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This chapter walks through running a single Claude Code session end to end on a real app — writing a strong first prompt, reading and correcting the model's plan, building a trustworthy project memory file, and cleanly resuming work the next day — then closes with a roundup of recent pricing, rate limit, and SDK changes.
Learning your codebase, one session at a time
The core of this chapter is a single hands-on walkthrough of running one Claude Code session properly, using an ordinary TypeScript/Next.js app with Postgres behind it as the running example. It opens with the problem of a session that keeps rediscovering the same facts about a repository — how to run the tests, where things live — because nothing was ever written down for it to read. From there it builds out a full first prompt: naming the goal in outcome terms, scoping what not to touch, pointing at the real files or an existing pattern to imitate, and stating a concrete done-condition such as a test that fails without the change. It covers how to read the plan that comes back — checking the file list, the silent assumptions, and whether the approach matches the project's actual conventions — and makes the case for interrupting the moment an assumption is wrong rather than after several files have been built on top of it.
From there it turns to project memory: generating a starter file with the init command, then cutting it down to only what's true and verified — real commands, real layout, real conventions — while stripping out prose, philosophy, and anything nobody will maintain. It explains how these memory files stack rather than override each other, how nested files load lazily, and how imports work. It closes with finishing a unit of work cleanly and picking it back up, covering the continue and resume flags, the from-pr option, and the naming and forking commands that make sessions easier to find again.
This week in Claude Code
The main item is pricing: Sonnet 5's standard rates are now set at $2 per million input tokens and $10 per million output tokens, cancelling a planned increase, alongside removal of peak-hour throttling and doubled five-hour rate limits on paid plans.
A recent changelog entry adds separately configurable prompt cache lifetimes for main sessions and subagents, finer usage telemetry, an organisation-configurable model picker, and a fix for remote tool servers dropping their connection in print mode. Recent releases also brought a design-drafting command preview, a Concise output style, persistent goal conditions across resumes, and an environment variable for setting a default model. On the SDK side, the Python Agent SDK picked up in-process Model Context Protocol server support and a structured error type, and the platform Python SDK reached version 1.0 on a new HTTP transport.