Early users shape a platform’s understanding of the problem it is trying to solve. Rajeev Khandelwal’s professional network offers ALFA Digital access to varied institutional perspectives, but familiarity alone is not the best selection criterion. The most useful initial participants are those whose needs reveal the actual work of preparing, reviewing, publishing and maintaining an asset record.
Choose a representative task
The first institution should have a genuine information need that matches the service the platform intends to provide. A demonstration assembled only to look impressive may avoid the difficult parts of the workflow. A real task introduces ordinary constraints: incomplete documents, multiple contributors and changing information. Learning from those conditions gives the team a more accurate view of what the product must support beyond a controlled presentation or internal trial.
Include different roles in the feedback
The asset owner, reviewer and reader may experience the same record differently. Each should contribute to the assessment of the journey. An owner may find submission easy while a reviewer cannot locate the evidence needed for a decision. Observing both sides prevents the team from optimizing one stage at the expense of another. It also helps identify where a clearer handoff or a better definition would improve the whole service.
Ask for evidence of difficulty
General praise is less useful than a specific account of where someone hesitated, repeated work or misunderstood a status. The team should observe those moments and connect them to the user’s purpose. This produces actionable learning. It also prevents a close professional relationship from making early feedback unrealistically positive, because participants are invited to improve a concrete process rather than judge whether they like the founder’s broader vision.
Use the network as a learning advantage
Rajeev’s ecosystem contains institutions with different capabilities and operating contexts. That breadth can help ALFA Digital learn quickly if the early programme is designed around real tasks and candid feedback. The outcome should be a clearer service model and a more dependable journey. A strong initial user group provides insight into the work, giving the platform a better foundation for serving institutions beyond the existing professional network.
