Engineering management is leverage, not administration

Engineering managers are not paid to run calendars, rewrite meeting notes or chase documents. They are paid to create clarity, enable people and make decisions that move an organisation forward.

When most of your time is absorbed by repetitive administrative work, you are not being careful or thorough. You are under-leveraging your role.

This is precisely where AI changes the nature of the job.

AI is no longer optional

AI tools are not experiments, toys or distant bets on the future. They have become basic infrastructure for modern knowledge work.

Used well, they extend how you think and prepare. They help you write more clearly, synthesise information faster, prepare conversations more thoroughly and follow through more consistently. They do not replace judgement, but they amplify it.

Choosing not to use AI in an engineering management role is not a principled stance. In practice, it is a productivity and quality gap.

AI can hold more context than any individual ever could

An engineering manager operates in a constant flood of information: months of one-to-one notes, meeting transcripts, Slack discussions across multiple teams, half-made decisions, evolving objectives and performance feedback coming from many different sources.

No human can reliably keep all of this in working memory, and pretending otherwise usually leads to recency bias and shallow pattern recognition.

AI, on the other hand, can ingest and reason over large volumes of qualitative information. When used carefully, it can help you prepare end-of-year reviews grounded in real history rather than recent impressions. It can surface recurring themes across multiple one-to-ones, highlight repeated blockers or stalled trajectories, and help you identify growth patterns that only become visible when you look across months instead of weeks.

It can even support the creation of genuinely personalised development plans and reveal emerging interpersonal dynamics across meetings and teams.

This is not automation. It is augmented perception.

AI as a counsellor, not an oracle

Some of the hardest parts of the job are situations where there is no obvious correct move. Tension between two people, feedback that feels true but is difficult to phrase, conflicts with human consequences that cannot be reduced to a decision tree.

In these moments, AI is most useful when it acts as a thinking partner.

It can help you reframe a situation, explore alternative interpretations, suggest questions worth asking and reason through trade-offs before you speak. Its value lies in broadening your perspective, not in producing a final answer.

AI should never decide for you. It should help you decide better.

Remove friction, not accountability

AI is extremely effective at removing the mechanical friction that surrounds people management. It can help you summarise one-to-ones and extract actions, prepare difficult conversations with more clarity and empathy, synthesise feedback across time and sources, structure performance reviews and objectives, turn scattered discussions into usable decision logs and prepare alignment updates in minutes instead of hours.

What it cannot do is understand trust, read a room, choose the right moment or own the consequences of what is said and decided.

AI can support your judgement, but it can never absorb your responsibility.

Spend less time managing process and more time managing people

The highest-leverage work of an engineering manager is not documentation. It is conversation.

Coaching, context-setting, decision making, unblocking and aligning individuals with strategy are where real impact is created. AI should compress the mechanical parts of the role so that you can invest more of your attention in the human ones.

If AI gives you time back, the goal is not to fill that time with more administration. The goal is to reinvest it in people.

Preparation beats improvisation

Strong managers rarely rely on improvisation. They show up with context, with intent and with well-chosen questions.

AI is a powerful force multiplier for preparation. Drafts, summaries, alternative framings, possible scenarios and follow-up prompts all become easier to produce. You still make the decisions, but you arrive at them with more depth and more perspective.

The bar is higher now

Using AI simply to manage less is missing the point. The best engineering managers use AI to manage more intentionally.

More clarity. More consistency. More fairness. More follow-through.

AI does not lower expectations. It raises them.

The mindset

Delegate repetition to machines. Keep judgement with humans. Use AI to think better, not to think less. Optimise for leverage, not comfort.

Engineering management remains a craft. AI does not replace that craft. It removes many of the excuses for not practising it well.