Software Factory
An agent that suggests code moves work onto your reviewers. Output arrives faster than anyone can verify it, and the bottleneck simply relocates. Delivery needs structure around it.
A software factory models delivery as dependency-aware work orders, gives each role its own harness specification, and puts evidence and approval between an agent and your main branch.
Dependency aware
Work is ordered by what it depends on rather than queued at random.
Role specific
Planner, implementer and reviewer each get their own specification.
Gated
Captured evidence decides what reaches your main branch.
Work order
dependency aware
Planner, implementer, reviewer
a harness spec per role
Evidence
captured per step
Approval gate
you decide what merges
Fit
Who This Is For
Teams past the pilot, where agent output now arrives faster than anyone can review it.
Platform engineering
Teams asked to industrialise agent output rather than pilot it
Delivery leaders
Groups where review capacity now caps how much ships
Regulated environments
Organisations needing an audit trail behind every automated change
Maintenance backlogs
Codebases with repetitive work nobody has capacity to clear
Process
How It Works
Pipeline discovery
We map how work reaches your main branch today, where review happens, and what your team will and will not let an agent merge
Workflow design
Delivery is modelled as work orders with explicit dependencies, isolated workers and recovery when a step fails
Harness per role
Planner, implementer and reviewer each get a specification covering tools, permissions and the checks they must pass
Pilot and gate
One repository first, with evidence capture and approval gates in place, then a runbook for the team inheriting it
Deliverables
What You Receive
Workflow design
Delivery expressed as dependency-aware work orders with isolated workers and defined recovery
Role specifications
A versioned harness specification per role, covering tools, permissions and required checks
Gates and evidence
Approval points backed by captured evidence, so nothing reaches the main branch unreviewed
Runbook and handover
Written operating guidance and enablement for whoever owns the pipeline after we leave
In practice
What an Engagement Looks Like
Three shapes this work usually takes. Scope is agreed before anything starts, and none of these depend on you running a particular vendor.
One repository first
Discovery, workflow design and gates on a contained piece of work, so the model is proven before the wider organisation commits to it.
Reviewed pull requests only
Agents open work and humans keep the merge decision. A common starting point for teams not yet ready to grant more autonomy.
Evidence for assessors
Audit trail, approval controls and retention designed for environments where every automated change has to be defensible.
Pricing
Engagement Options
Scope depends on your CI, your review culture, and how much autonomy your team is willing to grant.
Most requested
Pilot
One repository, one workflow
Typically 6 to 10 weeks
Single pilot repository
Prove the model on a contained piece of work before anyone commits the wider organisation.
- Pipeline discovery
- Workflow design in work orders
- Harness specification per role
- CI and headless integration
- Evidence capture and gates
- Runbook for the pilot
Programme
Multiple teams and repositories
Scoped per rollout
Custom scope
Extend a proven pipeline across teams, with governance and enablement built into the rollout.
- Everything in Pilot
- Multiple repositories and teams
- Shared specification library
- Governance and policy design
- Enablement for each team
- Phased rollout plan
Regulated
Audit and compliance first
Scoped per environment
Custom scope
For environments where every automated change needs a defensible trail behind it.
- Everything in Programme
- Audit trail design
- Approval and segregation controls
- Retention and evidence policy
- Documentation for assessors
- Rollback and incident procedures
Prices exclude VAT where applicable.
People
Who You Work With
Work is delivered by the Superagentic AI team, supported by consultants and researchers brought in on demand when an engagement calls for depth in a specific area. The same lead stays with you from the first call through to handover, so context does not get rebuilt between phases.
Open source
Projects Behind This Work
Agent-run delivery is what we build in the open. You are not buying these tools, and we work inside the pipeline you already have.
Questions
Frequently Asked Questions
Ready to move from suggestions to delivery
Tell us how work reaches your main branch today and what your team is willing to automate.
Working from London and San Francisco. Remote by default, on site where it helps.