Claude Code Features That Matter After the First Demo
ZarifThe first impressive demo gets an agent into your workflow. What happens on the fifth task determines whether you keep using it.
Does it remember the project's constraints? Does it show how it checked the change? Can you pick up the work later without reading the entire conversation?
Those are the questions I would use to decide which Claude Code features deserve attention.
Correction, September 5, 2026: the earlier article attributed a specific feature list and personal working habits to Boris Cherny without a linked original source establishing them. That framing has been removed. This guide uses current documentation and editorial recommendations, not a creator interview or a hands-on benchmark.
Persistent context: stop repeating the project
Claude Code documents project instructions in CLAUDE.md and automatically saved memory as complementary sources of context. The useful distinction is between instructions you deliberately maintain and notes accumulated during work. Memory documentation.
My recommendation is to begin with the things you otherwise repeat: the project layout, the commands that validate a change, and the mistakes the agent should avoid. A note about a past task should not silently override the current project state.
The CLAUDE.md guide expands this approach with a small template based on this site's actual working principles.
Verification: define an observable result
Anthropic's best-practices guide recommends giving Claude a way to verify its work, such as tests, screenshots, or expected output. It also discusses exploring and planning before implementation where appropriate. Claude Code best practices.
The part worth adopting is the observable finish line. “Improve this page” leaves too many decisions implicit. “Correct the unsupported claims, preserve the URL, validate links, and confirm the build” is a task that can be reviewed.
This does not require building an elaborate benchmark for every article. A factual correction can be checked against its source. A layout change can be inspected. A claim about conversion needs actual conversion evidence.
Task boundaries: keep the assignment coherent
My preference is for an agent to make routine decisions within the work I have already authorized. Repeatedly asking whether it should continue can create more work than it removes.
That preference needs a boundary. Editing a draft and emailing it to a customer are different actions. Producing a deployment plan and deploying are different outcomes.
Write down the desired result and the actions covered by the assignment. Then require the agent to report the actual state, including anything it could not complete.
Handoffs: save the part the next session needs
The useful output of a long task is not just the chat transcript.
Ask for a short handoff with the changed files or artifacts, the verified result, and the remaining decision. Put durable instructions in the project's maintained notes. Keep temporary status somewhere it can be updated without becoming a permanent rule.
This is an operating recommendation rather than a claim that every product automatically assembles the same memory system.
Choose features around a recurring problem
A feature deserves attention when it removes friction you actually encounter. If you keep restating the same project constraint, improve context. If the agent stops at plausible code, improve the completion criteria. If finished work is hard to find, improve the handoff.
That is a more useful starting point than turning every available capability on at once.
Related Guides
- Claude Code vs GitHub Copilot: AI Coding Compared
- n8n vs Zapier: The Honest Comparison for 2025 (Pricing, Features, and Who Should Use Each)
- Claude Managed Agents vs n8n: The Real Difference (And Why You Probably Need Both)
Are these Boris Cherny's personal recommendations?
No. The previous attribution was not adequately sourced. This article now distinguishes vendor documentation from the author's operating recommendations.