Glossary

Eraser

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A Pangea Expert Glossary Entry
Written by John Tambunting
Updated Feb 20, 2026

What is Eraser?

Eraser is a diagramming and technical documentation platform built exclusively for engineering teams. Unlike general-purpose whiteboard tools, Eraser treats diagrams as code: every diagram is backed by a structured text representation that lives in Git, gets reviewed in pull requests, and diffs like source code. The platform bundles an AI diagram generator, a diagram-as-code editor, and a markdown document editor into one workspace — so engineers can write design docs and architecture diagrams without switching tools. Founded in 2021 in San Mateo, CA, Eraser reached one million users in its first year after raising $4M in seed funding. By 2026 it reports hundreds of thousands of monthly active users, with a new MCP Server enabling AI coding agents to read and write diagrams as part of automated workflows.

Key Takeaways

  • Diagrams are stored as version-controllable markup, so they can be diffed, reviewed in PRs, and tracked in Git like any other code.
  • Eraserbot monitors your repo and automatically regenerates architecture diagrams when Terraform or Kubernetes files change in a PR.
  • The free tier caps you at 3 files and 5 AI diagrams — meaningful team use requires a paid plan from day one.
  • AI credit limits on the $10/user Starter plan can constrain teams iterating rapidly through architectural designs.
  • Eraser's 2026 MCP Server lets AI coding agents generate and update diagrams, making it a design layer in agentic development workflows.

What Makes Eraser Different

Eraser's real edge is not that it can generate a diagram from a text prompt — several tools can do that. The differentiation is the CI loop. Eraserbot, a GitHub Action, watches specified files in your repository. When a pull request modifies a Terraform config or a Kubernetes YAML, Eraserbot regenerates the corresponding architecture diagram and commits the update back to the PR automatically. This treats architecture diagrams as first-class build artifacts, not documents that slowly drift out of date.

This mirrors the same philosophy that made infrastructure-as-code indispensable: if the source of truth is in the repo, everything derived from it should update automatically. Teams that have already adopted GitOps tend to adopt Eraser quickly because the mental model is identical. The diagram-as-code syntax resembles Mermaid closely enough that engineers familiar with it adapt within hours.

Eraser vs. Miro vs. Lucidchart

The three tools serve meaningfully different purposes, and conflating them leads to the wrong purchase decision. Miro is a general-purpose collaborative whiteboard — the right tool for cross-functional workshops, product brainstorming, and sprint planning boards. It has no diagram-as-code, no CI integration, and no engineering-specific diagram types. Choose Miro when your primary collaborators are PMs, designers, and executives.

Lucidchart sits between the two: more structured than Miro, deeply integrated with Google Workspace and Confluence, and familiar to non-technical stakeholders. But diagrams are visual-only objects with no code backing. Choose Lucidchart when your output needs to live in Confluence and be reviewed by non-engineers. Eraser is the choice when diagrams need to live in a repo, stay current with code changes, and be maintained by the engineering team without manual toil. The $10/user Starter price is comparable to Miro's team plan.

Pricing

Eraser offers four plans. The Free plan allows up to 3 files and 5 AI-generated diagrams — enough to evaluate the product but not to run a team on it. The Starter plan at $10/user/month unlocks unlimited files and 40 AI credits per user per month (30 standard, 10 premium). The Business plan at $25/user/month raises the credit allowance to 250 per user per month, which is where most active teams land. Enterprise is custom-priced and adds an AI reference library that ingests your company's specific technology stack and architectural patterns, giving the AI generation model better context for your environment. All paid plans allow unlimited free guests and support usage-based credit top-ups beyond monthly limits.

Eraser in Fractional and Contract Engineering Roles

Eraser surfaces in job descriptions alongside GitHub, Terraform, AWS/GCP, and technical writing — it is rarely the standalone required skill but appears as a signal of documentation discipline. Companies hiring through Pangea request Eraser experience most often in two contexts: staff-level engineers brought in for architecture documentation sprints, and developer advocates or technical writers engaged on documentation-as-a-service retainers.

The fractional use case is well-suited to the tool: a contractor can spin up in Eraser quickly (most engineers are productive within a day), produce a set of living architecture diagrams, configure Eraserbot to keep them current, and hand off to the internal team. That handoff is cleaner than with whiteboard-based tools because the diagrams live in the repo rather than in someone else's Miro workspace. We see this pattern increasingly requested by engineering-led Series A through C companies investing in technical documentation as a scaling lever.

Limitations to Know Before Adopting

Eraser is essentially unusable on mobile — fine for a desktop-first engineering tool, but worth knowing if your workflow involves tablets. The diagram-as-code syntax, while powerful, creates a contribution barrier for non-technical stakeholders who can edit Miro boards but cannot edit Eraser markup. There is no self-hosted option, which blocks adoption at enterprises with strict data residency or air-gap requirements. AI credit limits on the Starter tier ($10/user/month, 40 credits) can run short for teams doing rapid architectural iteration — credits are consumed per AI call, not per completed diagram, so exploratory sessions burn through them faster than expected. And because the free tier caps files at 3, nearly every realistic team evaluation immediately requires upgrading.

The Bottom Line

Eraser has carved out a defensible position in technical documentation by solving the problem that every engineering team eventually faces: diagrams rot. Its diagram-as-code foundation and Eraserbot CI integration make architecture documentation a maintained artifact rather than a one-time deliverable. For companies hiring through Pangea, Eraser proficiency signals an engineer who thinks about documentation systematically, understands GitOps principles, and can set up processes that remain useful after the engagement ends — not just produce polished diagrams that go stale in a month.

Eraser Frequently Asked Questions

Is Eraser only for large engineering teams?

No. Eraser is widely used by solo developers and small startups — its seed announcement cited customers from five-person startups to large tech companies. The free tier supports individual use, though the 3-file limit means most teams will need a paid plan quickly. The Starter plan at $10/user/month scales down to small teams without minimum seat requirements.

Does Eraser require engineers to learn a new diagram syntax?

There is a learning curve, but it is modest. Eraser's diagram-as-code syntax is similar enough to Mermaid that engineers familiar with it adapt in hours. The AI generation feature also lets users produce diagrams from plain English without ever writing markup manually, which flattens the initial barrier considerably.

How does Eraserbot keep diagrams up to date automatically?

Eraserbot is a GitHub Action you install in your repository. You configure it to watch specific files — Terraform configs, Kubernetes YAMLs, OpenAPI specs — and whenever a pull request modifies those files, Eraserbot regenerates the associated architecture diagram and can commit the updated diagram back to the PR. This means diagrams update as a side effect of your normal code review workflow.

How does Eraser compare to draw.io for teams already using Confluence?

draw.io (diagrams.net) is free, deeply embedded in Confluence via a plugin, and familiar to most technical stakeholders — a strong default for Atlassian-centric teams. The trade-off is that draw.io diagrams are purely manual with no AI generation and no CI automation. Eraser is the better choice when the goal is keeping diagrams synchronized with a live codebase rather than producing static reference documentation in Confluence.

Can a fractional engineer be productive in Eraser within a week?

Yes. Most engineers with infrastructure or backend experience can produce useful diagrams in Eraser within one to two days. The AI generation feature reduces dependence on syntax knowledge early on, and Eraser's documentation covers the diagram-as-code format clearly. Configuring Eraserbot for a repo takes under an hour for someone comfortable with GitHub Actions.
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