Codeer.ai User Guide
Turn one recurring expert judgment into an Agent you can inspect
Codeer is for work where a fluent answer is not enough. Someone who understands the work still needs to decide what a good result looks like, which boundaries must be respected, and when the Agent should hand the work back to a person.
Codeer calls this an expert-led AI Agent: the expert keeps the quality decision, while AI helps turn that judgment into an Agent that can be built, tested, launched, and improved.
You do not need to begin by writing a perfect prompt or building a large test set. Bring one real situation that happens repeatedly and make three things clear:
- What should the Agent help the user accomplish?
- What would make the result acceptable?
- What should the Agent avoid, clarify, or hand off?
Codeer can then help you create the first draft, try the behavior, keep important situations as reusable cases, and decide what is safe to publish.
Product evidence and team release decisions are different
Codeer stores cases, evaluation results, Agent versions, and conversations so the team can inspect behavior over time. It does not currently turn a must-pass set, named approver, or stop condition into an automatic publish gate. Your team chooses the required evidence, records the release decision, and decides when to publish, narrow, or stop a rollout.
A representative example
Representative workflow — not a customer outcome
A course owner repeatedly receives, “Which course is right for me?” A useful Agent should first ask about the learner's goal, current experience, and available study time. It should recommend only currently available courses, explain the basis, and hand the conversation to a person when the answer depends on an unconfirmed exception.
During Live Test, the Agent recommends a course before asking about study time. The owner keeps that situation as a must-pass case: ask about time before recommending a course. After the revised version passes that case and the nearby boundaries, the team makes it available only to an approved pilot group.
The team can now inspect whether later versions still follow that decision. This example does not prove time savings, sales, or learning outcomes; those require evidence from the real pilot.
Know the commitment before you start
A controlled pilot still needs someone to define acceptable work, someone to watch live use and handle exceptions, and someone with permission to manage access and releases. One person may cover several roles.
The effort depends on the risk, data, tools, and integrations involved. Start with one job and observe setup effort, human handoffs, operating time, and quality incidents before deciding whether expansion is worthwhile. Codeer does not remove expert responsibility; it makes the decisions easier to inspect, reuse, and verify.
Start from the work, not the product structure
The same workflow supports different kinds of expert work:
| Work pattern | Examples | What the expert decides |
|---|---|---|
| Answer and handle | Customer questions, course inquiries, orders, intake | What can be answered or completed, and when a person must take over |
| Guide and judge | Coaching, strategy support, internal guidance, triage | Which questions to ask, which reasoning boundaries to respect, and what next step is useful |
| Review and deliver | Draft feedback, lesson planning, professional work review | What quality looks like, what evidence is required, and what must be revised |
The examples differ, but the operating loop stays the same:
- Start with one real job.
- Let AI help create a first draft.
- Inspect the Agent on the real situation and nearby boundaries.
- Keep must-pass behavior as reusable cases.
- Publish only the scope you are ready to support.
- Learn from real conversations and verify the next change.
Start here
Start with one real job
Build the first Agent behavior, check its boundaries, and make a controlled launch decision
Use a Template
Answer the questions that define the work and review an AI-generated draft before creating the Agent
Operate Conversations
Handle live conversations, capture new cases, and decide what the next version should learn
Find the guide for your role
| If you are responsible for... | Start with... |
|---|---|
| Defining what is correct, useful, and safe | Start with one real job, then Verified Scenarios |
| Reviewing live work and handling exceptions | Conversations, then Reply to Conversations |
| Data, Channels, permissions, and rollout setup | Knowledge and Integrations, Launch Safely, and Team and Access |
One person may cover more than one role. The important part is that the quality decision, daily operation, and technical setup stay visible instead of being hidden inside one prompt.
Explore by job to be done
Build the Agent
Define how the Agent should clarify, decide, respond, and stay inside approved boundaries
Teach and Verify
Keep expert judgment as cases that can be rerun before a version is published
Launch Safely
Publish a controlled scope, choose who can use it, and keep unverified work on a safe fallback
Operate and Improve
Observe real work, respond when needed, preserve new judgment, and verify the next change
Knowledge and Integrations
Give the Agent the sources and actions required for the work, without adding unrelated complexity
Team and Access
Set clear responsibilities for experts, operators, reviewers, and admins
