3 AImigo S1E8: AI-native companies — episode materials (Category #AI4SDLC)

I've collected the materials from episode eight of 3 AImigo, “AI-Native: What Does It Mean for a Company?” The livestream took place on October 2, 2026, and the recording was published on October 3. Aleksey Litvinov, Evgeny Sergeev, and I discussed what needs to change when everyone has an AI assistant, yet the result still awaits approval in another department.

We discussed: 🔸 How agents become part of shared work Aleksey looks at agents coordinating across employees; Evgeny considers the entire journey from intent to outcome; I focus on redesigning processes and the organization. These are our working definitions, rather than a common AI-native standard. 🔸 Shared context and human attention Knowledge needs to stay current, past decisions need to be recorded, and questions for people need a queue. Otherwise, faster agents can quickly leave everyone waiting for a single manager. 🔸 Evolution or revolution I favor gradual, measurable changes in large companies; Aleksey worries that this cannot keep pace with technology. Pilots, executive support, and measurement across the entire product journey help establish the effect: a team may speed up and still be waiting for its neighbors. 🔸 An existing service or a custom tool Aleksey describes building a training recommendation system with an agent in a few hours. Evgeny points to existing payment services, while I stress maintenance and integrations. A few hours spent on a prototype can turn into years of obligations. 🔸 What to do with freed time Retrain people, find new products, or reduce costs? We disagreed here too: additional capacity does not itself create demand for the result.

Episode materials: 📌 Episode page 📖 Longread on the AI-native organization — a separate treatment I prepared for the livestream: processes, responsibility, evidence of impact, and the first 90 days of transition 🎬 YouTube, VK Video 🎧 Podster, Yandex Music, Apple Podcasts 📝 Edited conversation recap

If you are already redesigning work around agents, where are you getting stuck: context, approvals, maintaining custom tools, or finding valuable tasks?

#AI4SDLC #AI #Management #Architecture #Podcast