AI agent developers from $40/hr — and the rate is the smallest number here
Every other page you have read today either quotes rates or sells the service. None do both. Ours does — then spends the rest of the page on the costs nobody quotes you, and on where our engineers actually sit.
A quote is a build price. The bill is the build, plus the running cost, plus the cost of getting it wrong, plus whatever you are left holding if it ends. Three of those four are usually missing from the page you are comparing.
A price you can read is worth more than a promise you cannot check.
What do we charge to build an AI agent?
Published, in numbers, on the page that sells the service. This is the whole point.
We are a US-registered LLC with a remote engineering team based outside the United States. That is the reason our floor is lower than a US-based shop’s, and we would rather tell you that here than let you work it out from the invoice.
Where our engineers actually sit
You contract with a US entity. Agreements, invoicing and liability sit here.
The people writing your code are not US-based. This is where the price gap comes from.
Why we put this in the pricing section
- It is the most hidden thing in this market. Several agencies competing for this search carry a US city in their branding and deliver from elsewhere.
- The structure is fine. A great deal of good software is built this way.
- The silence is not. Letting you assume otherwise is the part we object to.
What you get, and what you give up
+What you get
- Senior work at half to two-thirds of the US-based rate.
- A US entity to contract with. Normal agreements, normal invoicing.
- The same person throughout. Whoever scopes it builds it.
- No subcontracting. Your work does not get passed on.
The rate gap is the reason remote teams exist. We will not dress it up.
–What you give up
- Same-day timezone overlap. We work a scheduled window with US hours.
- All-day availability. Not someone reachable at 4pm Pacific every day.
- An office you can visit. There is not one, yet.
- Bench depth. We are small. No spare team to swap in.
If any of those four is a dealbreaker, say so early and we will tell you straight.
What actually moves the number up or down
Not the agent logic, which is the part most people expect to be expensive. It is the integrations — how many systems it has to reach, whether their APIs are sane, and how long it takes to get credentials. Two agents doing similar work can differ threefold purely on access.
We publish these because a vendor who will not name a price has already told you something.
Should you buy hours, a team, or a finished project?
Same engineers either way. What changes is who carries the risk of a bad estimate — and that is the only part that matters.
Buy hours when the scope will genuinely move. Buy a project when it will not. Buy a dedicated team when the work is continuous and you want the same people every month rather than a queue. Most buyers are quoted whichever one the vendor prefers, which is rarely the one that fits.
Hourly — you buy time
Best when the scope is genuinely unclear, or you need a second pair of hands on something already running.
The catch you carry the estimate risk. If we misjudge the work, you pay for our misjudgement.
Minimum no retainer, no minimum block. Stop whenever.
by seniority and scarcity of the skill
Dedicated resource — you buy a person
Best when the work is continuous, you want the same engineer every month, and you would rather not re-scope every few weeks.
The catch you are paying for availability, so idle weeks still cost. Below about half-time it is usually worse value than hourly.
Minimum one month, then rolling. No annual lock-in.
half-time to full-time, one engineer
Fixed project — you buy an outcome
Best when the job can be described precisely enough to price. Most agent builds can.
The catch it needs real scoping first, so it starts slower. Changing scope mid-build means re-quoting.
Minimum nothing ongoing. One number, one deliverable.
fixed before we start, risk sits with us
Which one actually fits — the honest rule
| Your situation | Model that fits | Roughly | Why not the others |
|---|---|---|---|
| One agent, clearly described | Fixed project | $8K–40K | Hourly makes you carry our estimate risk for no reason |
| Small automation, one system | Fixed project | from $1.8K | Too small to justify a monthly commitment |
| Scope will genuinely change weekly | Hourly | $40–150/hr | A fixed price on a moving target is either padded or about to be re-quoted |
| Ongoing work, 20+ hrs a week | Dedicated resource | $3.2K–9.6K/mo | Hourly at that volume costs more and gives you no continuity |
| Several workstreams at once | Team of 2–3 | $9.6K–22K/mo | One engineer becomes the bottleneck |
| 160+ hrs a month, indefinitely | Hire an employee | $200K+/yr loaded | Genuinely cheaper than us at that volume. We will tell you so. |
Note the last row. Every agency comparison table stops just before the point where the honest answer is “employ someone”. That point is real, it is roughly full-time-and-permanent, and knowing where it sits is worth more to you than any discount we could offer.
The model decides who pays for a bad estimate. Everything else is detail.
What does a dedicated AI agent team cost per month?
Published, per role, with the caveat that matters: more people is not more capability if a function is missing.
A dedicated team means the same engineers each month rather than whoever is free. You are buying continuity and availability. It is the right model when the work is continuous — and the wrong one when it is not, because idle capacity still bills.
What each function does, and what breaks without it
The useful question is not how many people, but which functions are covered. A three-person team missing evaluation will fail where a two-person team covering it succeeds.
Only the first four are ours. The fifth is yours, and no amount of headcount on our side substitutes for it — if nobody internally owns the outcome, the project stalls regardless of how good the build is.
Can you add a resource to a team you already have?
Yes, and it is a common way to start. If you have developers but nobody who has shipped an agent, a fractional lead or one dedicated engineer working alongside your team is usually better value than a full pod — your people already know your systems, which is the expensive knowledge. We build the first one with them watching, and they own the second.
Count functions, not people. A gap costs more than a seat.
Why is the quoted price never the price you pay?
Four costs sit in this decision. Almost every page you compare covers one of them.
The build price is the one everyone competes on, which is exactly why it is the one that tells you least. The other three decide whether the project is still alive in a year. This applies whichever engagement model you pick — hourly, team or fixed project.
1The two costs you will be quoted
- The build. Design, integration, testing, deployment. Ours is fixed before we start.
- The rate. Hourly or monthly. Easy to compare, which is why every vendor leads with it.
These are real, and they are the smaller half.
2The two costs that decide the outcome
- The run cost. Model tokens, monitoring, evaluation upkeep, and the rework every time a model is deprecated. This recurs forever.
- The failure cost. What it costs when it does not reach production — which, per Gartner, is where a large share of agentic projects end up.
Neither appears on a quote. Both appear on your P&L.
“Why can nobody give me one number?”
Because two of the four costs depend on how much you use the thing, and nobody knows that before it exists. An honest vendor gives you a fixed number for the build and the shape of the other two, then says which parts are estimates. A vendor who gives one confident number covering all four has either padded it heavily or has not thought about months two through twenty-four.
The run cost is the one that surprises people
A build is a single event you can plan for. Running the thing is a subscription you did not sign. Token spend scales with usage rather than headcount, monitoring needs an owner, and every model deprecation is unplanned engineering work on a system that was “finished”. When we quote, we say what we think the running cost will be, and we say plainly when we are estimating rather than measuring.
Why we quote fixed price rather than hourly wherever we can
An hourly rate transfers the risk of a bad estimate onto you. If we misjudge the work, an hourly arrangement means you pay for our misjudgement. A fixed price means we do. That is the correct way round, and it is also why we insist on scoping properly before quoting — a fixed price given blind is either padded or about to move.
Compare four numbers, not one. Most vendors only want you looking at the first.
What do you actually own when the engagement ends?
Of the pages ranking for this search, not one answers this. It is a top-three buyer anxiety and it is unwritten.
You should end an engagement holding a system you can operate without the people who built it. That means the code, the prompts, the integration logic, the evaluation set and a runbook — not a running service you cannot see inside.
- Code and promptsYours outright. Prompts are not a trade secret we withhold; they are the product.
- The evaluation setThe tests that prove the agent behaves. This is the item most often missing, and without it you cannot safely change anything after we leave.
- Integration logic and runbookHow it connects and how to operate it, written for someone who was not in the room.
- Your own API keysThe agent runs on your accounts, not ours. If we disappear, nothing switches off.
- No platform lock-inWe build on open frameworks and resell no database or platform, so there is no license to lose.
- An exit that is not a cliffIf you want to bring it in-house, we hand over and help your team pick it up. That is a normal ending, not a failure.
Why the evaluation set is the item to fight for
Of everything on that list, this is the one most often missing and the one you will miss most. Without it, every later change — a new prompt, a swapped model, one more feature — is a gamble, because nothing tells you whether you just broke something. It is also the line most commonly absent from a competitor's quote, which is worth noticing when you are comparing two prices that look close.
If you cannot fire your vendor without losing the system, you did not buy a system.
Do AI agent projects fail for technical reasons, or hiring reasons?
Everyone writes “why pilots fail” and “how to hire” as separate articles. The interesting part is the join.
Look closely at why these projects die. Gartner puts the figure above 40% before 2028, and names runaway spend, value nobody can demonstrate, and missing controls. None of that is the model failing. Each is a decision, and most were taken in the room where the vendor was chosen.
What this means when you are comparing two quotes
Read each proposal for the five causes above rather than for the price. Does it name a run cost? Does it include an evaluation set? Does it say who does the work? Has anyone asked about your systems access yet? A cheaper quote that answers none of those is not cheaper — it has moved the cost somewhere you cannot see it yet.
Most agent projects are lost at the scoping call, not in the code.
Should you hire in-house, an agency, a freelancer, or offshore?
Every comparison like this is published by an interested party and lands on its own model. Ours lands on us twice out of four times, and says so.
| Option | Realistic cost | Best when | Worst when |
|---|---|---|---|
| In-house hire | $200K+ loaded, 8–16 weeks to fill | AI is your product and the work never stops | You need one agent built. You will spend a quarter recruiting for a six-week job. |
| Freelancer | $50–150/hr | A contained, well-specified piece of work | The job needs several skills, or somebody has to still be reachable in month eight. |
| Large offshore agency | $25–35/hr | Budget is the binding constraint and the spec is fixed | You are one account among hundreds, the engineer changes without notice, and nobody senior is reachable. |
| US-registered, remote team — us | $40–150/hr, or $8K–40K fixed | You want a US entity to contract with, senior work below US-based rates, and it built, proven and handed over | You need same-timezone availability all day, a large team, or continuous capacity for a year. Then hire in-house or a US-based shop — genuinely. |
The threshold where an employee beats any agency
Roughly 160 hours a month, sustained. Below that, recruiting cost and idle capacity make a full-time hire worse value than buying the work. Above it, agency margin starts costing more than a salary and you should hire. The number is not precise and it moves with seniority — but the shape of it is real, and no agency page will volunteer where its own ceiling sits.
When we will tell you not to hire us
- An off-the-shelf tool already does it. If your workflow is standard, buying beats building and we will name the product.
- You need more than about 160 hours a month, indefinitely. At that point an employee is cheaper than any agency, including us. The arithmetic is not subtle.
- You need a large team, or someone reachable all day US time. We are small and we are remote. We will not pretend otherwise to win the work.
- Budget is genuinely the only constraint. A large offshore shop will quote below us. If price is the whole decision, take it — just ask who your engineer will be and whether they change.
A comparison that never recommends against its author is an advert with a table in it.
How do you evaluate an AI agent developer if you are not technical?
Six questions. You do not need to understand the answers technically — you need to notice whether they are specific.
You cannot assess someone's code. You can assess whether they have operated something real, because people who have carry specific scar tissue and people who have not speak in generalities.
If they have never talked a client out of one, they are selling, not advising.
Anyone who has run these in production has one. A blank is a bad sign; a vague answer is worse.
Listen for evaluation and monitoring. If the answer is “you'd notice”, they have not run one at scale.
They may not know precisely. They should know the shape, and say which parts are estimates.
Ask directly, and ask us. Our answer: a US-registered LLC, engineers based outside the US, no subcontracting. Subcontracting and remote delivery are both fine — being vague about either is the problem.
The answer should be concrete: code, prompts, evaluation set, runbook, keys.
The tell that matters more than any single answer
Specificity. Someone who has run agents in production answers with particulars — a system, a date, a number, a thing that broke on a Tuesday. Someone who has only demoed them answers with categories and best practice. You do not need to follow the technical content to hear the difference, and it is the most reliable signal available to a non-technical buyer.
You are not assessing code. You are assessing whether they have been burned before.
Why hire LoopHawk, and when not to?
We are new. We would rather tell you that plainly than have you discover it.
We are a small US-registered team that builds AI agents and resells nothing. What we can offer instead of a client list is a working demo on your own data, a fixed price agreed before we start, and full ownership of everything we build.
- Our rates are on this pageYou did not have to fill in a form to see them, and we told you where the team sits. Almost nobody selling this service does either.
- Fixed price before we startIf we misjudge the work, that is our problem rather than an extra invoice.
- You own everythingCode, prompts, evaluation set, runbook, and it runs on your keys.
- The demo comes before the invoiceWe build something working on a sample of your real data first. You can judge it in an afternoon.
- We say when not to buildIncluding when an off-the-shelf tool wins, which costs us the work.
- We are honest about being new, and about being remoteNo client logos here, because we have none yet. A US-registered entity, a team outside the US, and a working demo you can judge in an afternoon.
“You have no clients yet — why would we go first?”
A fair question and we will not answer it with adjectives. Go first because the demo costs you nothing and you can judge it on your own records in an afternoon; because the price is fixed before we start; and because you own the code, so the worst realistic outcome is that you keep a working agent and never call us again. That is a smaller risk than it first appears.
We cannot show you logos. We can show you the thing working on your data by Friday.
Hiring AI agent developers — your questions
How much does it cost to hire an AI agent developer in 2026?
Our published range is $40–150/hr. US-based shops typically start around $60 and run to $150; large offshore agencies sit near $25–35. We sit across that gap because the entity is US-registered and the engineering is remote. Most buyers are better served by the fixed-price route anyway — $1,800 for something single-purpose up to $40,000 for a production build.
What is the difference between hourly, fixed-price and monthly pricing?
Hourly transfers estimation risk to you. Fixed price keeps it with the vendor, which is the correct way round, but requires proper scoping first. Monthly retainers suit continuous work rather than a defined build. We prefer fixed price for builds and a small optional monthly fee for monitoring.
How much does it cost to build an AI agent, rather than hire the person?
Between about $1,800 for a single-purpose agent and $40,000 for a production system wired into live data with an evaluation set. The variable that moves it most is integrations, not the agent logic.
Which costs get left off the quote?
Four: model tokens as usage grows, monitoring and evaluation upkeep, rework when a model is deprecated, and the internal time your team spends on access and review. None of these normally appear on a build quote.
What will the agent cost to run each month after launch?
It depends on volume and how many model calls each task needs, so anyone quoting a confident figure before seeing your workflow is guessing. Ask for the shape of it and which parts are estimates — that answer tells you a lot about the vendor.
Should I hire in-house, use an agency, hire a freelancer, or go offshore?
Match it to how long the work lasts. A one-off build suits an agency or a freelancer; permanent, continuous AI work suits an employee. Ask about overlap hours rather than location — a remote team with a scheduled window works fine, a remote team with no overlap does not. The crossover point is roughly 160 hours a month sustained: past that, salary beats agency margin.
Can one developer build an entire AI agent, or do I need a team?
One experienced person can build a production single-purpose agent. What matters is whether the work covers all the necessary functions — integration, evaluation, monitoring — not how many people are on the invoice. More people is not more capability if a function is missing.
Can my existing software engineers just learn to build AI agents?
Often yes, and sometimes that is the right answer. The gap is rarely the model work; it is evaluation and knowing the failure modes, which is experience rather than knowledge. A common good outcome is that we build the first one with your team watching, then they own the next.
How do I evaluate a developer if I am not technical?
Ask the six questions in the vetting section above. You are not judging the technical content of the answers — you are judging whether they are specific. People who have run agents in production have particular scars; people who have not speak in generalities.
What are the red flags that a vendor will subcontract my project?
Reluctance to name who does the work, a rate far below the market for the country they claim, no direct access to the engineer during scoping, and vagueness about timezones. Subcontracting is not automatically wrong — being unclear about it is.
How is an AI agent developer different from an ML engineer or a chatbot developer?
Think of it by what each one ships. An ML engineer produces a trained model. A chatbot developer produces a conversation that answers. An AI agent developer produces something that goes and does the task in your other systems — so permissions, integration and proving it behaved take up most of the work, not the model itself.
How long until an agent is actually in production?
Two to four weeks for a focused build once access to systems and data is sorted. Access is usually what takes the time, not the agent. Any timeline that starts with a multi-month discovery phase before anything runs is a scoping exercise being sold as a project.
Why do most AI agent projects fail, and is it a hiring problem?
Gartner puts it above 40% before 2028. The reasons they give — spend that got away, benefits nobody could evidence, controls that were never built — are choices, not technical defects. The table further up this page maps each one back to the hiring decision behind it.
Where is your team based?
LoopHawk is a US-registered LLC and our engineers work remotely from outside the United States. That is why our floor sits below a US-based shop’s. We work a scheduled overlap with US hours rather than claiming to share your timezone, and we do not subcontract — the person who scopes your build is the person who builds it. If you need someone available across a full US working day, tell us early and we will say honestly whether we fit.
Who owns the code, prompts and data when the engagement ends?
With us, you do — code, prompts, integration logic, evaluation set and runbook, running on your own API keys. Ask any vendor this directly and get it in writing before you pay. Of the pages ranking for this search, none answer it.
If any answer above sounded like a pitch, hold us to it on the call.
Tell us what you need built — get a fixed number
We will scope it properly and come back with a price, not a range. If an off-the-shelf tool would do it for a fraction, we will tell you which one.
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