Picking up cold
Coming back after three weeks away
You — or a fresh session — return to a project and can’t remember how half of it works, so the AI re-derives or rebuilds things that already exist.
The scenario
Lena — a part-time maintainer, building a habit-tracking app she works on between contracts.
The goal
Drop back into a side project after a month away and ship a new feature quickly — without breaking the parts she’s forgotten how they work.
Lena hasn’t touched the habit-tracker in a month. The sync logic was fiddly to get right, and the details have evaporated from her memory. A fresh Claude session knows even less — it’s starting from a blank context every time.
Without afterclick
- The new session doesn’t know the retry logic already lives in `queue.ts`, so it builds a second, conflicting version from scratch.
- It “fixes” the sync code without understanding the edge cases Lena solved a month ago — quietly reintroducing a bug she’d already killed.
- Lena spends two days just re-learning her own codebase before she can safely change anything.
- Hard-won decisions live only in her head, so every gap in her memory is a gap in the AI’s too.
With afterclick
- The project remembers, even when she doesn’t. The feature catalog records how each part actually works, so the AI reads the truth instead of re-deriving it.
- Context handed over at startup. Every new session begins with the history, the roadmap, and the catalog injected — so it knows what exists and what’s planned.
- No rebuilding what’s already there. Because the AI knows the retry logic lives in `queue.ts`, it extends it instead of duplicating it.
- Back to productive in minutes. Lena picks up where she left off without a two-day re-learning tax.
What afterclick did here
- 1Injected the project’s feature catalog, history, and roadmap into the new session at startup.
- 2Recognized the new session was about to add its own retry loop.
- 3Pointed it to the existing implementation in `queue.ts` instead.
- 4Surfaced the edge cases Lena had solved a month earlier so they weren’t reintroduced.
- 5Kept the catalog updated as the new feature changed how things work.
What you’d have seen
Retry logic already lives in queue.ts
The new session was about to add its own retry loop. Pointed it to the existing implementation instead.
The obvious objection
Why not just read the README and git history?
READMEs go stale the moment the code moves past them, and git history tells you what changed, not how the thing works now or why. After a month away, reconstructing the sync logic’s edge cases from commit messages is archaeology — and a fresh AI session starts from nothing at all, so it re-derives or rebuilds what already exists. GitHub stores your code; it doesn’t hand the next session a current, plain-language map of how each feature works and what’s already planned. afterclick does — the feature catalog and roadmap are read into every session at startup, so neither you nor the AI begins from a blank slate.
For the senior engineer
You’ve felt this every time you returned to a codebase — yours or someone else’s — and had to rebuild the mental model from scratch. afterclick is that mental model, persisted and handed to whoever (or whatever) opens the project next. For a senior, the value lands the first time a fresh agent extends `queue.ts` instead of reinventing it: the context tax you’ve paid your whole career, finally amortized.
What it replaced for you
- The two days of re-learning your own codebase.
- The stale README that no longer matched reality.
- The duplicate, conflicting implementation the AI would have built.
- The reintroduced bug from forgotten edge cases.
The outcome
Lena shipped the new feature in an evening, not a week. The project’s memory carried the context her own had lost — and the AI built on what was there instead of around it.
Sound like you?
One paste, AI included, free to start.