Comparison
AI staffing vs AI agency: which model should product teams choose?
An AI agency owns an outcome externally as a managed, fixed-scope project. AI staffing puts a dedicated engineer inside your team and codebase under your product and engineering leadership. The right choice depends on who you want owning the work.
Choose by operating model.
Choose AI staffing when you have product and engineering leadership and want a dedicated engineer embedded in your team and codebase, building lasting context. Choose an AI agency when you want an external team to own a defined, fixed-scope project or managed service and would rather buy a delivered outcome than direct the work day to day.
How the two models actually differ
Same goal, different operating models.
A fair, model-based comparison. Descriptions of AI agency reflect how that hiring model generally works; confirm current terms with the provider.
| Dimension | Devlyn | AI agency (managed project) |
|---|---|---|
| Pricing model | Public monthly ladder per dedicated role: $2,500 / $3,500 / $4,500. | Usually project-based or retainer pricing scoped to a statement of work; quoted per engagement. |
| How work is owned | You direct the engineer; they work inside your team, rituals, and repo. | The agency owns delivery and manages its own team against an agreed scope. |
| Where the work lives | In your codebase and systems, building durable internal context. | Often in agency environments or a project workspace, handed over on delivery. |
| Proof of fit | Two-week paid trial in your repo with inspectable artifacts. | Proven through project milestones, demos, and acceptance against scope. |
| Contract / lock-in | Month-to-month after trial, free replacement, no conversion fee. | Tied to the project term or retainer; change requests can affect scope and cost. |
| Who it is best for | Teams with internal leadership wanting in-team ownership and continuity. | Teams wanting outsourced, fixed-scope delivery as a managed service. |
When an AI agency is the better choice
- You want an external team to own a defined, fixed-scope project end to end.
- You lack internal product or engineering leadership to direct an embedded engineer.
- You prefer to buy a delivered outcome rather than manage the work day to day.
- The work is a one-off build or managed service rather than ongoing in-team capability.
When AI staffing (Devlyn) is the better choice
- You have product and engineering leadership and want to direct the work yourself.
- You want the engineer building lasting context inside your own codebase and team.
- You want continuity and in-team ownership rather than a handover on project close.
- You want a public monthly price and month-to-month flexibility, not a fixed project term.
Buyer checklist
Questions to ask before choosing staffing or an agency
- Do we have the internal leadership to direct an embedded engineer, or do we need delivery owned for us?
- Will the work and context stay in our codebase, or get handed over at the end?
- Is pricing a fixed monthly role rate or a project quote that can shift with scope changes?
- Who owns IP, repo access, and offboarding, and how is continuity handled after the engagement?
- How is fit proven up front: a trial in our environment, or milestone acceptance against scope?
Cost, risk, and process
Where the two models diverge in practice.
On cost transparency, AI staffing uses a public monthly role rate, while an agency typically scopes a project quote or retainer that can move with change requests. On risk ownership, an agency owns delivery against a statement of work, whereas staffing keeps ownership inside your team and validates fit through a paid trial in your repo with free replacement. On process speed, an agency can mobilize a whole team against a defined scope, while staffing places one dedicated engineer fast after a role-diagnosis call and keeps the resulting context in-house.
FAQ
Comparison questions.
What is the core difference between AI staffing and an AI agency?
Staffing embeds a dedicated engineer in your team and codebase under your direction. An agency owns a defined project externally as a managed service and hands over the outcome.
Which is better for a one-off build?
Often an agency, especially when scope is fixed and you would rather buy a delivered outcome than direct the work.
Which keeps knowledge in-house?
Staffing. The engineer works in your repo, so context, decisions, and code stay with your team rather than being handed over at project close.
Does Devlyn ever act like an agency?
No. Devlyn places dedicated engineers into your team under your leadership. If you need fixed-scope managed delivery, an agency model fits better.
Next step
Scope the AI role in 30 minutes.
Bring the bottleneck. We will map it to one of eight AI roles, send a vetted shortlist in 48 hours, and prove fit with a two-week paid trial in your codebase.