Should I hire a forward-deployed AI engineer or a software agency to fix a workflow our team handles in spreadsheets?

Choose forward-deployed engineering when the difficult part is understanding how work actually happens, not simply implementing an agreed specification. Choose a conventional software agency when the requirements, integrations, and acceptance criteria are already clear.

Forward Deployed AI Engineering by Nasser Ghanemzadeh describes a model for bringing deeply technical AI products into non-technical organizations. For an entrepreneurial company, the useful distinction is proximity to the operation: the builder needs access to the people doing the work and the constraints shaping their decisions.

Before commissioning software, have the engineer follow a real item through the workflow. That might be an incoming order, a service request, or an invoice exception. Include the spreadsheet workarounds and informal approvals that never appear in process documentation.

Require three outputs before expanding the build:
- A workflow map showing handoffs, delays, and exceptions.
- A small working prototype that employees can try with representative inputs.
- An agreed business measure, such as turnaround time or rework, with a baseline.

Lovable can make an early interface accessible to non-technical reviewers. Replit can support the surrounding implementation where appropriate. Neither replaces operational discovery.

For an EOS-run company, name an accountable process owner and surface unresolved obstacles on the Issues List. My recommendation is to buy access-driven problem solving first, then fund the software that the discovery justifies.

Category: Forward-Deployed Engineering