Understand
Map the users, workflows, systems, constraints and business impact.
We sit with the people doing the work, follow the process as it actually runs, and write down where it breaks, who compensates for it and what that costs.
Delivery model
How we work: forward-deployed engineering
Our engineers work closely with your product and operations teams to understand the problem in its real environment, build the appropriate solution, integrate it with existing systems and support adoption.
Unfamiliar with the term? Forward-deployed engineering, explained without the jargon covers what it means in practice and when it is the wrong fit.
Process
Five stages, in detail
Define
Agree on the desired outcome, success measures, scope and technical approach.
Scope is written as outcomes with explicit exclusions, so that what is deferred is a decision rather than a surprise.
Build
Deliver in short, visible cycles and validate important assumptions early.
The riskiest assumption is tested first. You see working software during the engagement, not a demonstration at the end of it.
Integrate
Connect the solution to the real data, tools and operating environment.
Real records, real permissions, real failure modes. Integration is treated as part of the build, not a phase to negotiate afterwards.
Improve
Observe usage, resolve friction and support the team operating the system.
Adoption is measured by whether people use the system without workarounds. We fix what gets in their way and document what they need to run it.
1 / 5
Beyond the prototype
Demo versus system
PrototypeProduction
- Sample dataReal integrations
- Isolated environmentSecurity and permissions
- Manual oversightMonitoring and fallback paths
- Unclear ownershipDocumentation and handover
Engineering principles
What we hold to
- 01
Start with the operating problem
- 02
Use AI where it adds measurable value
- 03
Keep humans accountable for critical decisions
- 04
Design for production, not only demonstration
- 05
Make systems understandable and maintainable
- 06
Document important decisions
Technology decisions
What we use, what we avoid
Technology choices are made per problem. This is the default posture, not a fixed stack.
Use now
4 itemsProven in production for this class of problem.
- Typed application code
- Managed relational databases
- Automated CI/CD
- Infrastructure as code
Pilot
3 itemsPromising, applied behind a clear boundary.
- Retrieval-based assistants
- Structured document extraction
- Workflow orchestration services
Evaluate
3 itemsWatching closely, not yet recommended by default.
- Multi-agent orchestration
- Autonomous code modification
- Model-routing platforms
Avoid for this context
3 itemsPoor fit for regulated or operationally critical work.
- Unsupervised AI decisions
- Undocumented one-off scripts
- Opaque no-code chains at scale
Further reading
More on the delivery model
Software Delivery5 min read
Forward-deployed engineering, explained without the jargon
What the term actually means in practice, how it differs from outsourcing and staff augmentation, and when it is the wrong fit.
Read insightPlatform Engineering6 min read
What growing teams should expect from a CI/CD foundation
A reasonable baseline for a team of five to twenty engineers — and the parts that are usually over-engineered too early.
Read insightApplied AI6 min read
What production readiness means for an AI workflow
The checklist an AI workflow has to pass before it is handed to the people who depend on it: evaluation, thresholds, escalation and change control.
Read insightQuestions
Working with us
How is this different from staff augmentation?
Staff augmentation adds capacity to a backlog the client already owns. Forward-deployed engineering shares responsibility for understanding the problem, shaping the solution, integrating it and supporting adoption.
Will we see progress during development?
Yes. Reviewable increments, decisions, risks and deferred items should remain visible throughout the engagement.
How do you handle scope changes?
Changes are assessed against outcome, risk, cost and timeline. The team makes the trade-off explicit instead of quietly absorbing work until delivery becomes unpredictable.
How do you handle handover?
Repository access, documentation, deployment, credentials, ownership and support expectations are planned before the end of the engagement.
Next step
Start with one workflow
The Opportunity Sprint is the lowest-commitment way to test whether this model fits your organisation.