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The Pragmatic Engineer 20260414 The Impact of AI on Software Engineers in 2026 Key Trends Summary

2026-04-14 837 words 4 minutes #the-pragmatic-engineer

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The Pragmatic Engineer surfaced this April 14, 2026 piece, and the original post is The impact of AI on software engineers in 2026: key trends.

Gergely Orosz and Elin Nilsson use more than 900 survey responses from engineers and engineering leaders to describe how AI coding tools are changing daily software work in practice. The article is less interested in which model won last week and more interested in what happens once these tools become routine: who pays for them, who runs into limits, who benefits most, and what kinds of tradeoffs teams are quietly accepting.

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The Pragmatic Engineer 20260408 DHH's New Way of Writing Code Summary

2026-04-08 483 words 3 minutes #the-pragmatic-engineer

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What happened

The Pragmatic Engineer surfaced this April 8, 2026 piece, and the original post is DHH’s new way of writing code.

Gergely Orosz interviews David Heinemeier Hansson about a notable reversal. Six months ago, DHH said he did not want AI writing his code. Now he describes an agent-first workflow built around terminals, tmux, Neovim, and multiple models running in parallel. His argument is not that the principles of software craft changed. It is that the tools improved enough to make delegation worthwhile. Autocomplete used to feel annoying and low-value; newer agents can now produce code that he is comfortable reviewing and sometimes merging with minimal changes.

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The Pragmatic Engineer 20260407 Cycles of Disruption in the Tech Industry with Software Pioneers Kent Beck and Martin Fowler Summary

2026-04-07 343 words 2 minutes #the-pragmatic-engineer

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What happened

The Pragmatic Engineer surfaced this piece in its April 7, 2026 issue, and the original post is Cycles of disruption in the tech industry: with software pioneers Kent Beck & Martin Fowler.

Gergely Orosz summarizes a live conversation with Kent Beck and Martin Fowler about how AI compares with earlier technology shifts like the internet, object-oriented programming, and Agile. Their broad argument is that AI feels bigger, faster, and messier than those earlier transitions, and that it is already changing how software teams work, how companies measure performance, and what good engineering discipline looks like.

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