1. Use AgentFoundry for execution, not vague research
AgentFoundry is for reviewed software work. If the job is still mostly research, framing, or requirements discovery, start in Lexopedia AI first and move into AgentFoundry once the objective is clear enough to execute.
2. Prepare clean task boundaries
A strong AgentFoundry request defines the objective, repository or environment, constraints, approval points, and what counts as done. The clearer the scope, the easier it is to review what the system produced.
- State the objective in one sentence.
- Name the repository, branch, or code surface involved.
- List constraints: policy, security, budget, deadlines, or files that must not change.
- Define success: tests, report, patch, review artifact, or explanation.
3. Review the evidence, not just the result
AgentFoundry should make the work reviewable. Do not look only at the final patch or final claim. Review what changed, what passed, what failed, what still needs approval, and what the run cost or consumed.
- Check repository state and scope first.
- Check tests, checks, and review points.
- Check approval boundaries before accepting or merging anything important.
- Escalate when a run looks outside scope or under-evidenced.
4. Keep humans in the approval loop
AgentFoundry is designed for reviewed delivery. That means human judgment still matters at the approval boundary. Use the system to reduce mechanical work and improve traceability, not to skip review for risky changes.
5. Ask support when the run model is unclear
Contact support if you are unsure whether a job belongs in AgentFoundry, if the execution state looks inconsistent, if review artifacts are missing, or if access, billing, or pilot questions block adoption.