ChatGPT and Codex

The Practical Question

A founder is deciding what to delegate to AI and what evidence to require before accepting the result.

The immediate question is chatgpt and codex. The technical label matters only because it changes a product decision, a responsibility, or the evidence required before launch.

What a Sound Approach Establishes

Start with the product consequence, then choose the simplest technical treatment that protects it. A longer tool list is not a stronger plan.

For this decision, the useful standard is that the output satisfies explicit constraints and survives review outside the conversation that produced it.

• Make the decision explicit: Choose the surface according to whether the desired outcome is reasoning, a reusable artefact, or verified codebase change.
• Ask what evidence would show that the chosen approach works.
• Name the person or provider responsible when the approach fails.
• Record the result in the AI work brief, review record, and acceptance criteria.

A Decision Framework

Choose the surface according to whether the desired outcome is reasoning, a reusable artefact, or verified codebase change.

The principal risk is that a persuasive conversation is mistaken for repository-aware implementation evidence. This does not require the most expensive possible solution. It requires the consequence to be understood and the control to match it.

1. Describe the user or business outcome that must be protected.
2. Identify the most credible failure and its consequence.
3. Compare the simplest adequate approach with one realistic alternative.
4. Set a review point for when the decision may need to change.

What Confidence Should Be Based On

Warning Signs

• Nobody can explain how chatgpt and codex changes a user or business outcome.
• The proposal does not address this risk: a persuasive conversation is mistaken for repository-aware implementation evidence.
• The only evidence is a successful demonstration of the easiest path.
• The decision has no named owner, boundary, or review point.
• A provider-specific feature is being mistaken for a permanent product requirement.

Questions to Ask a Consultant

• What decision are we making about chatgpt and codex?
• Which user or business outcome does the recommendation protect?
• How have we reduced or accepted this risk: a persuasive conversation is mistaken for repository-aware implementation evidence.
• What evidence can I review without relying on the original implementer?
• What is deliberately deferred, and when will it be reconsidered?
• Who owns the accounts, data, documentation, and recovery process?