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Visual social scheduling with media libraries and profile-based allowances

Social planning and publishing with per-network previews and an optional AI copilot

Publish social posts and collect customer photos, stories and testimonials

Team social publishing and community replies with shared approval processes

Social publishing projects with reusable assets and scoped team access

Build searchable knowledge portals and review documentation changes in isolated branches.

Generate an MDX documentation site or manage docs in a hosted editor with AI and publishing tools.

Write private notes in a flexible app, with optional services for syncing or publishing them.

Publish verified knowledge collections as governed documentation sites with access controls and analytics.

SEO automation that finds keywords, writes articles, and builds backlinks

A coverage-guided fuzzer that mutates input corpora to find crashes and hangs in instrumented programs.

Coordinate publishing calendars, changing priorities and a social-response inbox

Promote application configuration through GitOps stages so a GitOps agent can deploy each stage.

Build and operate WordPress, Drupal, and Next.js websites through managed environments and Git-connected workflows.

Create repeatable local development environments with a Vagrantfile and managed virtual machines.

Deploy supported application code to managed dynos without administering the host servers.

Query and update YAML, JSON, XML, and other structured data from the command line.

Run GitHub Actions-compatible workflows on Depot compute with local-run and job-debugging tools.

Automate dependency and lockfile updates through reviewable pull requests across many repository platforms.

Show estimated cloud-cost changes and FinOps checks alongside infrastructure code reviews.

Model Kubernetes builds, deployments, tests, and local development as a dependency-aware action graph.

Trace and investigate AI application calls with a local or self-hosted observability interface.

A Go library for verifying infrastructure code by deploying it, checking behavior, and cleaning up resources.

Develop Python in a project-aware desktop IDE with a debugger, test runner, and optional coding-agent tools.