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The Manager’s Path in the Age of AI

by Camille Fournier19 Sept 2026

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  • Why do we care about technical skills in management? Because a lot of what we call “management” is in fact a risk management function. The manager is responsible for, among other things, making sure the work gets done, at reasonable quality, in reasonable timeframe, without causing so much personnel strain that people constantly quit. When building software systems, it’s hard to really know how long something should take, and what good looks like, if you don’t have any experience building this sort of system yourself.
  • the act of creating software has changed a lot, very quickly
    • People are really obsessed with productivity
    • The amount one person can do by themselves is a lot higher, so we have to completely revisit our intuitions about how to break up work to account for this increased capacity per individual

  • Signal Processing

  • things like diagnosing problems, debugging teams, making decisions in the face of ambiguity. How good are you at not just getting information but getting the right information in order to make the best decisions?
  • we have a problem that reliance on AI tooling may be inhibiting the development of situational awareness. You know, your ability to read the room? A lot of information is carried in non-text formats. Body language, tone of voice, camera on, camera off, the things said and the things left unsaid
  • I suspect many of us are starting to lose those subtle situational awareness signals because we are tuning out in meetings where we are relying on AI to do all of the note taking and transcription for us
  • relying on summaries even of digital artifacts means that we are trusting that the algorithm has highlighted the important details we have to know, but it is necessarily stripping out some amount of information that might actually encode useful signals we might want to be aware of.
  • Machines cannot be held accountable, so they cannot make management decisions, to paraphrase the immortal words of IBM circa 1979
  • if someone wrote code to solve a problem, it was a sign they were really willing to put in some elbow grease and effort, they cared a lot, they had a strong opinion. This didn’t always lead to great outcomes, but it was a useful signal that whoever wrote that code cared. Nowadays? Code is cheap.
  • AI undermines the small day to day activities that help build trust across organizations. It’s great that AI can quickly answer simple questions, and I would never suggest taking that away. But when you talk to glean, slackbot, claude, chatgpt, you aren’t talking to your colleagues. You aren’t asking them for help, and exchanging the kind of low-stakes favors that form connections; you aren’t learning their personalities and building your network.

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In summary, the most compelling insight is that while AI dramatically amplifies individual productivity, it simultaneously erodes the subtle human signals, trust, and contextual awareness that managers must intentionally cultivate through direct human interaction to keep teams aligned and functional.

  • AI's promise to eliminate or drastically reduce management is unrealistic; human oversight remains essential for accountability, context, and maintaining team coherence.
  • Over-reliance on AI for information gathering and decision-making degrades situational awareness, obscures cultural signals, and fuels organizational politics.
  • Managers must actively engage with AI tools to guide their teams through the transition rather than retreating to comfort zones or ignoring the shift.
  • Leverage AI-driven productivity gains to invest in deliberate human alignment practices, such as design reviews and direct conversations, to preserve trust and prevent fragmentation.

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