Oracle has integrated ChatGPT and Codex into its workflows, transforming tasks that once took days into minutes. Over a hundred thousand employees now use these tools across various departments, from recruitment to engineering. For beginners learning to build software with AI, Oracle’s approach offers practical insights into how AI can streamline complex processes.
Recruiting research made efficient
Oracle’s talent acquisition team built a talent market intelligence tool using ChatGPT Work. This tool takes a job description, researches comparable roles, benchmarks compensation, and assesses the talent pool across relevant locations. What used to take 2–4 days now takes just 15–20 minutes.
Tip
This tool ensures consistency in the recruitment process. Every hiring manager receives the same quality of data and insights, regardless of the recruiter they work with.
Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition at Oracle, notes, “We’ve gone from zero to a hundred. Now we’re able to sit down and prep for about 15 to 20 minutes using the tool that we’ve built using [ChatGPT] Work.”
Faster answers for business users
The Oracle Applications Lab team created an ontology of the company’s objects, relationships, and rules. This allows business users to describe an outcome in plain language, which Codex then turns into a reliable SQL query. The system gathers the necessary information and returns an analysis, report, or application almost instantly.
Richard Lam, Group Vice President at Oracle Applications Lab, explains, “Business users now describe the outcome they want instead of hunting for a report. That is a major shift. I would even call it a business transformation.”
Incident resolution in production engineering
Site reliability engineers (SREs) use Codex to gather relevant context about incidents and automatically pull up the right playbook. This reduces the time spent hunting for information and allows SREs to focus on guiding decisions. A typical simple incident that used to take an hour to resolve can now be handled in minutes.
Leadership lessons
Oracle’s experience with AI offers valuable lessons for beginners:
- Provide correct guardrails: Ensure your system design, architecture, and security are robust. Codex needs the right structure to produce reliable code.
- Use prototypes instead of specs: Instead of writing detailed specifications, create prototypes to communicate your ideas.
- Own the code: Work alongside Codex to ensure the code remains maintainable. Unattended code can quickly become unmanageable.
What’s next for Oracle
Oracle continues to integrate AI across its operations. Employees use ChatGPT and Codex for countless tasks, shifting how the company operates. Barry Shilmover, Vice President and Technical Advisor to the CIO, sums it up: “I don’t know what the answer is because I don’t know what my next problem to solve will be. I just know that one of the first things I’ll do is I’ll leverage Codex to do that.”
For beginners, Oracle’s approach demonstrates the transformative potential of AI in software development. By focusing on outcomes and leveraging AI tools, you can streamline complex tasks and improve efficiency.
Read next
- What ML Drift Means for Beginners Building AI at the Edge
- What Asana’s 76x Cost Cut with GPT-6.1 Sol Means for Beginners Building AI
Want to try all of this hands-on? Start with the free Claude Code from Zero course.
Source
Based on OpenAI’s announcement, “How Oracle turns days of work into minutes with ChatGPT and Codex”. Written for people learning to build with these tools.