You need more engineers
and you need AI.

The answer to both is the same place.

THE PROBLEM

You are being squeezed from both sides. Your board wants AI integration. Your ops team wants more engineers. Neither conversation has given you anything executable next quarter.

Here is what nobody in those rooms is telling you: the capacity problem and the AI problem are the same problem. The fastest place to solve both is a process your firm runs every single month that is quietly consuming the hours of your most valuable technical people without anyone tracking the cost.

Your proposal process.

The people writing your proposals are not your junior staff. They are your most seasoned engineers, the ones with 15 and 20 years of experience, the ones your clients ask for by name, the ones you cannot replace if they walk out the door.

Right now, a significant portion of their time is spent hunting through SharePoint folders for past project examples, reformatting qualifications pages built for a different RFP two years ago, and writing scope language that looks 80 percent identical to the last proposal they submitted.

That is what your talent that drives $600/hr in revenue is doing on a Saturday.

Doing it the way we used to does not work in 2026. The firms that figure that out first will be cheaper to operate and harder to beat within 24 months.

THE NEW PROCESS

01	Build a queryable knowledge database Every completed project tagged by type, geography, scope size, permit agency, and contract structure. Not a shared drive. A structured library an AI pulls from in seconds. When a new RFP arrives, the system retrieves the most relevant past work automatically.

02	Feed the entire RFP into the system Every evaluation criterion, every stated preference the client put in writing. The system builds a proposal organized around what that specific client asked for, not around the template your firm has been recycling for a decade.

Add the client transcript layer

Every conversation your team has had with that client: kickoff calls, site visits, scope clarification meetings. The AI writes to that specific client, in their language, around their stated priorities. Senior engineers review a 90% complete output instead of barely getting the proposal started.

04	Let the system handle the CVs Every engineer has a CV with 50 projects. The client needs the 8 that are directly relevant. The system selects only matching projects and formats them to the evaluation criteria. Every proposal, every time, without your senior engineers touching it.

REAL USE CASE: THE NUMBERS

A business major straight out of school, less than two years of experience, is now writing proposals instead of what used to require a team of four people and a committee sign-off process. Same quality. Better client focus. Senior engineers freed up entirely.

THE POINT

The capacity problem your ops team keeps raising is real. But the first move is not a hiring plan. It is stopping the bleed of senior technical hours into a process that no longer requires them.

BEFORE

24 hrs

Senior engineer hours
per proposal

→

AFTER

4 hrs

Total hours, zero
from senior staff

SAVINGS

½ week

Production time
recovered per proposal

This isn’t just about making proposals faster. It is about giving your most experienced technical people their time back so they can do the work that actually requires them.

If you want to learn more, email me at Mike@mod-eng.com

Michael Groselle, P.E.

CEO / Founder, Modern Engineering Solutions

You need more engineersand you need AI.

Build a queryable knowledge database

Feed the entire RFP into the system

Add the client transcript layer

Let the system handle the CVs

You need more engineers
and you need AI.