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Hi! I'm your AI Assistant
I can help you analyze interview sessions, understand candidate performance, and provide insights about your recruitment data.
SKILL.md files, giving agents expertise only when needed.Here's an uncomfortable truth: Most AI implementations are wasteful.
Developers and founders are cramming everything—documentation, guidelines, examples, edge cases, historical context—into a single prompt. They're treating context windows like infinite resources. They're not.
Even with models boasting 1M+ token contexts (looking at you, frontier Pro models), there's a cognitive cost. More context means more noise. More noise means slower inference, higher costs, and—counterintuitively—worse decision-making.
Think about it: When you hire a specialist consultant, you don't hand them your entire company wiki. You give them the relevant brief. The same principle applies to AI agents.
At JobInterview.live, we built the AI Board Room on a radical premise: Agents should know everything, but remember only what matters.
This is Progressive Disclosure. And it changes everything.
Progressive Disclosure is a design principle borrowed from UX: Show users only what they need to see, when they need to see it.
In AI architecture, it means:
SKILL.md files)Instead of Atlas (our Strategy specialist) carrying around knowledge about SQL optimization, financial modeling, AND content strategy simultaneously, Atlas loads only the skill required for the current task.
When you ask about market positioning? Atlas loads market_analysis.SKILL.md.
When you pivot to pricing strategy? Out goes market analysis, in comes pricing_strategy.SKILL.md.
This isn't just elegant—it's necessary.
Each SKILL.md file is a self-contained expertise module. Think of it as a microservice for knowledge.
Here's the anatomy:
# SKILL: [Domain Expertise Name]
## Context
When this skill is needed and why it matters.
## Core Principles
The fundamental truths that guide this expertise.
## Frameworks & Methods
Step-by-step approaches, decision trees, templates.
## Common Pitfalls
What to avoid (learned from real-world failures).
## Integration Points
How this skill connects to other domains.
When Atlas needs to evaluate a market opportunity, the system dynamically loads:
When the conversation shifts to, say, hiring? That skill unloads. Atlas becomes a clean slate, ready for the next expertise injection.
Let's get provocative: If you're loading your entire knowledge base into every agent interaction, you're building a system that looks smart but acts dumb.
1. Dilution of Signal
When an agent has 50 skills loaded simultaneously, it becomes a generalist. Generalists are useful, but they're not who you call when you need a expert opinion. You want Cipher (our Tech Architect) to think like a senior engineer, not a Wikipedia article.
2. Latency & Cost
Every token in context costs money and time. Processing 100K tokens vs. 10K tokens isn't just 10x slower—it compounds. For real-time systems like Native Audio (our voice mode), this latency is user-facing. Unacceptable.
3. Decision Paralysis
Too many frameworks create analysis paralysis. When Cipher evaluates a tech stack, we want decisive recommendations based on relevant criteria, not a hedge-fund prospectus of every possible consideration.
Progressive Disclosure cuts through the noise.
Let's walk through a real scenario.
User: "I'm launching a B2B SaaS tool for freelance designers. What's my GTM strategy?"
Step 1: Action Extraction
The system (powered by our Deterministic Backbone via Google ADK) identifies this as a strategy question. Routes to Atlas.
Step 2: User Dossier Check
Atlas pulls context: User is a solo founder, budget-conscious, design background, first SaaS launch. This shapes the advice.
Step 3: Dynamic Skill Loading
Atlas loads:
market_analysis.SKILL.mdgtm_strategy.SKILL.mdpositioning_messaging.SKILL.mdAtlas does NOT load:
financial_modeling.SKILL.md (not needed yet)hiring_strategy.SKILL.md (premature)legal_compliance.SKILL.md (irrelevant to this question)Step 4: Response with Delegation
Atlas provides strategic direction, then delegates:
"I'll bring in Pulse (our Marketing specialist) to detail your content strategy, and Cipher to evaluate your unit economics for scalability."
Step 5: Agent-to-Agent (A2A) Protocol
Nova and Cipher activate their relevant skills. Nova loads content_strategy.SKILL.md and audience_research.SKILL.md. Cipher loads saas_architecture.SKILL.md.
Each agent operates with surgical precision.
Step 6: Critic Agent Review
Before delivery, the Critic Agent (our QA layer) validates:
This entire orchestration happens in seconds. The user experiences a cohesive "board meeting," not a Frankenstein's monster of generic advice.
Here's where it gets interesting.
Progressive Disclosure doesn't just save tokens—it enables emergent behavior.
Because agents aren't bogged down by irrelevant context, they can:
pricing_strategy.SKILL.md without touching Atlas's core identity.market_analysis.SKILL.md is loaded.This is the difference between a chatbot and a system.
You don't need to build an AI Board Room to apply this thinking.
1. Modularize Expertise
Stop hiring "full-stack everything" people. Build a team (human or AI) where specialists activate on-demand. Your designer doesn't need to sit in every engineering standup.
2. Context is Expensive
Every meeting, email, and Slack thread has a cognitive cost. Be ruthless about what's need-to-know vs. nice-to-know.
3. Automate Routing
Use systems (like Action Extraction) to route problems to the right expert automatically. Stop playing traffic cop.
Imagine this:
You're building a fintech startup. You subscribe to regulatory_compliance_fintech.SKILL.md from a vetted provider. Your AI Board Room now has expert-level compliance knowledge—updated in real-time as regulations change.
You pivot to crypto? Unsubscribe from fintech compliance, subscribe to crypto_regulation.SKILL.md.
This is where we're headed. Skills as modular, updateable, shareable expertise. The AI equivalent of npm packages or WordPress plugins.
Reading about Progressive Disclosure is one thing. Experiencing it is another.
The AI Board Room at JobInterview.live is live. Talk to Atlas about your strategy. Let Cipher audit your tech stack. Watch Nova craft your messaging.
Notice how each agent feels like a specialist, not a generic assistant. That's Progressive Disclosure at work.
Solo founders, entrepreneurs, freelancers—you don't need to hire a full executive team. You need the right expertise, at the right time.
[Start your first Board Room session at JobInterview.live →](/ai-boardroom)
The future of work isn't about having all the answers. It's about knowing which questions to ask—and loading the right expertise to answer them.
