Get up to speed on an unfamiliar codebase in an afternoon — ground the AI in the project, have it explain the hard parts, and keep what you learn.
The slowest part of joining a project isn't writing code — it's the weeks of figuring out where things live, why they're arranged this way, and which files you're allowed to be scared of. AI can compress that, but only if you set it up right: give it the project's shape first, ask for explanations at the level you actually need, and capture what you learn so you're not re-asking the same questions in every new chat.
Each step uses an existing NewPrompt tool, pre-filled by a matching resource. Open the resource to read it, or jump straight into the tool with the inputs ready.
Set up what the project is
Build a short profile of the project — stack, domain, conventions, what it's for — so every explanation the AI gives is grounded in this codebase instead of a generic one. You write this once and reuse it.
Get the lay of the land
Ask for an architecture-level tour: the major pieces, how they fit, where a request flows. Go wide before you go deep — on day one the map matters more than any single file.
Open up the files everyone avoids
Every codebase has a 900-line class or a module nobody volunteers to touch. Have the AI walk it section by section until it stops being a black box.
Save what you learned for next time
Package the context and the explanations into a handoff you can paste at the start of your next session, so the AI — and future-you — resumes warm instead of relearning the project every chat.
You come away with a mental model of the codebase's architecture, a real understanding of its hardest parts, and a reusable context profile so the knowledge sticks. Days of ramp-up compressed into an afternoon.
Explaining one file is a single step here (step 3). The workflow runs it inside a bigger arc: you set a project context profile first (step 1) so every explanation is grounded in this codebase, work architecture-down to the scary files, then save the result so you never re-onboard the AI from scratch.
Onboarding is about you understanding the project, not feeding the whole repo to the model. Work module by module. If you genuinely need to fit large amounts of code into context, that's a separate job for the context tools.
Yes — that's the point of the last step. The handoff and project profile become the opening context for future sessions, so the model starts informed instead of blank.
Three things: a mental model of the architecture from step 2, a section-by-section walkthrough of the intimidating files from step 3, and a reusable context handoff from step 4. The handoff is the durable artifact — you paste it to open future sessions warm.
Run the four steps in order in your own AI tool. Build a project context profile with the project-context-builder, feed it in, then use the code-explanation-prompt for the architecture tour and the hard files, and finish with the context-handoff-builder. NewPrompt supplies the prompts; you run them.
Check it against the actual code, not the AI's confidence. Open the files it described, trace one real request path yourself, and confirm the architecture claims match imports and call sites. If an explanation contradicts the code, re-ask with the specific file pasted in — the model may have guessed.
Complete build journeys that include this workflow as a stage.
The full path to taming an inherited codebase — understand it, document its architecture, pin its behavior with tests, then refactor, modernize, review, speed up, and ship it without breaking what works.
Generate documentation that matches the code instead of drifting from it — have AI explain what the code really does, write it up as structured docs, then validate the format holds.
Carry a project into a new chat, model, or teammate without the context evaporating — capture the state, distill what's worth keeping, and rebuild it as durable context on the other side.
A complete AI-assisted review pass — not one prompt — that ends with ranked findings, tests guarding behavior, and a refactor plan when one is warranted.