Same AI. Different results.
GPT, Claude, Gemini — today, anyone can use a top-tier AI model. So why do people still get very different results from the same model? The quality of AI-driven work isn’t decided by model performance alone. What you check, how you judge it, what you execute, and where you stop — the experience and judgment built into that harness is what decides the outcome.
It’s not the model. It’s the Harness.
Not theory — experience built up in production.
GIIP FDE’s harness isn’t built on AI-generated generalities. It’s built on real experience facing design, incidents, performance problems, scaling and cost optimization in large-scale production environments.
40M
DAU
Experience running a service at 40M DAU scale
600K
Concurrent Users
Up to 600K concurrent connections
300M / day
Transactions
300M transactions per day at scale
1.76 PB
Storage
Petabyte-scale storage operations
300 Gbps
Traffic
Large-scale delivery infrastructure
¥200M / year
Cost Reduction
Roughly ¥200M/year in infrastructure cost reduction delivered
Using the best AI doesn’t automatically get you the best result.
AI model
Knowledge, reasoning, coding ability, writing, tool calling. Anyone can use the same model.
Harness
What to check, what to question, in what order to investigate, which tools to use, what to execute, where to require human approval, what to validate afterward. This is where experience makes the difference.
If the model is the “brain,” the harness is “how the work gets done.”
From an AI that answers questions, to an AI that runs Production.
General AI Assistant
- Question
- Answer
Coding Agent
- Instruction
- Coding
- Test
GIIP FDE
- Observe
- Diagnose
- Plan
- Risk Check
- Execute
- Validate
- Monitor
- Improve
GIIP FDE doesn’t stop at writing code. It’s designed so the scope of work covers the service actually running — and staying stable afterward.
Nearly 30 years of experience — not a prompt, but execution rules.
The judgment we built up over decades in production doesn’t stay as tribal knowledge. It’s encoded into the harness as concrete, repeatable rules.
- 1
Investigation
What to check first, which logs, metrics and queries to look at.
- 2
Diagnosis
An investigation order built to find the root cause, not just the symptom.
- 3
Architecture
Design judgment that accounts for performance, availability, cost and operability together.
- 4
Production Safety
Judging which changes are safe to execute and which require human approval.
- 5
Performance
Bottleneck analysis across database, application and infrastructure.
- 6
Continuous Improvement
Not stopping at execution — checking the result and feeding it into the next improvement.
You don’t need to write a clever prompt.
Just ask, the way you’d ask a human engineer on Slack.
You don’t need to become an AI expert.
AI is a tool whose output can vary a lot with the prompting skill of the person using it. But adopting an FDE doesn’t mean every employee at your company needs to become an AI expert. When the quality isn’t what you expect, GIIP checks and adjusts the model, prompts, tools, knowledge and execution procedures on our side.
Getting the most out of the FDE isn’t your job. Continuing to grow the FDE into something that works well is GIIP’s job.
This experience, available monthly — not by the person-month.
Could you hire an infrastructure engineer with nearly 30 years of production experience, available 24 hours a day, for ¥500,000 a month?
GIIP FDE Box is not a service that keeps one human engineer on-site 24 hours a day. It’s a service where an AI FDE — built on production engineering experience and judgment turned into a harness — keeps executing work continuously, with a senior FDE stepping in when needed.
FDE Box Full-Operation Plan
Requests any time, 24/7/365
No limit on the number of requests
No extra quotes for GIIP’s work
Work is executed in order of scale, risk and priority. High-risk operations such as production changes or data deletion follow the approval policy. Third-party usage fees (AWS, Azure, external AI APIs, SaaS, commercial licenses, etc.) are billed separately.
Same GPT.
Same Claude.
Same Gemini.
The results still aren’t the same.
Use the difference nearly 30 years of production experience makes — built into the Harness, not the model.
Nearly 30 years of experience, as your company’s AI FDE.
Frequently asked questions
Why do results differ even with the same AI model?
It’s not only about model performance. What you check, what order you investigate in, which tools you use, where you require approval, and what you validate afterward — this harness is what changes the outcome of the work.
What is GIIP FDE’s Harness?
GIIP FDE’s harness is the execution layer that connects AI models to infrastructure, databases, cloud, repositories and monitoring tools, and keeps investigation, judgment, execution, validation and improvement running continuously. It reflects judgment criteria and operational know-how built up over roughly 30 years of production engineering.
How is this different from ChatGPT or Claude Code?
ChatGPT and Claude Code are extremely capable AI models on their own. GIIP FDE is not a model — it’s a harness and operating environment that uses multiple AI models and tools together to continuously run investigation, development, database work, infrastructure, deployment, monitoring, incident response and improvement in a production environment.
Do I need AI expertise to use this?
No. You can request work the same way you’d ask a regular engineer. If the results don’t meet expectations, GIIP checks and adjusts the model, prompts, tools, knowledge and execution procedures.
How much does FDE Box cost?
JPY 500,000 per month (excl. tax). This includes dedicated FDE Box hardware, installation, environment setup, continuous operation, FDE Box incident response, answer-quality tuning, and senior FDE support. There are no additional per-request quotes or extra person-month charges for GIIP’s work.
Can I request work 24 hours a day?
Yes, requests to the FDE can be made 24/7/365 with no limit on the number of requests. Work is executed in order of scale, risk and priority, and high-risk production operations follow the approval policy.