ChatGPT Codex & Co.: What AI-Assisted Software Development Delivers Today
Digital Airways·
«Our software is now built with AI» is a sentence many Swiss SMEs hear from software providers these days. What exactly lies behind it often stays vague. Is this the same autocomplete used when writing an email? Or does the AI actually write the software on its own?
This article puts what tools such as ChatGPT Codex from OpenAI, Claude Code from Anthropic, or agentic features in modern development environments genuinely deliver in 2026 into perspective – vendor-neutral and without marketing exaggeration. And what it means for you if you do not have your own development team, but are planning a custom solution or choosing a software partner.
Three generations of AI support in programming
Not every «AI in code» is the same tool. It is worth distinguishing three levels.
Code completion. The oldest form suggests individual lines or short blocks while someone types – similar to text suggestions on a smartphone. It saves typing but makes no independent decisions.
Chat-based assistance. A developer asks the AI a question or requests a code snippet and inserts the result manually. Useful for explanations and individual building blocks, but a human stays in control at every step.
Autonomous coding agents. This is the current level, to which ChatGPT Codex and Claude Code belong. Such an agent receives a task in natural language, then independently searches the project, reads the existing code, plans several work steps, implements them, runs tests and corrects itself when something fails – without anyone dictating every line individually.
When people speak of «AI-assisted software development» today, they usually mean this third level. It differs from the first two not gradually but fundamentally: the work shifts from «writing code» to «describing, checking and taking responsibility for a result».
What agents such as ChatGPT Codex can realistically do today
Public debate swings between two extremes: «AI will soon program everything itself» and «this is just hype». Neither matches reality. A more realistic picture emerges when you distinguish by type of task.
| Task type | Performance today |
|---|---|
| Recurring patterns (forms, lists, standard views) | Very strong – often in a fraction of the previous time |
| Understanding and documenting existing, unfamiliar code | Very strong – especially valuable with legacy systems |
| Narrowing down bugs and writing tests | Strong |
| Adding new features to an existing system | Solid, when the task is clearly described |
| Architecture and data-model decisions | Weak – remains the task of experienced developers |
| Knowing your business’s special rules | None – this knowledge exists in no code |
The common thread: the more a task consists of known patterns, the stronger the effect. The more it demands judgement and contextual knowledge about your business, the more stays with humans. This holds regardless of whether a team works with ChatGPT Codex, Claude Code or another agent – the tools differ in detail, not in this underlying logic.
What this means for you as a client, even without your own developers
You do not need to operate these tools yourself to benefit from them – but it is worth understanding what they change about a project.
Custom solutions become more affordable. Projects that previously failed on development cost are often viable today. A tailor-made application for a single process has thus become a genuine option for far more businesses – not only for large companies with their own IT budget.
You see something working sooner. A first functional version often appears in days rather than weeks. This is an advantage you should actively use: the earlier you can touch and comment on a prototype, the more cheaply misunderstandings can be corrected.
The tool does not replace diligence. The difference between a solid and a fragile solution does not arise from typing, but from requirements clarification, architecture, security review and code review – exactly where an agent contributes least. A provider who develops «AI-assisted» is therefore not automatically faster or cheaper if these steps are missing.
How ChatGPT, Claude and Microsoft Copilot generally suit different tasks is covered in our article Claude, ChatGPT & Copilot Compared. How a concrete development process with a coding agent runs in practice is described in Building Software Faster with Claude Code and AI Coding Agents.
Questions worth asking a software partner
If a provider advertises AI-assisted development, these four follow-up questions are more useful than asking which specific tool is used:
- Who reviews the generated code before it goes live? A clear answer names a person and a process – not «the AI handles that».
- How are requirements captured before the agent starts? A vaguely formulated task leads an AI agent to a wrong result just as reliably as it does a human.
- What happens to your code and your data? Reputable providers use paid business plans, where inputs are generally not used to train the models, and can explain this on request.
- Who owns the code afterwards, and who can develop it further? Software built quickly needs to be operated and maintained just like any other.
A provider who can answer these four questions concretely has usually understood that the agent is a tool – not a substitute for a well-thought-out project.
Limits that still apply in 2026
For all the acceleration, the limits remain the same as for any tool without insight into your business:
- Agents do not know your business’s exceptions – for instance why a particular order always needs two approvals.
- They often make architecture decisions that are plausible but do not look two to three years ahead.
- They appear confident even when the result is flawed – one reason review is not an optional step.
- They are no substitute for a conversation on site, where someone sees how work actually happens in your business.
Conclusion
ChatGPT Codex, Claude Code and comparable agents have genuinely changed software development in 2026, but selectively: they considerably speed up routine work and known patterns, while architecture, judgement and responsibility remain with humans. For Swiss SMEs this means above all one thing: a custom solution is achievable faster and more cheaply today than two years ago – provided the partner takes the steps before and after just as seriously as the tool itself.
Are you wondering whether a tailor-made application is worthwhile for one of your processes? In a free initial consultation we look at your workflow and tell you honestly what is realistically achievable today.
