My background
My field of study was BI/ML but i ended up working as an odoo developer. Recently, i ‘ve been drawn to exploring the field of artificial intelligence with all the hype around ai agents, automation, vibe coding.
I started experimenting with AI editing tools such Claude code, windsurf, etc. all of these tools have some common features, which focus on : generating execution plans, managing memory through markdown files or builtin tools. executing plans through tool calls in order to interact with the development environment.
The Three frustrations
Some of the most frustrating issues i encountered while experimenting building professional or testing product ideas were :
- Intent misalignment: the AI does not fully understand my intent due to poor communication structure or stale context that pollutes the model’s prediction. The outcome will be broken features, deleted code you need.implementations that miss the point entirely.
- Ai amnesia : long contexts that by pass the token limits cause the model to lose critical information. You find yourself re-explaining the same architectural decisions, re-injecting large amounts of context trying alignment and understanding.
- Random pollution : Even with explicit instruction and communication modes, AI editors still magically generate markdown files, using scripts for repetitive tasks instead of calling direct read/write tools, or make arbitrary decisions that break your workflow patterns
These problems grows exponentially in larger projects, Then the most important skills is not creating clever prompts, it’s how creating structured efficient communication, well writing specification and engineering the context for predictable outcomes.
What I Learned from Claude Code
Of all the tools I’ve tested, Claude Code offers sophisticated solution to these problems:
- subagents: each subagent have a specific role in the system, create it’s own context window separately, preventing context pollution.
- dynamic delegation : the main agent delegate tasks to the most appropriate subagent
- hooks: Custom functions to execute before or after every tool use. Giving programmatic control.
With these tools, i built a guided system of specialized subagents (planner, frontend, backend, verifier ..) It works remarkably well after huge amounts of tinkering and iteration.
What become clear: even with a well engineered subagent system, you need a source of truth in the form of well managed, structured specifications that compile to any form of code.
The implications are profound : if specifications become the primary artifact, then the most effective programmer will be the excellent communicators and specification creators.
The aha moment
in a quiet moment, while trying to align Claude code to generate the exact specification i wrote in my prd file. it hit s me, all developers using AI editors suffer from the same memory problem. What if we could build a layer that solves this once, for everyone?
A persistent memory layer that maintains specifications across all your conversations, across all your tools, across all your projects. an AI assistant that never forgets
What I'm building
SpecVault is the memory layer for AI development.
it remembers:
- Every feature you've discussed
- The "why" behind decisions
- User stories and their evolution
- What you've validated and what's still uncertain
- Specification conflict resolution
- Implementation lineage from spec to code
it structures:
- Conversations become living specifications
- Decisions become documented rationale
- Ambiguity gets flagged for clarification
- Patterns emerge and get surfaced
it integrate:
- Export to Jira, or any project management tool
- Generate Claude Code/Cursor/Windsurf contexts with full project knowledge
- Builtin features to rapidly build your product in a predicable manner.
- Open memory model, see exactly what it remembers, edit when needed
- Works across all your AI editors, maintaining consistent context
your specification becomes the source of truth, compiled into whatever format your AI editor needs. You're not managing prompts anymore. You're managing knowledge. And knowledge, unlike conversation history, compounds over time.