Cloud Coding Agents: What Changed, What Stayed the Same, and Where Remedy Fits

A cloud coding agent is not magic. Strip away the product gloss and most of the category is the same machine: the model plans, tools read and write state, execution happens in somebody else’s sandbox, git and validation provide feedback, and the end result is delivered as a branch, a PR, or a recorded attempt. The interesting competition is not over whether this pattern exists. It is over who owns the control plane and what trust boundary they choose.

That distinction matters because the same runtime ingredients can produce very different products. GitHub uses Actions-adjacent environments and platform-native permissions. Cursor uses editor-driven cloud agents and branch workflows. Autonomous “software engineer” products frame the whole experience as open-ended delegation. Infrastructure vendors like E2B, OpenCode, and Vercel Sandbox sell the execution substrate itself. Remedy fits none of those exactly. It is closer to a review-triggered execution layer than a general-purpose AI employee.

PART ONE

What A Cloud Coding Agent Actually Is

PART TWO

A Practical Map Of The Market

Those layers get bundled differently. GitHub’s value is native workflow gravity. Cursor’s value is authoring velocity with cloud continuation. Devin-style products sell the dream of a session that keeps going. E2B and Vercel Sandbox sell the compute substrate. OpenCode sells a headless agent engine you can drive from another product. Critique does not need to replace all of them. It composes the pieces that matter for review and bounded execution.

PART THREE

The Design Tensions Everyone Hits

This is why “agent mode everywhere” is not automatically “safe auto-merge everywhere.” Every serious team eventually asks the same questions: what files can it touch, how many times can it retry, what secrets does the sandbox see, how do we price model plus compute plus re-review, and can we explain the change in a way a reviewer will trust? Those questions are not vendor-specific. They are the category.

PART FOUR

Where Remedy Fits

Remedy is not trying to win the same primary interface as a general cloud coding agent. In Critique, review is the upstream control plane. Findings, severity, file anchors, and confidence become structured inputs. Remedy compiles that into a blueprint, persists a RemedyRun and RemedyAttempt, and executes through OpenCode today, with E2B-backed isolation available when configured. That puts Remedy on the same infrastructure plane as the broader market while keeping a different product contract.

PART FIVE

General Cloud Agents Versus Remedy

That distinction changes who should buy what. If your team wants open-ended delegation from the IDE or a GitHub issue, cloud agents are the natural category. If your team already believes quality is a pipeline and wants findings to become bounded fix attempts with explicit validation, Remedy is the sharper tool.

PART SIX

The Model Layer Matters Less Than The Routing Layer

The market still loves to argue about which foundation model “wins,” but production systems rarely work that way. The durable advantage comes from separating roles. Stronger synthesis models can act as review lead. Faster or cheaper models can power specialists. Execution models can be different again. Critique already exposes that kind of separation across review and Remedy, which is why model diversity is a feature, not a branding exercise.

CLOSING

Pick The Abstraction That Matches Your Org

Cloud coding agents are converging on the same primitives: isolated compute, tool loops, git, validation, and asynchronous execution. The real differentiation is control plane and trust boundary. GitHub, Cursor, Jules, Devin, OpenCode, E2B, and Vercel Sandbox all tell different stories with the same underlying ingredients.

Remedy belongs in that conversation, but not as a generic “AI staff engineer in the cloud.” It is a review-attached execution layer with exportable blueprints, bounded fix loops, BYOA support, and infrastructure choices that align with how serious teams already govern code change. Judge it alongside PR review automation and policy-bound fix pipelines, not only against open-ended delegation products.