Working as a team
Collaboration needs responsibilities and access boundaries.
What you will learn
- Explain: check access before use
- Apply the idea in an example: Working as a team
- Recognize limitations and verify the exercise outcome
Collaboration needs responsibilities and access boundaries. Check effective organization and project roles rather than only UI labels.
These steps refer to features identified in the application code. This material has not been validated on a live instance; check the documentation and the options in your version.
How it works, step by step
Check access before use
Permissions must be enforced by servers and the data layer. Do not let the model decide whether a user may see a document. Filter sources before they enter context, not after generating the answer. Use minimal-access credentials, keep them out of prompts, screenshots and browser code, and rotate exposed keys. A widget domain allowlist does not replace API authentication. Authentication identifies you; authorization determines the operations and data you can use. Test denied access too.
Define success before optimizing
Prepare representative requests and expected answers or properties. Include ordinary cases, ambiguity, missing data and tool errors. For RAG, measure evidence retrieval separately from answer correctness. Recall@k measures the share of relevant evidence found in the first k results; precision@k measures the share of returned results that are relevant. For agents, also track actions, permissions and stopping. An LLM-as-judge can speed evaluation but needs calibration against humans. Do not change prompt, model and index simultaneously if you want to understand what improved results.
Errors need explicit paths
A timeout differs from a permission error. Retry only transient errors, with bounded attempts and increasing delays. An operation with side effects may execute before its response is lost; retrying without an idempotency key can duplicate the effect. Streaming shows progress but does not guarantee completion. Checkpoints may allow failed stages to resume within runtime limits. Store the run identifier, stage, duration and error while removing secrets from logs. Measure slow paths as well as averages.
The visual map
Follow the solid arrows for the main flow. Dashed blue arrows supply data or context; dashed pink arrows show feedback or returning results. Colors and shapes distinguish models, stores, decisions and outputs. On smaller screens, scroll horizontally to follow the entire diagram.
A complete example
Two teams have support and documentation projects. An unauthorized member must not see private sources through search, answers or API calls.
Try it yourself
- Invite test accounts with different roles and check two synthetic-data projects.
- Record the input, source and expected outcome before running the experiment. Use only the fictional data in the example.
- Follow the diagram stages. At every step record what information is received and produced; do not confuse intermediate output with the final outcome.
- Repeat after removing necessary information or making the input ambiguous. Check whether the system clarifies, stops or invents an answer.
- Compare with the explained solution. Keep the configuration, date, result and an explanation for differences. Change one thing and retest.
An explained solution
An access matrix documents reading, editing and administration and tests both allowed and denied cases. A successful exercise lets you show the connection between input, stages and outcome. When information is missing, a cautious answer is more useful than invented details. Compare more than style: check conditions, sources and operations too.
When it helps and what can go wrong
Do not assume folder grouping enforces access. Choose this approach when it improves a measured need. Keep a simple baseline and compare outcomes using identical inputs. One successful example does not establish reliability in every situation.
Check your understanding
Why is removing a private source after answering too late?
The data has already entered model context and can be disclosed.
Does a good style score prove agent success?
No. The agent may write beautifully after using the wrong tool or data.
What outcome should this exercise produce?
An access matrix documents reading, editing and administration and tests both allowed and denied cases.
Words to remember
- Autorizare / Authorization: Checking the right to access an operation or resource.
- Regresie / Regression: A change that breaks a previously correct case.
- Idempotency: Controlled repetition without duplicating an effect.
Sources and your next step
To prepare: U06 — API access and integration for developers