Now that AI writes the code, what should engineers learn? Understanding code still matters, and understanding code means learning how a senior engineer thinks. diff-tour turns a git diff into a tour you step through with → and ←: what the change is for, where to look, what a senior asks (what if it runs twice? can it roll back?), what must be fixed and what is a nit, and where they'd say "wait", asked as questions so you guess first. Runs on your AI coding CLI. Read-only, open source.
Hi Product Hunt 👋 I'm Dai, the maker of diff-tour.
I also run WebTerm Learn, which launched here in August, and I talk with a lot of people who teach software engineering. One question comes up again and again: now that AI writes the code, what should engineers learn?
People rarely write code by hand anymore. AI often reviews it too, and software moves so fast that reading every line is hard. Still, I'm sure of one thing: understanding code matters as much as ever. And understanding code means learning how a senior engineer thinks. That is what lets you give AI the right instructions, notice what really matters in a problem, design well, and keep a project moving in the right direction.
So diff-tour teaches that thinking on real changes. Point it at a branch, and the AI coding CLI you already use writes a tour of the change. Then you step through it with → and ←:
What the change is for, and which files to read next, including ones that didn't change
What a senior engineer asks: What if this runs twice? Can it be rolled back? Would the tests fail if the code broke?
What must be fixed, what's only a nit, and what looks risky but is fine
The moments they'd stop and say "wait", asked as questions so you can guess before you see the answer
Getting started is just this: install with the one-line script in the README, then run it in any git repository:
cd your-repo
tour
The first run asks for a language and an AI CLI, with recommended choices already selected. Press Enter three times and the tour starts being written.
Things I cared about:
It's read-only. The AI gets a copy of the files git tracks and read-only tools, enforced by command-line flags, not only by the prompt
The code on screen is read from git at the right commit, never copied from the AI's reply
No server, no telemetry, MIT licensed. It runs on your own Claude Code, Codex, Gemini, OpenCode or Copilot plan
diff-tour keeps growing, and what you say today shapes what comes next. I'd love to hear: which part of reading a change do you wish someone had taught you? And if a tour got something wrong, tell me where.
The guess first part is the whole thing for me. We're building learning stuff too (nutrition, not code) and making people commit to an answer before they see it is what actually makes it stick. Do you track if people's guesses get better over time?
The guess-first part is what sets this apart from another AI review summary for me. When an agent hands me a big diff, my weak spot is skimming until something looks off instead of asking the runs-twice and can-it-roll-back questions up front. Pointing me at files that didn't change is the other smart bit — that's usually where the real risk is hiding. Read-only, no telemetry, and running on the CLI I already use is exactly how a tool like this should ship.
I think it's still useful to understand the code so you got my upvote. However to chime a response to your question, software engineers should focus on modelling, planning, scoping and more importantly architecting the code building. The coding tool is here but designing what the code does is my focus. Even AI will push back on some implementation for design or architectural direction.
To your question, I've mostly stopped reading the code myself, so for me it would be the data model. What's stored and how it connects is the one thing I still keep a close eye on.
About diff-tour on Product Hunt
“AI writes the code. Learn to read it like a senior engineer.”
diff-tour launched on Product Hunt on November 2nd, 2026 and earned 100 upvotes and 11 comments, placing #13 on the daily leaderboard. Now that AI writes the code, what should engineers learn? Understanding code still matters, and understanding code means learning how a senior engineer thinks. diff-tour turns a git diff into a tour you step through with → and ←: what the change is for, where to look, what a senior asks (what if it runs twice? can it roll back?), what must be fixed and what is a nit, and where they'd say "wait", asked as questions so you guess first. Runs on your AI coding CLI. Read-only, open source.
diff-tour was featured in Education (79.5k followers), Software Engineering (43.2k followers), Developer Tools (522.3k followers) and GitHub (41.5k followers) on Product Hunt. Together, these topics include over 169.5k products, making this a competitive space to launch in.
Who hunted diff-tour?
diff-tour was hunted by Dai Aoki. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how diff-tour stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Dai Aoki
Hi Product Hunt 👋 I'm Dai, the maker of diff-tour.
I also run WebTerm Learn, which launched here in August, and I talk with a lot of people who teach software engineering. One question comes up again and again: now that AI writes the code, what should engineers learn?
People rarely write code by hand anymore. AI often reviews it too, and software moves so fast that reading every line is hard. Still, I'm sure of one thing: understanding code matters as much as ever. And understanding code means learning how a senior engineer thinks. That is what lets you give AI the right instructions, notice what really matters in a problem, design well, and keep a project moving in the right direction.
So diff-tour teaches that thinking on real changes. Point it at a branch, and the AI coding CLI you already use writes a tour of the change. Then you step through it with → and ←:
What the change is for, and which files to read next, including ones that didn't change
What a senior engineer asks: What if this runs twice? Can it be rolled back? Would the tests fail if the code broke?
What must be fixed, what's only a nit, and what looks risky but is fine
The moments they'd stop and say "wait", asked as questions so you can guess before you see the answer
Getting started is just this: install with the one-line script in the README, then run it in any git repository:
The first run asks for a language and an AI CLI, with recommended choices already selected. Press Enter three times and the tour starts being written.
Things I cared about:
It's read-only. The AI gets a copy of the files git tracks and read-only tools, enforced by command-line flags, not only by the prompt
The code on screen is read from git at the right commit, never copied from the AI's reply
No server, no telemetry, MIT licensed. It runs on your own Claude Code, Codex, Gemini, OpenCode or Copilot plan
diff-tour keeps growing, and what you say today shapes what comes next. I'd love to hear: which part of reading a change do you wish someone had taught you? And if a tour got something wrong, tell me where.