No Miracle, Just Method: AI Copilot’s Value in Product Development by Salome Mikadze

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At all times, AI solutions are to be assessed from the angle of looking at how exactly they alter the team’s internal processes. AI copilots, such as the one from Thinkpilot, are equipped to become a true accelerator for product teams, but only under one condition—the team must already have its own basic structure and adaptability. It’s not about automation as a tribute to fashion trends but about strengthening analytical thought processes, a focus on true priorities, and minimizing informational noise.

In most teams, chaos occurs not because of lacking processes but from their inability to answer a simple question—Why are we doing this right now? If the AI copilot helps teams shape such why’s, then its usefulness goes far beyond the so-called GPT wrapping. It can substantially improve the communication between founders, product managers, and developers, which is already a big advantage in early growth stages.

Personalized AI copilots are not an add-on but a necessity. They integrate with concrete workflows, relieving people from the routine and providing an opportunity to concentrate on what truly matters. Particularly, Thinkpilot’s strength, in my opinion, is in its narrow specialization. It’s not a universal platform with a bunch of features, but a targeted product for product teams. And this is why it has an excellent chance to become an effective solution for the CEE region where teams often wish to scale quickly, but without unwanted bureaucratic layers. However, as always, the quality of implementation and the feasible culture of evolution are critical. Because no technology does miracles with the change-readiness of teams themselves.

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