieger: Yes, almost four months now.

How Labs Operates: Bi-Weekly Pivots, Small Teams Validate Big Products

Alex Heath: Almost four months. I want to start here for people who don't know what Labs is. It's a pretty unique organizational structure. We talked about it a bit when I visited your office a few months ago. What exactly is Labs, and what is its mission within Anthropic?

Mike Krieger: Simply put, my understanding of Labs – the current version, which I'd call Labs v2 – we can talk about Labs v1 later, and what Labs v2 aims to do.

But I think Labs does two main things.

First, it bridges the gap between Claude's theoretical capabilities and its everyday user experience. Meaning, Claude can do many things in theory, but how do those abilities truly integrate into people's daily work and life? What products, prototypes, or projects do we need to create to demonstrate how to unlock more of that potential, and shrink this gap as much as possible?

Second, we act more like a "frontier scout," figuring out which direction the model needs to evolve to meet the needs of different users.

So, a successful Labs project isn't necessarily one that ships as a product. It could be a prototype. We build it and discover: the model isn't good enough yet to handle this task. Then we put it aside, re-evaluate when the next generation model comes out, or turn it into an evaluation benchmark for future model development, and keep iterating.

Therefore, unlike a product lab in a pure product company, where success might be measured by "did you ship a product," at Anthropic, Labs' value can also be measured in other ways: it can influence Anthropic's future direction.

Alex Heath: Labs has made some blockbusters, right? Claude Code is one, MCP is another. What else?

Mike Krieger: Agent Skills was another important project from Labs. Also, I can talk about a project that didn't ship but was very helpful for research: computer use, getting Claude to use a computer.

I joined Anthropic in May 2024. Next week will be my two-year anniversary, we call it "antiversary" internally.

Alex Heath: Is it anniversary?

Mike Krieger: It's antiversary. Everything at Anthropic has to tie back to "ant." I resisted at first. We don't say dogfood, we say antfood.

After I joined, we started building Labs. One of the very first projects proposed was: why not try to get Claude to use a computer?

Alex Heath: That's computer use.

Mike Krieger: Yes.

Alex Heath: What model era was that?

Mike Krieger: That was Claude Sonnet 3.5. That was also the first model I was involved in launching. I joined in the third week and was already working on that launch. We often joke that Anthropic doesn't have an onboarding program; it just throws a really hard project at you. And I was directly involved in the launch by my third week.

Sonnet 3.5 was a very interesting model because it was one of the first to truly unlock some coding scenarios. Not quite full agentic coding, but you could see the beginnings.

So, we took Sonnet 3.5 and built a computer use product around it. But it had many problems. It was too slow at using the computer, not accurate enough, its vision wasn't good enough. It would look at the screen, say "I need to click that button," and end up clicking somewhere else.

But building that "not quite usable" testing framework was incredibly helpful. Because later, when we got to Sonnet 3.5 v2 – we can discuss that naming later, it really was one of my darkest days at Anthropic – we could plug the new model into that framework and test it.

Then we tried 3.6, still not good enough, but a little better. Then came 3.7. I remember that day vividly. I was on a business trip in New York, visiting the New York team. Suddenly, someone messaged me: we think that thing Labs built, the computer use project that had been sitting for nine months, is showing real signs of life with Sonnet 3.7. We think it's time to make computer use a capability we can open up and discuss publicly.

That took about nine months. We tried plugging a new model into the same testing framework every few months. Even though Labs had put the project aside, it remained very useful as a test suite to track the evolution of the model's computer use ability.

Alex Heath: When you joined Anthropic, you were Chief Product Officer. I remember thinking: Mike Krieger, the Instagram co-founder, someone I associate very much with consumer products, why join an enterprise AI company?

Mike Krieger: Yeah.

Alex Heath: I think we talked about this then. It seemed like a very interesting choice. In hindsight, it was the right choice. The timing was also great, of course.

I'm curious, you joined as CPO, in charge of the whole product line. And "AI product" is a somewhat fuzzy concept that changes very fast. How did you transition to Labs about four or five months ago? I understand you're more of an IC now, an individual contributor? Do you still manage people?

Mike Krieger: I don't manage people now. We were just about to enter the performance review cycle.

Alex Heath: So this is what you wanted, right? to escape writing performance reviews?

Mike Krieger: Exactly. I opened the system to see who I needed to review, and found I only need to write a self-review and a review for my manager.

Alex Heath: That's it?

Mike Krieger: That's it.

Alex Heath: Now Claude writes all the performance reviews.

Mike Krieger: Claude does help write some reviews, which is useful. It doesn't write them entirely for you, but it helps you remember: what did I actually do in the last six months?

I think the company has gone through different stages, and my passion for different things has matched those stages differently.

When I joined, the entire product and engineering team was maybe 30 people, split roughly half and half. We had engineering teams working on research infrastructure, scalability, etc., but if you looked at people purely building the product, it was mainly Claude.ai and what we then called the API – it wasn't even called the Platform yet – maybe 30 or 35 people total, very, very small.

It still felt like an early-stage startup, with many things still being defined. What "this product even is" was far from settled. Claude.ai didn't have Projects or Artifacts. It was basically a list of conversations with Claude, barely any extra features.

So, joining Anthropic then felt like joining a startup finding its product-market fit. It already had tailwinds, of course.

Alex Heath: When you joined, the Claude 3 series was already out, right? Opus, Sonnet, Haiku.

Mike Krieger: Yes. That was the first time Anthropic had a model series that was at least near the frontier. There was so much product work to be done: what would this product become?

Although my background is more consumer, I was excited because, in the time between Instagram and Anthropic, I did a lot of investing with Kevin, the other Instagram co-founder. We had a whole set of investment themes. One was "the future of work" – how work would be done in the future.

Anthropic seemed very likely to unlock that theme: what happens when you have a very intelligent assistant to help you with your work? I didn't even foresee how disruptive this would become.

Alex Heath: You probably thought: this is a pretty interesting little AI company, maybe it can help me understand some investment themes.

Mike Krieger: Yeah, maybe help us understand some themes we were thinking about. But it actually changed far more than I anticipated.

That was Phase 1. The team was small, the projects were countable on one hand. Then we fast-forward to the end of last year. The product team was hundreds of people. We had a portfolio of projects. A lot of the work became deployment, understanding customer needs, customer-facing, management layers, and all the things that inevitably happen as a company grows.

I gradually realized that some people really enjoy that kind of work and are great at it. I have immense respect for them. But for me, I had a great coach who described this state as being in my "zone of competence" – things you're good at, you do well, you can handle, but it's not ultimately what ignites you, what drives you.

It's a very dangerous position to be in. You can stay there for a very long time and look competent, but it lacks the fire and energy you have at your best.

So, in Q4 last year, I started talking to Daniela about this. I said the company has grown. We've compressed a normal five-year growth process, even though it was only about two years.

Alex Heath: Yeah, I think you guys grew pretty well.

Mike Krieger: Yes, growth was okay. The team size and product portfolio expanded quickly. So I said, I think I want to build a new company.

Daniela asked: Is this because you want to leave Anthropic, or because you want to change what you do within the company? I said I really like the company. The people are great, I love the technology, the mission, etc.

And around that time, we were also restarting Labs. Labs v1 was too successful; all its projects had "graduated" and moved on, leaving no one behind. So, Labs was put aside.

So, we decided to restart Labs, and I returned to being a builder. Everyone I met, inside and outside of work, told me: "Mike, you look so happy."

Alex Heath: Some of your colleagues told me the same earlier today. They said Mike is in a great place, having a lot of fun.

Mike Krieger: Yes. I'm still my own harshest critic. So every day I think: how can I do better? What can we do? What can we build? What are we even validating?

So it's not an easy thing. But it does align much better with what truly drives me.

Alex Heath: I don't want to dwell on this too long,