AI software factory for Claude Code, Codex, Cursor, Antigravity CLI and Pi
Turn your coding agents into a software factory.
Markbase puts your agents to work on tickets, alerts and scheduled tasks. Every run starts from your team's decisions, skills and history, and adds what it learns.
We chose Markbase’s on-prem deployment to give our team a shared knowledge base while keeping control of our data and infrastructure. We’re excited to bring it into our workflows at Coverdash.
Perry RaskinHead of Web & Integrations, CoverdashSoftware factory
What is a software factory?
A software factory is a repeatable process for building and maintaining software with AI agents.
Your team defines how the work should be done, gives agents the project knowledge they need, and decides which checks and reviews are required along the way.
Markbase connects these workflows to the tools your team already uses and keeps the knowledge available as work passes between people and agents.
[ Markbase ]
Markbase is a complete software factory for development teams, built around your team's context.
Context is what your agents know about your work: the decisions, the history and the way your team works. Markbase keeps it in one place outside any single agent, as readable documents your team can read and steer. It grows with every task, stays with the team when people move on, and comes with you if you change coding agents.
Shared knowledge
Gets better with every task
Every agent starts from the same knowledge: the agreed requirements, your access rules and the team's implementation and testing skills. That helps it make decisions that fit the project.
When a change merges or an investigation finds a problem, an agent records what changed, the cause and the fix. The next feature or issue starts from what the team has already learned.
Shared skills
Gives every agent the same skills
Your team writes skills for the work it does again and again, such as reviewing a change, writing tests or investigating an alert. Every agent uses the same version, whether it runs in Claude Code, Codex, Cursor or Antigravity CLI.
If someone improves a skill, for example so that code review flags changes that arrive without tests, everyone on the team gets the new version.
Your workflow
Works the way your team already works
Markbase follows the way your team already gets work done, so you don't have to change your process to suit your agents.
Take branches and pull requests. When an agent writes the design for a feature on a branch, that design stays with the pull request. Agents working from main don't see it until the pull request merges, so they don't build on plans that might still change. If the pull request is closed instead, the design is marked as abandoned.
Why run a software factory?
- Moves faster without breaking things
- Cycle times fall and you deploy more often, while your change failure rate stays where it was. Every change still passes the checks and reviews your team has agreed on.
- Makes delivery predictable
- Work goes through the same steps every time, so you can plan around it and keep to the dates you set. Quality stays consistent from one change to the next.
- Ties spending to shipped changes
- You can see what each accepted change costs, counting both your team's time and your AI spend. That cost falls as the factory improves.
- Brings your team and your agents together
- Agents take on more of the work, so the team can do more without growing. People spend their time setting direction, reviewing changes and making the calls that need judgement.
- Learns along the way
- Every task leaves something behind, such as a decision, the cause of a bug or the fix for it. Your agents start the next task knowing what the team has already learned, so less work comes back for rework.
- Gets new people productive from the first day
- A new developer and their coding agent start with the project's decisions, current plans and the team's skills. They work the way the team does from their first task, instead of spending weeks learning it.
[ Works with ]
Markbase works with the tools you already use.
Your coding agents share what they know through Markbase, and your other tools can start an agent when something happens. Anything that can send a webhook works too.
- Claude Code
- GitHub
- Sentry
- Codex
- Linear
- Cursor
- PagerDuty
- Antigravity
- Slack
- GitLab
- Grok
- incident.io
- Stripe
- DeepSeek
- Bitbucket
- Webhooks
- Kimi
- Shopify
- Pi
- Axiom
- Svix
GitLab
Grok
incident.io
Stripe
DeepSeek
Bitbucket
Kimi
Shopify
Pi
Axiom
Svix[ Use cases ]
Use cases
Investigate production alerts with the project's history in view
An alert triggers an agent to investigate using previous incidents, architectural decisions, and known constraints. Its findings go back into shared knowledge, giving the next investigation a better starting point.
Stop agents repeating a mistake that once took production down
Three months ago a database change locked a busy table and took the site down. The team wrote up what happened and what to do instead. When an agent plans a similar change, it finds that write-up first and takes the safe route.
Carry a feature rollout from development through customer testing
A feature needs two weeks of testing with selected customers before wider release. Preserve the rollout plan, feedback, release criteria, and follow-up dates so people and agents can carry it through each stage.
Hand work from a developer's machine to one inside your private network
An agent builds a feature on a developer's laptop, with a script to backfill existing data. The script needs the production database, which only your private network can reach. Markbase passes the work to an agent inside that network, which asks before running it.
Bring a new developer or agent into an active project
Give a new contributor the project's decisions, current plans and the team's skills. Their coding agent gets the same skills as everyone else's, so it works the way the team does from the first day and picks up every improvement after.
Build an integration against the events a service really sends
An agent is adding Stripe webhooks. It makes a short-lived webhook URL, you paste it into Stripe and send a test event, and the agent writes the handler against the real payload. It records what it learned about the events in Markbase, so the next agent working on payments starts from there.
Ask an agent from the Linear issue, GitHub pull request or Slack thread
Someone mentions Markbase on a Linear issue. An agent on your own machine picks it up with the project's background, answers in that thread as Markbase rather than as the person whose login it runs under, and moves the issue along when its pull request is up. A follow-up in the thread starts the next run with the conversation so far.
An alert triggers an agent to investigate using previous incidents, architectural decisions, and known constraints. Its findings go back into shared knowledge, giving the next investigation a better starting point.
Three months ago a database change locked a busy table and took the site down. The team wrote up what happened and what to do instead. When an agent plans a similar change, it finds that write-up first and takes the safe route.
A feature needs two weeks of testing with selected customers before wider release. Preserve the rollout plan, feedback, release criteria, and follow-up dates so people and agents can carry it through each stage.
An agent builds a feature on a developer's laptop, with a script to backfill existing data. The script needs the production database, which only your private network can reach. Markbase passes the work to an agent inside that network, which asks before running it.
Private networkGive a new contributor the project's decisions, current plans and the team's skills. Their coding agent gets the same skills as everyone else's, so it works the way the team does from the first day and picks up every improvement after.
An agent is adding Stripe webhooks. It makes a short-lived webhook URL, you paste it into Stripe and send a test event, and the agent writes the handler against the real payload. It records what it learned about the events in Markbase, so the next agent working on payments starts from there.
Someone mentions Markbase on a Linear issue. An agent on your own machine picks it up with the project's background, answers in that thread as Markbase rather than as the person whose login it runs under, and moves the issue along when its pull request is up. A follow-up in the thread starts the next run with the conversation so far.
[ Get started ]
Try Markbase for free
Connect the agents and tools you already use. Markbase is free for one person, with no card needed.
Start free
Sign up, create a workspace and connect your first agent in a few minutes.
Let your agent set it up
Copy one prompt into Claude Code, Codex, Cursor or Antigravity CLI. It installs the Markbase skill and connects your account.
Copies a setup prompt for your coding agentBook a demo
Talk to the team that builds Markbase for 30 minutes. We’ll show you how it fits your workflow and answer your questions about plans, security or deployment.
To see what each plan includes, compare plans.