AI tool comparison
CatDoes v4 vs Mercury Edit 2
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Developer Tools
CatDoes v4
An AI agent with its own cloud computer builds your mobile apps
75%
Panel ship
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Community
Free
Entry
CatDoes v4 ships with Compose — an autonomous AI agent that runs on its own cloud computer to build mobile apps, websites, and internal tools from plain text descriptions. You describe what you want, Compose plans the work, writes code, runs tests, fixes its own errors, and deploys — even after you close the browser tab. Every project comes pre-wired with a full backend stack: database, authentication, storage, edge functions, and real-time events. The v4 release focuses on higher reliability and GitHub integration for developers who want to export and own their codebase. Free plans start at 25 credits; paid plans begin at $20/month with more projects and higher cloud limits. What distinguishes CatDoes from the crowded AI app builder space is the "own computer" framing. The agent doesn't just generate code for you to paste — it has an execution environment where it can actually run and debug the app, catching errors before you see them. Whether that closed-loop debugging holds up in practice for complex apps is the open question.
Developer Tools
Mercury Edit 2
Diffusion LLM that predicts your next code edit in parallel — not word by word
75%
Panel ship
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Community
Paid
Entry
Mercury Edit 2 is the second-generation coding model from Inception Labs, built on a fundamentally different architecture than every major LLM you're used to: a diffusion language model. Rather than generating tokens one at a time in a left-to-right sequence, Mercury operates in parallel — refining a full draft across all positions simultaneously. The result is next-edit prediction that runs up to 10x faster than GPT-4o and Claude 3.5 Sonnet at equivalent quality, with latency that finally matches how fast a human developer types. The model is purpose-built for the "edit" step in agentic coding loops — where an agent needs to predict what change should happen at a given location in a codebase, not generate a full file from scratch. Mercury Edit 2 takes in a code context, a cursor position, and optionally a natural-language intent, and outputs the predicted edit. Benchmarks show it matching or exceeding autoregressive models on HumanEval and MBPP tasks while cutting time-to-first-token by 80%. Inception Labs was founded by researchers from Stanford, UCLA, Google DeepMind, and OpenAI who bet that diffusion would eventually outpace transformers for text the same way it overtook GANs for images. Mercury Edit 2 is the clearest signal yet that this thesis has legs. At $0.25/1M input and $0.75/1M output tokens, it's meaningfully cheaper than GPT-4o-class models — and the speed advantage makes it a natural fit for high-frequency agentic tasks.
Reviewer scorecard
“The closed-loop debugging is the real differentiator. Most AI code generators dump code on you and walk away — Compose actually runs the result and iterates. At $20/month with code export and GitHub sync, it's a serious prototyping accelerator even for experienced devs who just want to skip the boilerplate.”
“The speed argument is real — I've integrated it into a Cursor-style flow and the round-trip latency for edits dropped to something that genuinely feels instantaneous. The architecture also means it's less prone to 'over-generating' — it just predicts the edit, not a rambling block of new code.”
“Every AI app builder claims autonomous error-fixing, and in practice they all hit the same wall: anything beyond CRUD starts failing in unpredictable ways. CatDoes is also a relatively unknown indie — if they fold or pivot, you're left with a codebase that was built in their proprietary stack. Export and own is a good safety valve, but validate it before depending on it.”
“Diffusion LLMs have been 'about to beat transformers' for two years. Mercury Edit 2 is faster, sure — but for complex multi-file refactors it still struggles with global context. The benchmark cherry-picking on HumanEval is a red flag when most real coding tasks are messier than a LeetCode problem.”
“This is the trajectory: agents that don't just write code but execute, test, and observe it running. When the agent can monitor its own output in production and self-correct, we've crossed into genuinely autonomous software development. CatDoes is an early bet on that future at an indie scale.”
“This is the first credible sign that the transformer monoculture in language AI might actually break. If diffusion models hit parity on reasoning while maintaining 10x speed, the cost curve for agentic loops changes completely — and Inception Labs has a year head start on everyone else.”
“As a designer who occasionally needs a working prototype but doesn't want to learn Swift or React Native, this is a gift. Being able to describe an app in natural language and get something testable on a real device within an hour is exactly the kind of tool that removes the 'I need a developer' blocker from creative projects.”
“For code-to-design workflows where I'm iterating on UI components in tight loops, the latency improvement is huge. Faster edit prediction means the feedback cycle between idea and implementation collapses — and that changes the creative dynamic substantially.”
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