How AI is changing engineering roles and feedback loops

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Our CTO, Pau Beltran, shared something interesting with me this week: AI tools are not only making engineers much more efficient, but they’re also fundamentally reshaping their role. And as their output scales, engineers need to stay closer to the clients who use what they build. Yes, AI lets them produce 10x more code, but how do they gather 10x more client feedback to know how they can make the tools they build even better? If you’re in sales, this will sound familiar: how do you give your product and engineering managers more exposure to client feedback when most salespeople are naturally protective of their accounts? You like to stay in control of client conversations and limit who gets involved. In reality, the issue isn’t that client feedback isn’t being captured. It is, every day. The challenge is making it accessible to your engineers, and you can’t expect them to dig through HubSpot to find it. Our EU Private Equity Leader Nikunj Agarwal recently came up with a clever workaround using n8n. Instead of bringing engineers into the sales workflow, Nik realised we need to bring client feedback directly to the engineers. Here is the automation Nik built for Arbolus (check out his n8n flow below): >Every feedback call artefact is summarised, segmented and scored >It’s then pushed into Hubspot and uploaded into the contact profile >The summary is posted instantly to engineers in a Slack channel. All Sales needs to do is call clients; all engineers need to do is read Slack. The real value is the discourse that flows in real time. Sales & Engineering sharing instantly and asynchronously without any changes or disruptions to their workflows, fast iterating on user feedback. What automation setups are your commercial teams using? Share in the comments if you can!

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This is very cool! We were having a related discussion last night at the Data & AI Product Management meetup, wondering how can we bring together all the different sources of info that we _theoretically_ have access to in an org, but which sit behind different systems and context. Those of us who had made progress on this front cited the same approach: Use automation tools like n8n to move relevant info to the right place, instead of getting analysis paralysis from having to use 20 different tools. Thanks for sharing Peyton!

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