Coding agents are incredible, we use them every day. But the current wave of AI tooling has mostly handed engineers faster ways to yolo code into production. The focus has been on creation, not on the process that makes creation reliable: question, plan, execute, review. There's a big difference between "rebuild Slack for me" and "solve this bug in one of these 16 repos, undocumented and impossible to reproduce."
We're building something better, and we just raised $1.23M in pre-seed funding from Freestyle Capital, Vermilion Cliffs Ventures, and angels to do it. Wallfacer creates persistent development environments for AI agents: dedicated workspaces so agents can do their best work, you can preview what they're building, and your team can stay effective in parallel.
Join the Beta waitlist and see for yourself.
Persistent Environments, Not Ephemeral Sessions
Coding agents have become essential, but they're often treated like disposable tools. Spin up a session, get a response, throw it away. You're stuck at your desk, tied to your machine. You are now limited by tools that were never designed for agents that work anywhere, on a persistent codebase, that you can actually see and preview.
Wallfacer provides a persistent development environment in the cloud -your developer machine everywhere., The agent has a real place to work: a sandbox where it can build, test, and iterate. You can preview what's being built in real time. No port collisions, no worktrees, no setup friction. Just a ready-to-go development environment that the agent can use, and you can access from anywhere.
Planning-First Workflows
Most AI tools skip the planning phase entirely, they sprint straight into execution. They write fast, they ship fast, and hope it works. But that's not how reliable engineering works. Real engineering teams follow a process. They question the requirements, break down the problem, plan the approach, execute and review.
And that's what Wallfacer enforces: in a world where anyone can create anything, anyway they want, an opinionated process rooted in experience is not a constraint. It’s what makes building faster and smoother possible.
How It Works
The workflow in Wallfacer follows the process engineers actually need:
Question → Scope → Plan → Execute → Review
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Start by describing the work. You give the agent context: “Here is what I'm seeing” or “we need to fix this”. The agent researches your codebase, understands the issue, and auto-generates a GitHub issue that documents what you're actually trying to solve. This becomes your North Star.
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Next, generate a plan. You can skip this and go straight to coding if you want. But we make planning so frictionless that most teams don't. Hit a button, and the agent generates a structured plan with sections designed to keep it on track: what's the approach, what are the phases, what's the testing strategy. You review it, tweak it, approve it.
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Then tell the agent to code. Once the plan is locked in, the agent executes. It builds in your persistent environment, maintaining full context of the plan and its own work. You can preview everything in real time.
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Finally, auto-generate the PR. When the work is done, generate a Pull Request directly from Wallfacer with a proper title, description, and context.
Get Access
Wallfacer is launching in closed beta.
If AI-assisted development is already part of how you work, and you want workflows that persist, scale, and travel with you, you can join the waitlist today.