Claude for Design Work: How to Stop Repeating the Same Taste Arguments Every Session
Running a web agency on Claude (Cursor, Claude Code, custom skills) produces solid code fast, but design taste degrades across sessions. The root cause: Claude has no persistent memory of rejected variants, accepted tokens, or design judgments. Brand facts are preserved; taste history is not.
The Core Problem
- A Stripe-inspired hero brief (brand docs, screenshots, 6K-token system prompt) generated gradient mesh, glassmorphic cards, feature pills, glow CTAs — generic 2023 SaaS #4 output. It took 18 iterations to fix, and spacing tweaks in prompt 13 reintroduced the glassmorphic card killed in prompt 5.
- A premium law firm brand kit produced fintech-style rounded cards and soft blue because Claude's training distribution averages “professional + clean” to that look.
- Two sections from the same kit (hero vs testimonials) in fresh sessions produced mismatched type pairings and button styling — as if designed by different studios.
Why Prompts and Projects Don't Fix It
Prompts forget. CLAUDE.md stores facts, not judgments. Projects pin documents, not taste history. The accumulated decisions (“8px radius forever,” “no glassmorphism on this account”) vanish each session.
The Workaround (Custom Memory Layer)
The author wired a separate layer that holds:
- Rejected variants
- Accepted tokens
- Voice rules with examples of what the client actually shipped
This subset is injected into every Claude call as live context. Same model, but now reading taste history instead of guessing.
Open Questions
The author asks the community:
- How do you keep taste consistent across sessions in AI-driven design work?
- Has anyone gotten Projects +
CLAUDE.mdto persist judgments (not just facts)? - Anyone using a memory layer (custom or off the shelf) specifically for design work?
📖 Read the full source: r/ClaudeAI
👀 See Also
vllm-mlx fork adds tool calling and prompt cache for local AI coding agents
A developer has modified vllm-mlx to fix tool calling issues and add prompt caching, reducing TTFT from 28s to 0.3s for OpenClaw on Apple Silicon. The fork supports Qwen3-Coder-Next at 65 tok/s on M3 Ultra with working function calling.
Using a Local LLM as a Claude Code Subagent to Reduce Context Usage
A Reddit user demonstrates how Claude Code can delegate tasks to a local LLM running via LM Studio, keeping file content out of Claude's context. The setup uses a ~120-line Python script with LM Studio's tool-calling API to handle file operations locally.
Echo-TTS Ported to Apple Silicon with MLX for Native TTS with Voice Cloning
Echo-TTS, a 2.4B parameter diffusion text-to-speech model with voice cloning, has been ported from CUDA to run natively on Apple M-series silicon using MLX. On a base 16GB M4 Mac mini, a 5-second voice clone takes about 10 seconds to generate, while 30-second clones take about 60 seconds.
SkillsGate: Open Source Marketplace for AI Coding Agent Skills
SkillsGate is an open source marketplace that indexes 45,000+ skills for AI coding agents like Claude Code, Cursor, and Windsurf. It provides semantic search with vector embeddings and one-command installation via npx.