What should I charge for building a back-end AI system in Python to replace NAN with open AAI integration, self-hosted APIs, databases, async workflows, self-auditing logic, mainly building our own core, quoted at $7,000? Should I charge more, hire or not, and where?
Great profile pick. I see a make.com scenario watching type form there. How much would I charge for this? I think you're putting the cart before the horse. The reason is you're asking how much I charge without clearly delineating who you're building this for and what their needs are. Generally, the way I build things out, and the way I build scopes and pricing documents as a consultant, is to always start with client needs first and then work backwards. So my approach isn't 'what goes into this project?' but 'what are the client needs? How much money is the client currently spending on their crappy solution? What does it do to their project management, lead generation, team unity, and so on? What headcount are they managing as a result? What's their payroll? How big of an issue is this to solve today? What are the at least bird's-eye view financials of the company? If we don't solve this today, is this an existential risk for the business? I try to figure all this out because it helps inform what the client is willing to pay and what a reasonable price would be. This isn't always me trying to squeeze every last dollar out of them; often I charge them what would be a fair price given the return on investment. It also lets me ask whether this is even the right solution for them, or if they're kind of putting the cart before the horse. I don't know exactly how much I charge for this. The question I'd look to answer is what need or problem does this solve and how big a financial issue is that problem? If you're quoting $7,000, I'd make sure the system delivers at least $20,000 to $25,000 worth of value. Bigger projects like this typically have more issues during building and implementation. So instead of charging 30% of the value as I normally recommend, I might charge something like 20% or so.
Um, so here's the really interesting thing about what's happened over the last year or so when I started my agency: OpenAI and AI credits in general were super expensive—I was spending thousands of dollars every month on OpenAI credits for my writing business and several hundred bucks per month for things like enrichment and personalization of email first lines. Since then, costs have dropped precipitously. Where they were before versus where they are now, you can realistically run AI 24/7 on every corner of your business unless you're using the absolute best model, which is only a few percentage points better than the previous generation. You'd be spending about three bucks a month, so you can cover most of the OpenAI credits yourself. It's not like it used to be; now it's very easy and simple. If you do this, you typically avoid the rate‑limit issues I see a lot of people run into on lower‑tier accounts—OpenAI tier five is pretty trash, you might be limited to a few thousand tokens per minute, which causes problems. So OpenAI credits are a nuanced topic, but I would not charge new clients for OpenAI credits; I’d bundle all the AI fees into my pricing because I have partnerships with various providers. In your case, maybe you can’t say that yet, but if you get a partnership you could. Regarding custom tools—if it’s something like Make.com, I’d have the client pay for it, but the good news is that Make.com‑type tools usually cost under $50 or maybe under $100 a month, so it’s low enough that it doesn’t matter much. There are a couple ways to approach offers: you could swallow everything up and charge the client a slightly larger fee (the simplest, lowest‑friction approach), but that adds liability on your end and complicates handoffs—if you and the client split, how does the client get access to what you built? Do they get it or do you take it away? I prefer to have the client own most of their infrastructure, aside from the OpenAI API key, which is simple enough to walk them through in ten seconds if we ever do a handoff. That way I have zero liability, they have the accounts, and I just use their password to access them. It’s simple and easy for everybody.
Nate explains that pricing should be proportional to the value the system provides. He starts by considering where you are in your journey and what you’re optimizing for—brand, case studies, testimonials can let you charge more. If you’re just starting, focus on gaining experience and understanding the exact value you deliver, which you need to express in terms the client understands: hours saved and dollars saved. In discovery, ask the right questions to get those figures. Then make it a no‑brainer: for example, a system saving 5 hours a week when the client values an employee’s time at $100/hour saves $500 weekly; over months that could be $50k, so you could charge $7–$15k (or even more) because the client is saving $35k. You have to frame the benefit in the client’s language at a high level. The other speaker agrees, saying Nate hit on many important concepts—packaging of the service, the provider, perceived and objective value. They then shift to a quick sponsor shout‑out for Whimo, noting how convenient and cost‑effective it is (about 30% more than an Uber but 10× safer), mention that their Instagram ads have been only for School and Whimo, and wrap up by thanking each other, saying it was a pleasure, looking forward to hanging out again, and promising to cover brand stats tomorrow.
My view on AI consulting is that there’s no real difference—it’s just consulting repackaged. Whenever you see terms like AI automation, AI consulting, AI growth systems, or AI operators, they’re all the same thing; people are just trying to sell a business model and differentiate themselves in a crowded space, which in content is called packaging. At its core, this is foundational marketing: nothing has really changed since the SMMA craze; we’re still selling marketing systems, just rebranded as AI automation. Most AI automation sellers are actually selling marketing systems—content repurposing, social media automation—so it’s just repackaging. Regarding cost per acquisition for an AI agency client, it depends entirely on your lead‑generation mechanism. If you run an inbound funnel with massive distribution, your CPA is essentially just your time on new inquiries—near zero. If you’re doing Upwork applications at $2 each and need about 33 applications to land a client, your CPA is $66. If you run a cold‑email campaign spending $450 per month and sending roughly 3,000 emails to land three clients, your CPA is about $150. However, CPA alone means nothing unless you also know the order value or lifetime value of the clients. For example, if Pete’s CPA is $64 and he sells a product for $1,000 on average, his CPA is 6.4% of revenue. If Samantha’s CPA is $150 and she sells for $10,000 on average, her CPA is only 1.5% of revenue. You also need to factor in referrals and other variables to judge which business is truly more successful. After that, I mention I’m running out of time because I have a podcast with Jack Roberts. We’ve become fast friends after initially being hesitant to collaborate due to a scarcity mindset. We now chat regularly, run a podcast together, and plan to play video games like Halo, Fortnite, or League of Legends while streaming, which I think will be fun and more engaging. I’m even considering buying a gaming computer just to stream with Jack weekly. Ultimately, I’m moving into Twitch streaming to play video games all day.
ai consultingcost per acquisitionltvlead generation
You need to charge more, proportional to the value you provide. If you solve a $10,000-per-month money need, you can reasonably charge 30%–50% of that, i.e., $3,000–$5,000 per month. From the business owner's perspective, this is a simple ROI: hiring you should yield about a 3x return, acknowledging some uncertainty between the $3,000 fee and the $10,000 value. You can charge a proportion of the value delivered. Focus on profitability by charging significantly more for your services. On the expense side, avoid accruing unnecessary liabilities. Many who sell cold email or lead generation merely wrap a cold email product with minor added value and then bundle in unnecessary costs like email inboxes, platform fees, and domains. Instead, have the client pay for some of those costs so you're not left liable if you don't deliver results or fulfill guarantees. For example, one consulting client guaranteed a client $10,000 but only sought payment after delivering that amount; due to a long sales cycle, the client didn't receive the $10,000 for four or five months, while the consultant's ongoing email costs were $600–$700 per month, totaling $2,400–$2,800 over that period, yielding a 76% margin after COGS. Don't put yourself in that situation.