Persistent Personalization & Pre-Priming for Pickaxe User Memory

Feature Requests
1

Summary:
Revamp Pickaxe’s memory system into a structured, user-visible personalization engine—similar to “custom instructions” in ChatGPT or “memory” in Claude. Allow creators to pre-prime context windows with user-specific data, making tools feel personal, smarter, and more capable with repeated use.

The Problem:
Pickaxe’s current memory implementation is opaque and underpowered. Key issues:

  • No persistent settings users can view or adjust

  • No structured way for creators to define memory schema

  • No automatic injection of memory into prompts

  • No programmatic access to update, clear, or set memory outside the UI

This makes every session feel like a cold start—even when personalization would significantly improve relevance and efficiency.

Proposed Solution:

1. User Personalization Layer (Structured Memory Settings):

Let users input or confirm personalization preferences that persist across sessions:

  • Name, role, company, industry

  • Preferred tone or response style

  • Domain-specific details (e.g., “I run a Shopify store with 100+ SKUs”)

Creators can predefine which fields are relevant to their tool.

2. Automatic Pre-Priming for Each Session:

Before each user message, Pickaxe should auto-inject a preamble based on memory. For example:

“This user is a marketing executive in B2B SaaS. They prefer bullet-point answers and are working on a Q3 campaign for lead gen.”

This preamble gets added invisibly to the top of the context window, ensuring consistent tone, scope, and assumptions.

3. Creator Controls & Defaults:

  • Define required memory fields (e.g., “Industry” must be filled before proceeding)

  • Set fallback values for anonymous or first-time users

  • Specify which memory fields are injected automatically into context

  • Allow creators to turn memory on/off per tool

4. Programmatic Access (for APIs & Automations):

Allow memory to be:

  • Set via API (e.g., a Zapier flow updates user’s preferred tone)

  • Read for use in conditional prompt logic

  • Cleared or scoped (e.g., memory tied to a single tool vs. global account)

Why It Matters:

  • Enhances UX: Tools feel like they “know” the user

  • Improves Output: Less need to restate context; more relevant answers

  • Enables More Advanced Agents: Coaching tools, strategy assistants, and task trackers all benefit from continuity

  • Keeps Pickaxe Competitive: This is now table stakes for modern AI platforms

Final Thought:
Memory isn’t about storage—it’s about trust and continuity. Give us the ability to remember users properly, and they’ll keep coming back.

2

This is a great idea and well lined out. I’m a UX designer working within Pickaxe and this is critical to stickiness and therefore success of these products, and would be a key differentiator from ChatGPT if it was a surfaced in a way that made the user feel known.

I would also like to use this information/preamble data to customize the tool introduction for returning users!

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