Claude Research, Plan, Implement: Keep Each Step Grounded

A Claude research, plan, implement workflow separates finding evidence, choosing an approach, and making the change. Ask for a checked research summary first, approve a specific plan next, and verify the implementation against observable results rather than accepting a confident completion message.

This is a working method you can describe in plain language, not a universal Claude research command. fenbs keeps the evidence, human decisions, and next step together when the stages happen in different sessions or supported AI apps.

What are the steps from research to implementation?

1. Define the outcome and boundaries. Say what should change, what must stay stable, and which actions need a person’s approval.
2. Research the current situation. Ask Claude to inspect the relevant material, identify primary sources, and separate observations from assumptions.
3. Review a plan. Require a proposed approach, affected files or deliverables, open questions, and a way to check success.
4. Approve a specific version. Record any changes you make to the plan before authorizing implementation.
5. Implement and verify. Compare the result with the agreed outcome, then save completed work, actual checks, and unresolved next steps.

Anthropic’s Claude Code best practices↗ (opens in a new tab) recommend separating exploration and planning from coding. The same distinction helps a noncoding project: researching a customer guide, agreeing its structure, and drafting the approved sections are different jobs. Each needs a clear output.

Use the full sequence for work with real uncertainty. A corrected typo may need only a direct edit and a quick check. A change to account recovery, a long report, or a migration deserves more care because a mistaken assumption can affect several later choices.

What should Claude research before proposing a plan?

Start with the thing that exists. For a software task, that means the current code, nearby conventions, repository instructions, and relevant checks. For a writing task, it means the audience, approved source material, existing draft, and claims that need verification.

Ask for a compact evidence record. Each important finding should say what was observed, where it was found, and what it means for the requested outcome. “This path retries twice” is an observation to check in code. “Two retries are enough” is a judgment that needs a reason.

• Known facts: source-backed details that affect the work.
• Open questions: missing information that could change the approach.
• Constraints: instructions, access boundaries, and required checks.
• Possible approaches: a short explanation of the meaningful choices.
• Recommendation: a proposal with reasons, clearly separated from approval.

For example, say you want a password reset message to explain what happens next. Research should inspect the existing message and actual reset flow before suggesting wording. Otherwise a polished draft could promise an email, timing, or account behavior the product does not provide.

An assistant-led investigation is a separate question from the stage handoff described here; see Claude research agents for that workflow. Keep the summary short enough that a reviewer can inspect the evidence behind the recommendation.

What makes a plan ready for approval?

A plan is ready when a person can understand the intended result and the limits of the authorization. It should name the deliverable, the main changes, the risks that matter, and the evidence needed to call the work complete. Avoid steps such as “make it better” that cannot be checked.

For coding work, Anthropic documents plan mode↗ (opens in a new tab), where Claude Code explores and proposes changes without editing source files until approval. Our Claude Code plan mode guide covers that feature in more detail. A written plan still needs a person to review its assumptions.

Record what the person actually approved, including exclusions. If the reviewer removes a database change from the plan, the implementation handoff must show the revised scope. Decisions and rules in fenbs preserve that choice so a later session does not revive an earlier proposal.

How do you keep implementation inside the approved scope?

Begin implementation with the approved plan and the small set of facts that support it. Ask Claude to identify the first action and the check that will follow. This gives you a chance to catch a stale assumption before it becomes a larger change.

Use explicit stop conditions for meaningful scope changes. Discovering an unrelated typo may be routine; discovering that the plan requires a new external service may change the decision. Ask for the new evidence and a revised recommendation when the original approval no longer describes the proposed work.

Keep approval separate from tool access. An assistant may have permission to edit files while still needing authorization for the particular release, payment, or live-data change. State those boundaries in ordinary language and carry them into the handoff rather than assuming a tool setting expresses every project decision.

If you are new to the coding environment, the Claude Code introduction explains its role. This workflow does not require moving every project into a coding tool; use the application that can actually inspect and change your deliverable.

How should you verify the finished work?

Check the behavior promised in the plan. For the reset message, compare the final words with the actual flow and exercise the relevant success and failure states. For a research report, follow the cited sources and confirm the conclusions do not outrun the evidence.

Ask for the checks that ran and their results. A proposed check is not a completed check, and a tool error is not a passing result. Record anything a person still needs to confirm, such as whether a design reads clearly to its intended audience.

When verification fails, describe the failure precisely enough to repeat it. Revise the implementation within scope, or return to planning if the failure changes the approach. Keep the current status visible rather than replacing “untested” with “done” because the output looks plausible.

How to do this with fenbs

1. Create a free account and add a project for the work. One person can start free, with no credit card.
2. Create a task with the problem and expected result. Save the research findings as concise AI context notes with source references, and keep proposed implementation steps in the task’s plan.
3. Record the person’s approved choice in Decisions and rules. Leave unanswered questions open; an assistant cannot decide or sign off for the person.
4. Connect your supported Claude app through the integration guides. Ask it to read the project context before starting and save task progress, verification results, and the next step before it stops.

fenbs does not automatically import Claude chats or verify your research. If a single short task fits in one conversation and needs no later handoff, that conversation may be enough. Use a separate work record when approvals and progress must remain available beyond that session.

What belongs in the handoff between stages?

Save the current goal, checked findings, approved plan version, completed changes, actual tests, and next action. Include links or paths to the working material. Mark assumptions and waiting decisions so the next assistant does not mistake an unresolved question for an instruction.

Before continuing, ask the next assistant to explain what it will do and why. Its answer should match the saved approval and recognize unfinished checks. The context engineering guides explain other ways to keep an assistant’s starting material focused on the work ahead.