An AI coding agent that writes code is accountable for nothing: your vendor is the one who has to be, contractually. That's the question most executives forget to ask in a sales meeting, even though it determines everything else. The word "agent" has shown up in every tech vendor's pitch deck over the past eighteen months, often describing wildly different things.
- ⚠️ Chatbot in disguise, an AI agent that neither plans nor executes actions is just a chatbot dressed up as a product.
- 🛠️ Blurred accountability, if nobody knows who answers for a bug an agent produced, the contract is incomplete.
- 📊 Market under pressure, Gartner forecasts that over 40% of agentic AI projects will be abandoned by 2027, for lack of demonstrated value.
- 🔑 The right question, always ask who reviews the code before it ships to production, not just who wrote it.
The problem isn't AI itself. It's the deliberate fog some vendors maintain between "we use AI" and "we understand what that means for accountability, oversight and delivered quality". Here are the five signs that give away a vendor riding the buzzword without mastering the technical reality behind it, along with the precise questions to ask in order to expose them in a meeting.
1. They're selling you a chatbot repainted as an AI coding agent
The first sign is about terminology, and it says a lot about the rigour of everything else. An AI agent, in the technical sense, perceives a context, plans a sequence of actions and executes them with minimal human supervision. A conversation with ChatGPT or Claude that answers a question isn't an agent: it's a chatbot.
Jeff Su, a content creator specialising in AI tools, sums up the distinction in his video AI Agents, Clearly Explained: a large language model produces an output from an input, full stop, whereas an agent has to reach information and tools it doesn't natively own in order to act autonomously. Dan Martell, in You're Not Behind (Yet), puts it even more simply: a conversation is like a meeting, an agent is like an employee. The chat answers, the agent runs an entire workflow.
How do you spot the confusion in a meeting?
Ask a precise question: "when your agent hits a case it has never seen, what does it actually do, with no human intervention?" If the answer always comes back to "we rerun the prompt" or "we tweak the instructions", you aren't dealing with an agent that plans and acts, but with a chatbot someone queries by hand. There's nothing wrong with using a chatbot internally, but selling it as an autonomous AI coding agent is pure packaging.
2. They want to automate without ever having the generated code reviewed
Even when the terminology is right, the real danger starts when a vendor proposes letting an agent run unsupervised on code headed for production. A developer described this exact situation on r/developpeurs: in their small team, a senior consultant billed to improve the architecture wanted to put Claude on autopilot around the clock to read tickets, generate code and never have it reviewed again, "thanks to safety mechanisms that guarantee quality".
The developer, for their part, describes their own practice: they supervise the LLM on the tickets they handle, break tasks down precisely, decide on the implementation, and review everything systematically. That's exactly the difference between serious use of AI and a bet on luck. A safety mechanism that guarantees quality without ever having the result reviewed simply does not exist in 2026, whatever model you're using.
Why is review still non-negotiable?
An AI coding agent can produce syntactically correct code that still fails on architecture, security or edge cases, precisely the areas generative AI handles worst according to IBM, which points out that building a reliable agent demands deep skills in AI, machine learning and software engineering, not just a subscription to a tool. If your vendor can't describe their review process line by line, they probably don't have one.
3. They can't answer "who pays when the agent takes down production"
This is the question that most often leaves an unprepared vendor stammering, and that's exactly why it should come first in an IT audit. When a bug produced by an AI agent brings down a live service, who takes on the fix, out of which budget, and within what contractual deadline?
A serious vendor has a written answer, usually a clause distinguishing AI-generated code from hand-written code, with a documented review obligation before merge. A vendor who's bluffing answers with a platitude along the lines of "we stand behind our deliverables", without ever spelling out the mechanism. Full disclosure: I run an offshore software company that sells AI-augmented Vietnamese developers, so I'm biased on this topic, but that's also what lets me see exactly where sales promises come off the rails. I've written elsewhere about who should pay when AI-generated code breaks in production, and the short answer is: always the vendor, never "the AI".
Which clause should you demand in a development contract?
Insist on an explicit line in the specification: the vendor commits to identifying code generated by an AI agent, documenting its human review, and taking on the fix under normal warranty, with no different treatment from hand-written code. If the vendor refuses that clause, it's because they have no oversight process to document.
4. They confuse one developer's speed with the whole team's performance
On this specific point, a real gap separates the sales pitch from the ground truth. Maximilian Jesch, product manager on IBM's AI-assisted development tool used by 80,000 developers, explains it in a Q&A session on r/u_ibm: almost every developer already uses AI tools and is individually faster, but most large companies still can't translate that into measurable delivery metrics. Individual gains don't automatically turn into team gains.
A vendor selling you an immediate headcount reduction thanks to AI agents ("we'll deliver with half as many developers") is skipping that step. On r/webdev, developer George Hotz is quoted claiming that the adoption of AI agents in software development could turn out to be "one of the most costly mistakes in the field's history". I don't share that total pessimism: in my view, a well-equipped senior developer genuinely does ship faster than before, and I see it on my own teams. But individual speed never removes the need for organisation, tests and real code review.
"AI doesn't replace good developers, it increases their output. A product generated fast with no technical control can cost far more to repair than it would have cost to build properly from the start."
Vincent Roye, September 2026
Why is team size still a poor indicator?
The AI agent market reached 7.6 billion dollars in 2025 and is expected to grow 49.6% a year through 2033 according to DataCamp, a pace that mechanically pushes vendors to pitch speed rather than reliability. The number of developers assigned to your project tells you nothing about the level of oversight in place. Ask instead: how much human review time per line of generated code, and by whom.
5. They have neither an oversight method nor a budget line for testing
The last sign is often the easiest to verify factually: ask to see the test pipeline applied to the code produced by the vendor's AI agents, not just to hand-written code. A well-structured vendor distinguishes the two and applies at least equivalent test coverage to generated code, because that's exactly where the most expensive mistakes hide.
On Reddit, a discussion about the launch of Meta's Muse Code, an agent designed to write and organise code autonomously, raises the right question without answering it: the battle is no longer about model quality, but about the ability to chain complex tasks end to end without supervision. That's precisely the terrain where an under-equipped vendor gets caught out, often six months after delivery, when the accumulated technical debt becomes visible.
On golivesoftware.co, the article on offshore software development in Vietnam remains one of the most-read on the blog, with 458 Search Console impressions over the last thirty days: a modest but clear signal that the question of supervising AI in offshore development already matters to executives drafting their specifications.
What does the price your competitors pay tell you here?
Before writing this article, I looked at what competitors actually pay to show up on these queries in France. The keyword "externalisation informatique" shows an average cost per click of 30.73 dollars for 320 monthly searches, "prestataire informatique" climbs to 18.39 dollars for 880 searches, and "audit informatique" sits at 10.68 dollars for 590 searches. A cost per click of 30 dollars is what consulting firms are willing to pay for a single visitor still weighing up several vendors.
That figure alone is reason enough not to rush into the first sales proposal that mentions AI agents. The market knows this decision is expensive to get wrong, and it invests accordingly to catch your attention at the right moment. You have every reason to do the same on the verification side.
| What to check | Serious vendor | Vendor to avoid |
|---|---|---|
| Definition of "agent" | Distinguishes agent from automation, concrete examples | Uses "AI agent" as a synonym for "AI" in general |
| Review of generated code | Documented process, human review before merge | "Our mechanisms guarantee quality" with no detail |
| Accountability for bugs | Written clause covering AI-generated code | Vague answer like "we stand behind our deliverables" |
| Speed argument | Quantified on the project, not the individual | Promise to halve the team from day one |
| Tests on AI code | Coverage equivalent to manual code | No distinction mentioned |
SOURCE: GoLive Software field experience and analysis of the sources cited in this article · UPDATED 09/2026
The market knows this decision is expensive to get wrong: Gartner forecasts that over 40% of agentic AI projects will be abandoned by the end of 2027, for lack of demonstrated business value or because control costs were underestimated. That's exactly the terrain where an unprepared vendor gets caught out. A vendor with genuine command of AI coding agents will never sell you a miracle cost reduction without spelling out who reviews what, nor a delivery pace that dispenses with testing. If anything it's the opposite: the more seriously a vendor uses AI, the more precise they should be about their guardrails, because they genuinely need them day to day.
To go further on what separates quick prototyping from a genuinely maintainable product, I've written about the difference between vibe coding and supervised development in offshore teams, and the fundamental distinction between an AI agent and a developer. The blog ai-first.fr covers the same subject from the business adoption angle, if you're looking for "how to roll out AI internally" rather than "how to choose a vendor who already uses it".
The right instinct stays the same whichever vendor you pick: ask the five questions listed here before signing, demand the answers in writing in the specification, and be wary of any speed promise that doesn't come with a detailed oversight method. A vendor who answers these five points clearly deserves your trust. One who dodges deserves a lot less.
Frequently asked questions
What exactly is an AI agent in software development?
An AI coding agent is a system able to perceive a context (a ticket, a specification), plan a sequence of actions and execute them with minimal human supervision, for example writing code, running tests and fixing the errors it finds. It differs from a plain chatbot, which answers a question without acting autonomously on an external system.
Does a vendor using AI agents necessarily charge less?
Not necessarily, and be wary of any immediate price cut promised purely on the back of AI. The real gains come from better work organisation (task breakdown, systematic review, automated tests), not from the mere presence of an agent in the production chain.
How can you verify that a vendor really supervises AI-generated code?
Ask to see their written code review process: who reviews, against what criteria, and within what deadline before a change ships to production. A vendor who can't describe that process precisely, or who answers with a generic line about "safety mechanisms", probably has no documented method.
Should you demand a specific clause on AI-generated code in the contract?
Yes. The clause should state that the vendor identifies code produced by an AI agent, documents its human review, and takes on the fix under warranty on the same terms as hand-written code. Without it, accountability for bugs stays blurred and hard to enforce after the fact.
Do AI agents replace junior developers at an offshore vendor?
No, they change the nature of the work more than they replace anyone: a well-mentored junior spends more time reviewing and testing than writing from scratch. The skill that stays rare, and therefore drives a team's value, is the ability to judge whether the agent's output is correct, not the speed at which it was produced.
Vidéos YouTube
- AI Agents, Clearly Explained — Jeff Su
- You're Not Behind (Yet): How to Build Your First AI Agent (Full Guide) — Dan Martell
Discussions Reddit
- Field report: a consultant wants AI everywhere and full development automation — r/developpeurs
- I'm Max, a Product Manager on IBM Bob — r/u_ibm
- "I'm calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field's history." - George Hotz — r/webdev
- Meta launches Muse Code, an AI that no longer just suggests code, it can build software autonomously — r/HighTechFR
