Founder of Goodspeed
Hiring an agency to build with Codex and other AI coding agents should be one of the highest-leverage decisions you make this year. Done well, you get production software faster and cheaper than the old way. Done badly, you get a confident-looking prototype that falls apart the moment real users touch it, and a bill for the privilege.
The difference usually is not luck. It is a handful of avoidable mistakes that buyers make again and again because the market is new and the signals are unfamiliar. We are an AI engineering team that ships production software with coding agents like Codex and Claude Code, and we see the aftermath of these mistakes when clients come to us to fix work that went wrong elsewhere.
This is the honest list. Avoid these and you will already be ahead of most people hiring in this space.
Hiring on hype instead of evidence
The most common mistake is buying the story. An agency that talks fluently about Codex, agents, and the future of software can sound impressive without having shipped anything durable. Hype is cheap right now, because the vocabulary is new and most buyers cannot yet tell a real practitioner from a good talker. If you choose on enthusiasm alone, you are gambling.
The fix is to demand evidence over narrative. Ask to see live products with real users, not decks and not demos. Ask what happened after launch, whether the software is still running, and what broke along the way. Practitioners who have genuinely shipped will have specific, slightly unglamorous stories. People selling hype will keep returning to the vision, because the vision is all they have.
Choosing on price alone
Because agents make building faster, a wave of very cheap offers has appeared, and the temptation to take the lowest quote is strong. The problem is that cheap agent-built software often means unreviewed agent output shipped straight to you. It looks finished. It is not. The corners that were cut are invisible until the system is under load, handling real data, or being changed six months later.
Price should be weighed against total cost, not sticker cost. A cheap build that has to be rewritten is the most expensive option available, because you pay twice and lose the time in between. Look at what is included: engineering rigour, testing, security, documentation, and handover all cost something, and their absence is exactly what makes a suspiciously low quote possible. Judge the whole package, not the headline number.
Accepting demos as proof of production capability
A polished demo proves that an agency can make something look good in a controlled setting. It proves very little about whether they can run software in production, where the inputs are messy, the traffic is uneven, and failure has consequences. Agents are especially good at producing things that demo beautifully and behave badly under real conditions, which makes this trap easy to fall into.
Insist on production evidence. That means live systems you can use, uptime and reliability they can speak to, and a clear account of how they handle errors, edge cases, and scale. Ask what happens when something goes wrong at two in the morning. An agency that has actually operated software will have answers. One that only builds demos will change the subject back to the interface.
Ignoring engineering rigour underneath the agent
The biggest misconception is that using Codex removes the need for engineering discipline. The opposite is true. Agents generate code quickly, which means they also generate mistakes quickly, and without rigour those mistakes ship. The teams worth hiring have built the scaffolding that keeps agent output honest: automated tests, evaluation harnesses, type safety, code review, staged rollouts, and monitoring.
When you are vetting, ask directly how they stop the agent from shipping something wrong. A serious answer describes real guardrails and a review culture where a human owns every line that goes live. A weak answer treats the model as trustworthy by default. If nobody on the team is rigorously reviewing what the agent produces, you are not hiring an engineering team. You are hiring a very fast way to accumulate technical debt.
Leaving ownership and IP unclear
Ownership is where a lot of agent-built projects quietly go wrong. You need to know that you own the code, the accounts, the infrastructure, and the credentials outright, with nothing locked behind the agency's private tooling or accounts. Some setups leave you unable to touch your own software without going back to the people who built it, which is a weak position to be in.
Settle this before any work starts. Get it in writing: full IP transfer, direct access to every repository and service, and no hidden dependencies on proprietary wrappers you cannot see. Ask what handover looks like on the day the relationship ends. If the answer is vague or the agency seems reluctant to give you full control, treat it as a serious warning. Software you cannot own or move is a liability, not an asset.
Skipping the maintenance conversation
Buyers often focus entirely on getting to launch and forget that launch is the beginning, not the end. Software changes, requirements shift, dependencies age, and AI-built systems in particular need ongoing attention as models and tooling evolve. An agency that only talks about the build and goes quiet on what comes after is setting you up for a cliff.
Ask what post-launch support looks like before you sign. Who fixes things when they break, how quickly, and on what terms. How do they monitor the software once it is live, and how do improvements get made over time. The agencies worth hiring treat maintenance as a first-class part of the work, because they know that is where software either compounds in value or slowly rots. Get clarity here or you will feel the gap later.
Assuming AI speed means lower quality
There is a flipped version of the price mistake, where buyers assume anything built quickly with agents must be worse, and either avoid it entirely or accept sloppy work as inevitable. Neither is right. Speed and quality are not opposites when the process is disciplined. A good team uses the agent to move faster and spends the time saved on testing, review, and refinement.
The mistake is not expecting quality. It is accepting the excuse that AI-built work is naturally rougher. Hold the same standard you would for any software: it should be reliable, maintainable, secure, and correct. The right agency will meet that standard and deliver faster because of the agent, not despite it. If someone uses AI as a reason to lower the bar, they have misunderstood the tool.
Not checking who actually does the work
Some agencies sell you senior expertise and then hand the work to whoever is available, with the agent papering over the gaps. Because agent output can look uniform regardless of who prompted it, this is easier to hide than it used to be. You can end up with software nominally built by experts but actually assembled by juniors leaning on the model with little oversight.
Ask who will be on your project, what their experience is, and how the work is reviewed. Meet the people who will actually build, not just the person who sells. The presence of the agent does not remove the need for experienced engineers; it raises it, because someone has to exercise the judgement the agent lacks. Know whose judgement you are actually buying before you commit.
Vague scope and no definition of done
Agent-accelerated projects can drift badly when the scope is loose, because it is easy to keep generating more without ever finishing anything properly. If nobody has agreed what done looks like, you get an ever-growing pile of half-features and no working whole. The speed of the tool amplifies the chaos of unclear direction.
Insist on a clear scope, defined milestones, and an explicit definition of done for each piece of work. Good agencies will push you towards this because it protects them as much as you. It also gives you a way to check progress against something real rather than a feeling that things are moving. Clarity up front is the cheapest insurance you can buy on any build, and it matters more, not less, when the work moves fast.
Believing in Codex certifications that do not exist
Because buyers are looking for a shortcut to assess capability, some agencies imply official credentials or certifications in Codex. Be clear with yourself here: there is no formal Codex certification. Anyone leaning on an official-sounding qualification is either mistaken or embellishing, and both should make you look more carefully at the substance behind the claim.
Assess genuine expertise instead. That is production evidence, clear engineering practices, honest answers about limitations, and a track record of software that has survived real use. Those signals are harder to fake than a badge and far more predictive of whether the agency can actually deliver for you. Do not let the absence of a tidy credential push you towards a fake one. Read the real work.
How to avoid all of this
Every mistake on this list shares a root cause: choosing on surface signals instead of substance. The correction is consistent. Ask for production evidence, insist on engineering rigour, settle ownership in writing, get clarity on maintenance and scope, and check who is actually doing the work. Weigh price against total cost, and ignore credentials that do not exist.
None of this is exotic. It is the same diligence you would apply to any serious supplier, adapted to a market where the tooling is new and the hype is loud. Do it properly and you dramatically improve your odds of hiring an agency that ships software you can rely on and keep. Skip it and you are trusting a story. In this market, the story is the most abundant and least reliable thing on offer.
Conclusion
The mistakes that sink Codex agency hires are almost all avoidable: buying hype, chasing the cheapest quote, mistaking demos for production, skipping engineering rigour, leaving ownership unclear, and ignoring what happens after launch. Underneath every one of them is the same fix, which is to judge substance over surface and demand real evidence before you commit.
Do that and you will end up with a partner who ships software that works, that you own outright, and that keeps earning its keep long after the build is done.
If you want a team that ships production software with AI coding agents, see our AI work, or book a free call with our AI engineering team.
Written By
Founder of Goodspeed