FocusDeep work

The Death of Deep Work in the AI Era

When an AI answer is always three seconds away, the will to think for ninety uninterrupted minutes quietly evaporates. This post argues that deep work is not dead — it is endangered, and recovering it is a skill in itself now. Inside: how to protect one 90-minute block a day, the exact setup (one tab, no AI, one problem, phone in another room), and why nothing meaningful in my career ever came from "fast" — it came from "long."

Siddharth PuriJanuary 18, 20267 min read
Skill Loss & Learning

The Death of Deep Work in the AI Era

January 18, 2026 · 7 min read · Siddharth Puri

Deep work needs two things: a hard problem and a human who will not leave the chair. AI threatens the second one, not the first. Hard problems are still hard. The bottleneck has always been the person, and the person now has a tempting escape hatch three seconds away.

This post is not a Cal Newport rehash — it is about the specific flavour of concentration loss that AI has introduced, and what to do about it in practice, not in theory.

Why AI threatens deep work specifically

Shallow work has always been seductive. Email, Slack, meetings — these have always eaten focus. What is new is that AI provides a fourth escape hatch that masquerades as deep work. You feel like you are being productive, because outputs are coming out, but you are actually in a rapid prompt-tab-copy-paste loop that looks like focus and is not.

The prompt-response rhythm is short. Deep work requires a long rhythm — thirty, sixty, ninety minutes with a single problem. If your default rhythm is fifteen seconds because that is how long a prompt takes, you have trained yourself out of the long one.

What deep work actually buys you

I want to make the case concretely. Almost everything meaningful in my career came from long blocks of uninterrupted thinking, not from fast iteration.

  • The architecture decisions that saved months of rework
  • The essays that actually mattered to readers
  • The product insights that changed roadmap
  • The debugging sessions that fixed the real bug, not a symptom
  • The strategic pivots that stopped us from wasting a quarter

None of these came from shallow work. All of them came from sitting, uninterrupted, with a problem. That is the output pattern I want to protect.

Protect one 90-minute block a day

Not two hours, not a whole morning — one 90-minute block. This is low enough that it is doable on every day, including bad days. High enough to produce real work. The specific number matters less than its non-negotiability.

The setup for the block is deliberately spartan. Shallow work is happy to expand into any available surface. Give it no surface.

  • One tab, no AI, one problem
  • Phone in another room, not on silent
  • Notes in a plain text file — no autocomplete, no AI suggestions
  • A written objective at the top — "by the end of this block, I want to have X"
  • End with a written summary of what you learned — not just what you did

What to do in the block

Actual deep work. Which means: thinking, writing longhand or in plain text, reading primary sources slowly, drawing diagrams, doing the hard part of the hardest problem you are stuck on. Not "preparing for deep work." Not "setting up a good environment for deep work." The work itself.

If you hit a wall — and you will — do not reach for AI. Sit with the wall. The wall is what teaches you. If you get unstuck by asking a model, you skip the learning that happens when you unstick yourself. Twenty minutes of staring is worth more than twenty seconds of a clean AI answer, most of the time.

How to make it stick

  • Same time every day. Morning is usually best, before the day gets busy
  • Tell the people you work with about the block. Defend it socially
  • Track streaks. Miss one day, fine. Miss two, fix the pattern immediately
  • Measure output per block in "did I learn something new?" — not in keystrokes or tokens
Nothing useful in my career came from fast. It came from long.

Deep work is not dead. It is endangered. In two years, being able to sit with a problem for ninety minutes without breaking concentration will be a rare, paid skill. That is both depressing and an opportunity. Pick up the opportunity.

All postsSiddharth Puri

Keep reading

View all →
AI & Future of Work

Claude 3 vs GPT-5: What Changed and Why It Matters

March 26, 2026 · 9 min

Claude 3 vs GPT-5: What Changed and Why It Matters

They both claim to be the smartest thing ever built, and both demos look suspiciously similar. This is a ground-level look at how Claude 3 and GPT-5 actually differ in reasoning depth, long-context reliability, code quality and tool use — plus a blunt cheat sheet for which one to pick for which job. Written in English, without the benchmarks theatre.

AI & Future of Work

Will AI Really Replace Developers or Just Upgrade Them?

March 18, 2026 · 8 min

Will AI Really Replace Developers or Just Upgrade Them?

The internet has been burying developers every year since 1998 and we keep showing up for breakfast. Here is the honest split — which parts of the job AI genuinely eats (boilerplate, docs, test scaffolding, Stack Overflow archaeology) and which parts quietly get harder and more valuable (product judgement, architecture, ambiguity). Short answer: it replaces the parts of your job you hated, and the parts that pay you get more fun.

AI & Future of Work

Jobs That Will Survive the AI Revolution (And Why)

March 8, 2026 · 9 min

Jobs That Will Survive the AI Revolution (And Why)

Forget the "creative vs repetitive" framing — the real line is "work customers trust a machine with vs work they do not." This post maps three tiers: jobs that will stay deeply human (health, founding sales, investigative journalism, skilled trades), jobs that will transform rather than disappear (design, engineering, teaching, support), and jobs that are quietly becoming the best bets of the decade. A calmer, less LinkedIn-flavoured take on the next ten years.