Issue-to-reviewed-change loop
Frame an issue, provide context, use AI for a focused change, generate test ideas, and document the review evidence.
Explore the software course →MHGrad uses project demonstrations to make the learning concrete and publishes testimonials only when feedback is genuine, attributable, and shared with permission.
These are guided project themes, not claims about completed client deployments. The exact brief is selected with the learner or team.
Frame an issue, provide context, use AI for a focused change, generate test ideas, and document the review evidence.
Explore the software course →Structure document inputs, extract useful information, add validation checks, and define escalation for uncertain cases.
Explore the solution area →Help a team find answers from trusted content while preserving source context and a human path for exceptions.
Explore the business course →Prepare research, proposals, CRM updates, or support replies with clear sources, reusable context, and review.
Explore the service solution →Define a trigger, tools, permissions, failure path, and human approval for a useful operational workflow.
Explore the agents course →Document what the system does, what it should not do, what to check, and when a person must take over.
Ask about team training →A genuine learner story should help a prospective learner make a decision, not just decorate a landing page.
When a learner agrees, MHGrad will publish their name, role or context, cohort or programme, project, exact words, and permission status. Anonymous feedback may inform improvements internally, but it is not presented here as a testimonial.
Request verified learner stories →This keeps the proof honest while the course foundation is prepared.
Ask for the context behind any result instead of relying on an unattributed claim.
Contact MHGrad if you need current references before a team engagement.
Project-first learning gives you something specific to inspect, improve, and discuss.