Core Agent Capabilities
Explore what modern AI agents can do: from tool use to complex reasoning
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0 / 5 completedDeep Dive: Core Capabilities
Let's examine each core capability in depth—understanding not just what agents can do, but the constraints, trade-offs, and design implications of each capability.
🔬 Capability Deep Dive
Select a capability to explore its technical details, limitations, and design patterns
🧠 Reasoning: The Core Capability
Reasoning is what makes agents "intelligent"—the ability to process information, make inferences, and generate solutions. But it's not human reasoning; it's pattern matching at scale.
✅ Strengths
- •Multi-step logic: Can follow complex reasoning chains (e.g., "If X, then Y, therefore Z")
- •Pattern recognition: Excellent at identifying similarities to training data
- •Context synthesis: Can combine information from multiple sources
- •Creative problem-solving: Generates novel approaches within learned patterns
❌ Limitations
- •No true understanding: No common sense or real-world grounding—just statistical correlations
- •Hallucination: Will confidently generate plausible but incorrect information
- •Math struggles: Precise calculations often fail (use tools instead)
- •Novel problems: Performance degrades on truly novel scenarios outside training distribution
🎯 Design Patterns
- • Use Chain-of-Thought prompting to improve reasoning quality
- • Validate critical reasoning steps with external checks
- • Provide examples of correct reasoning in context
- • Accept ~90-95% accuracy ceiling for complex reasoning
⚠️ Universal Limitations
Beyond individual capabilities, all agents share fundamental constraints:
💡 Key Insight
Understanding these capabilities isn't about memorizing lists—it's about developing intuition for what's possible, what's risky, and where human judgment remains essential. The best agent systems are designed with these constraints in mind from day one.