Automating Incident Response with AI Agents: Role-Division Lessons from SB OAI Japan's Codex Hackathon Win

Automating Incident Response with AI Agents: Role-Division Design Lessons from SB OAI Japan's Codex Hackathon Win

Drawing on the case of SB OAI Japan, which won a hackathon hosted by OpenAI, we explain—for Philippine sites—a design that automates incident response by dividing roles between AI and people.

---

Part 1: Why This Matters

Step 1: The Philippine Business Context (3 min)

The Philippines has many shared-services operations (organizations that gather common work at a single site) and BPO sites (local outsourcing operations) run by Japanese firms. At sites in Manila and Cebu, the first response to a system failure that occurs at night or on weekends is a major challenge. You can't exactly wait for the person in charge in Japan to wake up; local staff must carry things from root-cause investigation through to recovery on their own.

What is drawing attention here is automating incident response using AI agents (AI programs that take instructions from people and advance work autonomously). The prototype system SB OAI Japan won a hackathon with was designed for exactly this "nighttime first response," and there is potential to apply it to the operations of Philippine sites.

There are three reasons this theme matters for Japanese firms. First, even at small and mid-sized sites with little slack in Filipino staff and budget, handing investigation to AI lets you maintain the quality of the response. Second, because AI takes over the burden of reading English technical logs, the cost of training local staff goes down. Third, the role-division concept of having a human check the code the AI wrote can be applied directly to development outsourcing projects in the Philippines.

A scene of sharing this with a colleague at a Manila office "At our Makati office, while having coffee with Josephine after her night shift, she said to me, 'I got an error alert at 2 a.m. last night, and just reading the logs took me until morning.' I remembered the SB OAI Japan article I'd read in Tokyo and said, 'Apparently there's a setup where an AI agent does the root-cause investigation and the human just makes the final call.' Her expression changed and she leaned in: 'I'd love to try that at our site, too.'"

Step 2: Key Points from the Source Article (5 min)

We extracted only the facts written in the source article and created our own summary table.

Source: SoftBank News — "Building an agent on a 'programming is AI, checking is human' division of roles: SB OAI Japan wins OpenAI-hosted hackathon" (May 22, 2026)

This table was created for study purposes based on facts from public information. Please check the linked source article above for details.

Related: See How AI Agents Help Philippine Businesses Automate Internal Operations for a detailed discussion.

Step 3: Comprehension Check (5 min)

Q1. When was the Global Codex Hackathon held in Tokyo?

Hint: It's a date in April 2026. You can confirm it in the Step 2 table.

Q2. Name the three members of the SB OAI Japan team.

Hint: The names are stated in the source article. Confirm them, including how they're read.

Q3. What is the name of the certification participants were required to earn in advance to enter the hackathon?

Hint: A certification showing you can use Codex in practice.

Q4. In what situation does the AI agent SB OAI Japan developed start working?

Hint: The source article says "upon receiving an inquiry."

Q5. Does the winning team's AI agent complete the fix work itself, or handle up to just before that work?

Hint: The source article says "up to the point where it can begin the fix work." Read it with the role division in mind.

---

Related: See How AI Agent Development Helps Philippine Businesses Automate Beyond Prompt Engineering for a detailed discussion.

Part 2: Putting It Into Practice

Step 4: Rollout Steps in the Philippines (10 min)

We have organized into five stages the steps for adopting an "AI investigates, human checks" division of roles at a Philippine site.

Step 5: Common Mistakes and How to Avoid Them (5 min)

Mistake 1: "Dumping everything on the AI and skipping the human check"

Bad example: After adopting an incident-response AI agent, local staff—because they were tired—applied the AI's fix proposal straight to production, which caused a separate failure.

Good example: Create a procedure where a human always reviews the code or fix proposal the AI wrote before it goes to production. SB OAI Japan's prototype, too, is premised on a "programming is AI, checking is human" division of roles.

Mistake 2: "Sending logs to the AI without masking them"

Bad example: In a rush to investigate a failure, you sent logs containing customers' names and email addresses straight to the AI, and it later became something reportable to the Philippines' NPC (National Privacy Commission).

Good example: Add a process that redacts personal data in the logs before sending them to the AI. Check the NPC's guidelines in advance and, if needed, consult your in-house data-protection lead about how to obtain consent.

Mistake 3: "Skipping the briefing for local staff"

Bad example: The Japanese head office decided to adopt the AI agent unilaterally and made do with just sending an English manual to the Manila site. As a result, local staff felt "my job is being taken away," grew anxious, and stopped using the AI.

Good example: Hold a briefing in Tagalog or English before rollout, and carefully convey that AI is a tool to assist human judgment, not to replace it. Always set aside time to take questions, and have the local IT lead serve as a facilitator, too.

---

Part 3: Going Deeper

Step 6: Related Technical Terms (5 min)

AI agent (an AI program that works autonomously) is an AI that, to achieve a goal a person has set, figures out the steps itself and chooses among tools. For example, at a Manila IT help desk, an AI agent can receive a user's "I can't log in" inquiry, automatically check the logs to narrow down the cause, and hand a proposed response to the staff member.

Codex (OpenAI's coding-assistance tool) is an AI tool that writes and fixes program code when you give instructions in natural language. At a software development site in Cebu, a Filipino engineer can instruct it in Japanese or English to "rewrite this function to be more readable," with the human doing only the review.

Hackathon (a short, intensive development event) is an event where engineers gather for a limited time—from a few hours to a few days—to give shape to new software or ideas. A Manila IT department, too, can hold an in-house hackathon-style event once a quarter as an effort to draw out the creativity of Filipino engineers.

Monitoring data and logs (records of a system's activity) are time-series records of "when, and what" a server or application did. In Philippine call center operations, too, checking the call system's logs every day lets you catch early signs of line failures or response delays.

Role-allocation design (deciding the scope handled by people and by AI) means clearly drawing the line within a piece of work of "up to here is for the AI, and from here a human judges." At Philippine accounting shared services, a common division is to have AI handle reading receipts and drafting journal entries, with a Japanese manager giving final approval.

Step 7: Thinking About How to Apply This at Your Company (10 min)

Which parts of your incident-response flow can be handed to AI

Prompt to think about: Write out the procedure for responding to system failures that occur at night or on weekends at your Manila or Cebu site. Among them, tasks like "reading logs," "finding similar past cases," and "proposing fixes" are the parts most likely to be handed to AI. Conversely, "applying to production" and "final review of an apology letter to a customer" are parts where a human should bear responsibility.

Next action: Compile your current incident-response procedure into a single diagram, and label each step "suited to AI" or "suited to humans."

Whether to have Filipino engineers earn an AI-use certification

Prompt to think about: SB OAI Japan had every full-time employee in its engineering division earn the OpenAI Codex Practitioner Badge. In the same way, having engineers at your Philippine site earn an official certification can advance both visibility of technical skill and local-staff motivation at once. On the other hand, certification involves English exam prep and exam fees, so you need to weigh the cost-effectiveness.

Next action: Estimate the number of engineers at your site and the cost and time of certification, and decide one target to reach in six months.

Documenting "AI writes, human checks" as an internal rule

Prompt to think about: Merely sharing the role division verbally falls apart when the person in charge changes. By keeping rules such as "a human must always review code or output the AI wrote" and "review records are retained for at least six months" as internal regulations, you make it easier to maintain quality. In the Philippines, the culture of documentation and signatures is, in some respects, valued even more than in Japan.

Next action: Consult your in-house IT lead and draft a one-page (A4) "AI usage guideline."

---

Part 4: FAQ

Q1. Won't using AI agents reduce work for Filipino staff?

A1. In the short term, part of the work is automated, but in the long term it becomes an opportunity to move to higher-value-added work. In SB OAI Japan's design, too, AI handles "investigation and proposal," while humans do the final check and judgment. At Philippine sites, cases are emerging where staff who have gained the skill to make full use of AI raise their value as a bridge to the Japanese head office.

Q2. I'm worried about violating Philippine personal-data protection law.

A2. If the data you send to the AI includes the names or contact details of Philippine nationals, it falls under the Data Privacy Act of 2012. Because it may also become subject to registration with the NPC (National Privacy Commission), consult a local law firm or your in-house data-protection lead before rollout. Specifically, it's important to redact personal data in logs and to document where the data is stored and for how long.

Q3. Can we use an AI tool approved at the Japanese head office at the Philippine site as-is?

A3. Even if the tool itself is the same, the handling of data and the customs around signatures differ from Japan. In the Philippines, you need to document contracts and consent even more carefully than in Japan. We also strongly recommend reworking, together with the local IT lead, the operational flow of who approves an inquiry to the AI and who checks the logs.

Q4. How much budget should we plan for?

A4. At the prototype stage, you can start with an API usage budget of roughly 10,000–50,000 pesos per month and the labor of one or two local engineers. For a full rollout, adding the cost of integrating with monitoring tools, certification fees, and internal training, it's realistic to plan for roughly 500,000–2,000,000 pesos per year. The safe approach is to start small, measure the effect, and then expand.

Q5. How should we get Filipino engineers to learn this?

A5. Just handing over materials one-sidedly won't make it stick. Hold a short briefing and always create time for hands-on practice. Pairing an explanation in Tagalog or English with time for a Japanese manager to answer questions raises the effect. Also, as SB OAI Japan did, setting an official certification as a goal creates clear milestones for learning.

---

Tips for Getting It Right (3 Tips)

Draw your existing workflow into a single diagram before you start

Before bringing in an AI agent, try writing out your team's workflow on paper. You'll start to see where time is being spent and where human judgment is needed. Turning it into a diagram clarifies the line between the scope to hand to AI and the scope humans handle.

Decide the "AI writes, human checks" rule first

If you think about the role division after adoption, operations begin with the rules still vague, leading to quality problems. The prototype SB OAI Japan won with, too, placed role division at the center of its design from the start. At a minimum, document two points as internal rules: "AI output is applied to production only after a human checks it" and "check records are kept."

Involve local staff at an early stage

If you firm up the plan at the Japanese head office and then toss it to the local site, it won't be accepted at the Philippine site and becomes a rollout in name only. Bring in the local IT lead and engineers early in the design, and start from their pain points. People nurture the mechanisms they helped think up.

---

Bonus: How to Work With PH AI Works

PH AI Works supports the adoption of AI and technology for Japanese firms entering the Philippines and Japanese business professionals based there. Our strength is being able to walk alongside you in three languages—Japanese, Tagalog, and English—especially in the areas of "AI agent design," "role-division design between the Japanese head office and Philippine sites," and "AI training programs for local staff."

As a next step, you can consult us for free on themes such as the following.

• Work mapping and role-division design for adopting AI agents in incident response at Manila and Cebu sites
• Support for creating rules on sending data to AI, mindful of the Philippines' Data Privacy Act of 2012
• AI-use training for local engineers and planning a study path toward official certification

Please feel free to get in touch.

---

References and Sources

• SoftBank News — "Building an agent on a 'programming is AI, checking is human' division of roles: SB OAI Japan wins OpenAI-hosted hackathon" (May 22, 2026)
• National Privacy Commission (NPC)
• Department of Labor and Employment (DOLE)