Forward Deployed Engineering
Embedded senior engineers, working with AI agents, who own a problem from first conversation to working system.
Forward deployed engineering is a delivery model where senior engineers embed in the client's operation, work alongside the people with the problem and own it from first conversation to working system, independent of any vendor.
Engineers who think like operators.
Each engineer in the pod is broad across the business and deep in engineering, and works from a seat inside the team.
- 01
Business
sense.Reads the process, the cost of the delay and the number leadership cares about.
- 02
Product
judgement.Decides what to build first, what to leave out, and how people will use it.
- 03
Marketing
instinct.Knows the customer and the market the operation serves, so the work fits both.
- 04
Engineering
depth.Ships the integrations, data work and agents into the company's own systems.
Side by side with the operators.
Book a call
The roadmap is approved. The senior people to deliver it are not there.
- 01Hiring takes two quarters. Senior AI and platform engineers take months to find and longer to ramp. The roadmap does not wait.
- 02Agencies deliver from the outside. Work arrives in handovers, context is lost at every step, and the internal team inherits code it did not shape.
- 03Tool-tied FDEs sell the tool. A vendor's forward deployed engineers are there to make that vendor's platform stick. Independent pods choose the tools that pass the test.
A pod inside the team, from the first sprint.
The first quarter, week by week: scoping and the pod in place first, then delivery measured against the week-one baseline.
First quarter13 weeks
How forward deployed engineering compares.
| Compared on | FDE | Solutions engineer | Consultancy project | Staff augmentation |
|---|---|---|---|---|
| Who sets the roadmap | The client | The vendor's product | The consultancy's scope | The client |
| Where the work happens | Inside the client's repo and tools | Around one product | In the consultancy's environment, handed over | Inside the client's repo |
| Who owns the code | The client, from day one | Mostly the vendor | The client, at handover | The client |
| Tool choice | Whatever passes the test | That vendor's platform | The consultancy's stack | Whatever the client runs |
| How it is measured | Roadmap outcome and delivery metrics | Platform adoption | Deliverables accepted | Hours billed |
| Typical length | Quarters, resized each quarter | Months, tied to the licence | Fixed project | Open-ended |
| Best for | An approved roadmap and too few senior people | Rolling out one platform | One system, clearly specified | Filling seats on a stable team |
Priced per engineer-day, resized each quarter.
- 01
In place
in weeks.A pod starts two to four weeks after signature.
- 02
Priced per
engineer-day.Billed monthly, pod size agreed each quarter.
- 03
Kept by
the company.Code, specs, agents and dashboards run in its own cloud and stay there.
- 04
Free to
switch models.Each task uses whichever model passes its test at the lowest cost.
One call to size the first pod.
Book a callTwo other ways to bring Twistag in.
About forward deployed engineering.
What is a forward deployed engineer?
How is this different from staff augmentation?
Which tools and models does a pod use?
How big is a pod and who is in it?
How fast can a pod start?
What does it cost?
Who owns the code, the agents and the IP?
Can the pod work under a consultancy's brand?
What happens when the pod leaves?
Bring the roadmap.
Thirty minutes with a senior engineer on the roadmap, the team and what a first pod would take on.
A senior lead replies within one working day.
