Asynchronous & Unreliable - Conversations on The Edge of Software

← Asynchronous & Unreliable - Conversations on The Edge of Software24 aug · 42 min

Ep 23: Scale Demands Strategy! With Tech Veteran Jon Berger

Ep 23: Scale Demands Strategy! With Tech Veteran Jon Berger24 aug42 min

<h1>Shownotes</h1><p>Anne Currie talks with mission critical software veteran Jon Berger about his upcoming book on strategy, leadership and management, shaped by 30 years of experience across startups, scale-ups, and Microsoft. The conversation focuses on why context matters, how to build alignment, and why internal teaching, writing, and speaking can make leaders more effective when they are not physically present.</p><p>They also discuss Team Topologies, internal tech conferences, and how AI may create a real discontinuity in team evolution and software delivery.</p><p>Key topics</p><ul><li>Jon Berger explains that his book, What Happens When You're Not in the Room, comes from three decades of building, growing, and leading teams at many scales</li><li>Anne and Jon discuss why management advice often fails when it is treated as a universal template instead of something that depends on context</li><li>Jon describes the value of internal training courses, brown bag sessions, and company blogs as ways to build trust, spread ideas, and sharpen communication</li><li>The episode revisits alignment as both a strategic concept and a cultural one</li><li>Jon breaks strategy into three questions: what are we trying to achieve, what is difficult about it, and how are we going to approach that difficulty</li><li>Team Topologies is discussed as a way of organizing multiple teams so they can scale, stay aligned, and avoid stepping on each other’s toes</li><li>Jon highlights team cognitive load as a key insight from Team Topologies and one that matters in real organizations</li><li>The conversation turns to AI and whether engineering teams can evolve incrementally toward AI-assisted or AI-led workflows, or whether that change may be a discontinuity instead</li><li>Anne and Jon compare incremental experimentation with a more abrupt shift where engineers stop reviewing code and AI becomes the main producer</li><li>Jon reflects on the difference between useful history in code and tech debt that should not be carried forward</li></ul><p>Action items</p><ul><li>Think about whether your team is solving for the right goal, the real difficulty, and the right approach</li><li>Use internal speaking, teaching, or writing to help ideas survive after you leave the room</li><li>Review whether your organization has useful alignment at both the strategic and cultural level</li><li>Consider whether AI adoption in your team is incremental or whether it may require a more deliberate rethinking of team structure</li></ul>