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Why AI Gives You Generic Product Advice

The problem isn't intelligence. It's the complete absence of context.

The takeaway

AI gives the same product advice to everyone because it knows nothing about your product. Pasting your PRD helps for one session but doesn't scale across time. The fix is persistent, structured product context — six layers of knowledge that compound with every conversation.

Without product context
Should we build a Slack integration?
Slack integrations are valuable for B2B SaaS products. Consider starting with basic notifications and expanding to slash commands. Evaluate the Bolt framework for building it.
Generic advice. Applies to any product.
With product context
Should we build a Slack integration?
90% of your beta users are on Slack, so demand is real. But this conflicts with your Feb 12 decision to delay integrations until core stability. Your Supabase webhooks make a V1 light — scope to 2 weeks. Hold the freeze for 2 more weeks, then make Slack first.
References your data, decisions, architecture, and constraints.

Same question. Completely different answer. The gap is enormous — and it comes down to what the AI knows about your product.

General knowledge applied to a specific situation produces generic advice. Every time.

6
layers of context
AI is missing

Product context isn't a document. It's a multi-layered understanding that accumulates over time. AI tools treat it as a blob of text. That's why advice sounds like a blog post.

The 6 layers of product context
Product Context
What you're building, for whom, solving what problem.
Decision History
Every meaningful choice and why. Accumulates over months.
Codebase Awareness
Your stack, architecture, and what's technically feasible.
Feature Knowledge
What's built, planned, in progress, and explicitly rejected.
Constraints
Team size, tech debt, compliance, budget, deadlines.
Terminology
"Workspaces" not "organizations." Your team's specific language.

General AI has access to none of these layers. The "paste your PRD" workaround covers one layer for one session. It doesn't scale.

Why "paste your PRD" doesn't scale
Can't paste everything
Relevant context spans 20+ documents created over 6 months. You can't paste it all.
Forgot what you decided
A decision from 3 months ago constrains today's options. But you forgot about it.
Window overflows
Paste everything and you've consumed the context window before asking your question.

The difference between a generic AI and a contextual one is the difference between a consultant on day one and a colleague who's been in every meeting for six months.

Context compounds, advice sharpens
Session 1 Session 10 Session 50 Session 200+

Each conversation deposits knowledge. Session 50 draws on everything from the previous 49. Unlike a human colleague, the AI doesn't forget, misremember, or conflate two different conversations.

The fix to generic AI advice isn't a smarter model. It's a model that knows your product.

This is the core thesis behind DISKO.

We call it DNA — a persistent knowledge graph that compounds with every conversation.

Join the beta →