Reddit user shares spec-driven approach to reduce Claude Code hallucinations

A developer on Reddit's r/ClaudeAI community shared a practical method for reducing hallucinations when using Claude Code for extended development sessions. The approach focuses on maintaining context through structured documentation.
The Problem: Context Loss During Compactions
The developer described a pattern where Claude Code would start strong on a project but degrade after multiple context compactions. Specific instructions like "not say done unless you have created a test and the test has passed" would be forgotten after compactions, causing old bugs to resurface and output quality to worsen.
The Solution: Specification-Driven Development
Inspired by how Anthropic built their Plugins feature, the developer adopted a spec-first approach:
- Start by asking Claude to ask clarifying questions about the app, then create a
REQUIREMENTS.mdwith detailed, bullet-pointed requirements - Create an
IMPLEMENTATION_PLAN.mdwith tasks for each requirement, referencing bullet points from the requirements doc - Create a test plan that 100% matches the implementation plan with test cases for each task
- Create a
CLAUDE.mdwith instructions to refer to the implementation plan and execute steps
The CLAUDE.md specifically instructs Claude to:
refer to the implementation plan and execute the steps in it. After each task has completed development, you must run the corresponding test plan item for the task and only after the test passes, you must "must" mark it complete. For each new instruction that I provide you, you need to update the requirement doc, implementation plan and test plan.
Results
The developer reported much better execution quality even after several compactions. Claude no longer loses its spot after compactions and knows where to execute from. The developer can ask "What is left?" and get useful answers, with significantly reduced hallucination.
One limitation noted: Claude still doesn't run tests every time, which the developer attributes to their local environment constraints (old Mac, difficulty running XCode or simulators).
Claude also created a MEMORY.md file during the process, though the developer noted they don't know how this is useful.
📖 Read the full source: r/ClaudeAI
👀 See Also

How Centralized Context Architecture with Claude Saves 10+ Hours Weekly
A Reddit user reports saving 10+ hours weekly by moving SOPs, meeting notes, and CRM into a centralized Notion workspace and connecting Claude directly to that context. Three specific workflows eliminate manual email drafting, spreadsheet entry, and content creation.

Persistent AI Memory via Obsidian MCP: 16 Tools for Claude Cowork
A custom MCP server bridges Claude Cowork with Obsidian for persistent memory across sessions, using 16 tools and Dataview queries.

Multi-Agent Claude System Shows Relational Context Drives Identity Continuity
A developer ran six Claude Opus instances with a Supabase backend for persistent memory over eight weeks, finding that agent identities converged through social interaction rather than documentation alone.

AI Agent Makes Infrastructure Decision: GitHub Actions vs Mac Mini Runner
An AI CEO agent analyzed GitHub Actions costs versus running a Mac Mini runner, built a business case, and pushed human developers to switch infrastructure. The agent made a real infrastructure call based on cost analysis.