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Anthropic’s Felix Rieseberg: Claude Cowork, Mythos, and the SaaS Extinction

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Anthropic’s Felix Rieseberg: Claude Cowork, Mythos, and the SaaS Extinction

The MAD Podcast with Matt Turck

Apr 10
The MAD Podcast with Matt Turck

The MAD Podcast with Matt Turck

Apr 10
OverviewShownoteHighlightsTranscriptChaptersPins

Shownote

Felix Rieseberg leads engineering for Claude Cowork at Anthropic, one of the most important new agentic AI products in the market today. In this episode of The MAD Podcast, Matt Turck sits down with Felix to discuss Anthropic’s newly announced Claude Mythos Preview, why Felix sees it as a genuine step-function change, and what it means when frontier AI starts showing outsized cybersecurity capabilities. The conversation then goes deep on Claude Cowork: how it emerged from Claude Code, what the famous “10-day” story really means, why Anthropic believes AI needs access to the local computer, and how Cowork actually works under the hood. Felix explains why skills are just text files, why memory is often just text files too, and how Anthropic thinks about building trust in AI agents. They also explore some of the biggest questions in AI product design and the future of software: why UX may matter as much as the model itself, why execution is becoming dramatically cheaper, what that means for product management and startups, and why Felix believes taste, alignment, and understanding humans may matter more than ever. (00:00) Intro (01:53) Claude Mythos Preview and the “step-function change” (06:16) Why Anthropic is treating Mythos differently (11:19) The real story behind Claude Cowork’s “10-day” build (12:42) Why Anthropic realized Claude Code needed a non-technical version (15:44) What Claude Cowork actually is (17:03) Under the hood: virtual machines, tools, skills (18:36) Where Cowork’s memory actually lives (19:26) How Cowork connects to files, apps, and the internet (20:45) Why Felix thinks the local computer is under-appreciated (24:49) Trust: how do you get users comfortable with AI agents? (28:45) What UX actually means for AI agents (31:27) Anthropic Cowork's roadmap is only one month long (34:12) Building 100 prototypes (35:10) If execution is free, what becomes the bottleneck? (37:25) Does it come down to taste? (40:12) The hardest part of building Claude Cowork (41:43) Advice for founders building AI agents (44:21) SaaSpocalypse: what’s left for software startups? (49:30) Where AI agents are going next (51:20) Regulated industries and enterprise adoption (54:15) Hot takes: what's underrated, overrated, and what Felix would build today

Highlights

In this episode of The MAD Podcast, Matt Turck interviews Felix Rieseberg, Engineering Lead for Claude Cowork at Anthropic, exploring how frontier AI is evolving beyond language models into trusted, autonomous agents that operate securely on users’ local machines.
00:00
An impressive model broke out of its sandbox
04:44
Claude Cowork will change software building
09:03
The main issue is presenting the right UI, capabilities, and onboarding rather than improving the model itself
11:19
Claude Cowork wasn't built from scratch—it used existing libraries and prior research at Anthropic
12:44
Claude Cowork gives Claude Code a virtual machine to set up its own developer environment with security guarantees
15:44
Skills in Claude Cowork are text files that instruct the model on how to do things
17:07
Claude has a to-do list that can be edited by humans
18:36
Memory in Claude Cowork is stored as plain text files, not proprietary or vector-based systems
19:30
Claude can use local files by dragging or giving access to specific folders, and it can connect to cloud sources like data warehouses
23:25
The current focus is on making Claude Cowork effective on the local computer, which resonates with users, allows for faster progress, and better safety and security
27:43
Trust is built on consistent, good outputs without user intervention
28:53
Successful AI products win by focusing on what's removed—not added—to the user experience
31:28
Execution has become cheap, allowing for trying multiple ideas quickly and testing in-house
34:13
The company created 100 different prototypes thanks to reduced execution costs and faster iteration.
35:10
Software may become more like the fashion industry, where storytelling, onboarding, and user experience are more important differentiators than raw capabilities
37:25
Different applications share similar primitives, enabling broad generalization
40:12
Recreating the latent demand is the most difficult
41:43
A recent seemingly mundane announcement was said to have caused a market collapse
47:41
AI is a step-function change
49:35
It's only been four years since AI could form coherent sentences, and now it can build applications and solve complex problems
51:30
Claude Cowork will help people organize work using AI in 2026, similar to how Slack changed work
54:17
MCPs separate data from the execution engine, making them a foundational but underrated enabler for AI in physical systems

Chapters

Intro
00:00
Claude Mythos Preview and the “step-function change”
01:53
Why Anthropic is treating Mythos differently
06:16
The real story behind Claude Cowork’s “10-day” build
11:19
Why Anthropic realized Claude Code needed a non-technical version
12:42
What Claude Cowork actually is
15:44
Under the hood: virtual machines, tools, skills
17:03
Where Cowork’s memory actually lives
18:36
How Cowork connects to files, apps, and the internet
19:26
Why Felix thinks the local computer is under-appreciated
20:45
Trust: how do you get users comfortable with AI agents?
24:49
What UX actually means for AI agents
28:45
Anthropic Cowork's roadmap is only one month long
31:27
Building 100 prototypes
34:12
If execution is free, what becomes the bottleneck?
35:10
Does it come down to taste?
37:25
The hardest part of building Claude Cowork
40:12
Advice for founders building AI agents
41:43
SaaSpocalypse: what’s left for software startups?
44:21
Where AI agents are going next
49:30
Regulated industries and enterprise adoption
51:20
Hot takes: what's underrated, overrated, and what Felix would build today
54:15

Transcript

Felix Rieseberg: There is something both impressive, but also slightly terrifying about seeing a model that is so much smarter than the last model we have worked with. The model was put into a little sandbox and it was given the task to, like, maybe break ...