Core Agent Capabilities
Explore what modern AI agents can do: from tool use to complex reasoning
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0 / 5 completedUnderstanding Agent Capabilities
AI agents are powerful systems, but they're not magic. Understanding what they can and cannot do is crucial for building reliable, production-ready agent systems.
🎯 What You'll Learn
- ✓The four core capabilities every agent needs: reasoning, tool use, memory, and planning
- ✓Practical limitations and failure modes you'll encounter in production
- ✓How to design around constraints while maximizing agent effectiveness
- ✓Real-world examples of capability-aware system design
The Capability Spectrum
Modern AI agents operate across a spectrum of capabilities. They're remarkably good at some tasks, acceptable at others, and surprisingly limited in areas that might seem simple. Understanding this spectrum is the foundation of building reliable agent systems.
� Explore Core Capabilities
Click each capability to see what agents can and cannot do
Reasoning Capabilities
- • Break down complex problems
- • Follow multi-step logic
- • Synthesize information from context
- • Generate creative solutions
- • No true understanding or common sense
- • Struggle with novel problem types
- • Limited mathematical precision
- • Can confabulate plausible but wrong answers
Why Capabilities Matter
Understanding these capabilities isn't academic—it directly impacts how you design, build, and deploy agent systems:
Design Phase
Know what's possible before committing to an architecture. Avoid designing systems that require capabilities agents don't have.
Development Phase
Build guardrails and fallbacks for known limitations. Plan for failure modes rather than discovering them in production.
Production Phase
Monitor capability boundaries in real-world use. Understand when agents need human intervention.
Scaling Phase
Optimize for capability bottlenecks. Know which constraints will hit first as you scale.
⚡ Key Insight
The best agent systems aren't those that push capabilities to their limits—they're those designed to work reliably within capability boundaries. Understanding constraints is more valuable than understanding possibilities.