Your engineering team is at capacity. That is not a hiring problem yet.

Your engineering team is at capacity. That is not a hiring problem yet.The situation is common enough to be boring. There is AI work on the roadmap. The engineering team is already committed for the quarter. Someone suggests hiring, and a job description gets written.The job description is not wrong. It is just slow. Between writing it, sourcing, interviewing, an offer, a notice period and a ramp, you are realistically six months from that person being useful. The roadmap item was for this quarter.What the six month gap actually costsMost teams price the delay as zero. The work slips, nothing visibly breaks, and the cost never shows up on a line item.It shows up somewhere else. It shows up as the competitor who shipped the feature first and now owns the comparison page. It shows up as the board asking the same question a second quarter running. It shows up as your best engineer doing the AI work at nights because they wanted to, badly, and now the thing that matters is a side project maintained by one person.None of that is a hiring problem. It is a capacity problem wearing a hiring problem's clothes.The three ways teams usually close itPull someone off the roadmap. Fastest, and it works, right up until you notice you traded a shipped feature for a shipped feature. The roadmap does not get shorter because you moved people around on it.Hire a contractor. Faster than a permanent hire. The problem is that most contract arrangements are structured around handing over code and leaving, which means the knowledge leaves with them. Six months later nobody in the building can explain why the retrieval pipeline is built the way it is.Embed someone into the existing team. Someone who sits in your channel, works to your spec, ships into your repo, and is directed by your people rather than working in parallel to them. The distinction that matters is whether they are inside the team or beside it.When hiring is the right answerIf the AI work is going to be a permanent, load-bearing part of your product, you want that capability owned in-house eventually. That is a real position and it deserves a real hire.The question is what happens in the meantime. Waiting six months to start is a decision, even when nobody writes it down as one.What to check before you decideThree questions, and they are worth answering honestly before spending money either way.

Is the work a defined outcome, or a research project? Defined outcomes can be embedded against immediately. Research projects need someone who will still be there in a year.

Does anyone internally have enough context to direct the work and review it? If not, you are not buying capacity, you are buying a dependency.

Is this urgent because of something external, or because it appeared on a slide? External urgency is real and worth paying to close. Slide urgency is not.

If the outcome is defined, someone can direct it, and the urgency is real, then the six month wait is the most expensive part of the plan.We embed a native AI engineer inside teams in that position, usually live in about ten days. You can read how that actually runs, or send a written intake and get a proposal back inside a day.Either way, price the delay. It is the number most teams never put on the board.

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