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AI systems and automation / OpenAI Codex

Service scope

OpenAI Codex implementation for recurring business tasks

For teams that want Codex to run a recurring task they can rely on: a scheduled report, a data job or an integration inside an existing tool. We choose the right setup, define what it may read and change, test it on real examples and hand over a routine your team owns.

From idea to routine
From idea to routineThe first engagement takes one task from a promising demo to a routine your team owns.01Pick the setup02Define the task03Test and handover
From idea to routineThe first engagement takes one task from a promising demo to a routine your team owns.01Pick the setup02Define the task03Test and handover
The first engagement takes one task from a promising demo to a routine your team owns.
  1. Pick the setupSupervised, scheduled or integrated
  2. Define the taskInputs, permissions and an owner
  3. Test and hand overChecked runs and a written routine

The problem

From a promising demo to a dependable job

Codex can read files, run code and use tools, which makes it useful well beyond writing software. Turning that into a job the business relies on takes a clear task, the right permissions and a check before results reach anyone.

Without that setup, results vary from run to run, nobody owns failures, and leadership cannot tell what the automation delivered.

Client work

Built with Codex for an IT services startup

1page leadership reads each week, in place of a manual report

A growth dashboard for an AI-written blog

An IT services startup needed to see whether its automated blog was working. We built a dashboard that OpenAI Codex keeps up to date from Search Console and GA4, showing traffic, search clicks, top pages, conversions and leads by source, week on week. It replaced the manual weekly report, and leadership now reviews growth every week.

An IT services startup's leadership team; 2026

Outcome as reported by the client. Traffic and lead figures are not published.

Published case study

Read the case study

How it works

Four steps from idea to routine

  1. 01

    Choose the setup

    A supervised workspace, a scheduled job or an integration inside an existing tool. We explain what each needs to run before anything is built.

  2. 02

    Define the task

    Inputs, data sources, output format, permitted actions and the person who owns each result.

  3. 03

    Run a checked pilot

    Real examples, including messy and failing ones. Outputs are reviewed before anyone relies on them.

  4. 04

    Hand it over

    A written routine: how to run the task, check the result, recover from a failure and change the setup safely.

What you receive

A job your team can own

01 / Design

Task definition

The setup chosen, the data it reads, the output it produces, its permissions and its owner.

02 / Build

Working pilot

The running job or integration, with test examples and the checks that cover failed or blocked actions.

03 / Handover

Operating routine

Where it runs, how it signs in, what it costs to run, where its logs are and how to recover from a failure.

Where to start

Good candidates for a first pilot

Good candidates for a first pilot
TaskWhy it suits a first pilot
Leadership and growth reportingFixed sources such as Search Console and GA4, and an output that is easy to check.
Scheduled data jobsClear inputs and a result a person can verify.
Website and content operationsChecks with clear pass and fail conditions.
An action inside an existing internal toolOne defined action with an owner and an approval step.

How engagements work

A written scope and a fixed quote before any build

The founder of AGI Technologies leads every engagement, from the scoping call to the handover.

Every engagement starts with a written scope: the task, what you receive, how the result is judged, the running costs and who maintains it after handover.

The first pilot has a fixed quote, agreed before any work starts. It covers one scheduled task, so you can judge the result before anything expands.

Questions

Before a scoping call

Do we need a custom application?

Usually not at first. A scheduled job or a supervised workspace covers most first tasks. An integration inside your own tool comes when the task needs it.

Is this the same as using the OpenAI API?

Codex adds an agent that can work with files, code and tools. If a single API call or a fixed workflow does the job, we recommend that.

Can it update our business systems?

Only within permissions you approve. We start with read access and reviewable outputs, and add write actions one at a time.

Where does it run once it is live?

On a person's machine, on a schedule, or inside a production system. Each needs different access, hosting and support, and the written scope says which one you get and who maintains it.

How is the work priced?

After the scoping call you receive a written scope with a fixed quote for the first pilot. Running costs such as hosting and software accounts are listed separately in the same scope.

Product references

OpenAI's documentation

Checked on 14 October 2026. Codex is an OpenAI product. AGI Technologies is an independent consultancy with no partnership or endorsement claimed.

Scope the next step

Pick the report or job that repeats

Tell us which task comes back every week, where its data lives and who checks the result. On a 30-minute call we scope a first Codex setup and a pilot.