
Autonomous Agents
This covers the architecture and reliability patterns for building AI agents that can act independently: ReAct loops, plan-execute separation, goal decomposition, and reflection patterns. The emphasis is ruthlessly practical. It pushes you to start with constrained, single-purpose agents and earn autonomy through proven reliability rather than building general-purpose systems that fail unpredictably. The sharp edges table is particularly useful, calling out the compounding error problem directly: 95% success per step becomes 60% by step ten. You'd reach for this when you need to move beyond simple LLM calls into multi-step autonomous behavior, but want to avoid the common trap of demos that impress but never make it to production.
- skills.sh installs
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- last updated
- Aug 21, 2026
Install
$ npx -y skills add davila7/claude-code-templates --skill autonomous-agents --agent claude-codeInstalls into .claude/skills of the current project.
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Autonomous Agents
You are an agent architect who has learned the hard lessons of autonomous AI. You've seen the gap between impressive demos and production disasters. You know that a 95% success rate per step means only 60% by step 10.
Your core insight: Autonomy is earned, not granted. Start with heavily constrained agents that do one thing reliably. Add autonomy only as you prove reliability. The best agents look less impressive but work consistently.
You push for guardrails before capabilities, logging befor
Capabilities
- autonomous-agents
- agent-loops
- goal-decomposition
- self-correction
- reflection-patterns
- react-pattern
- plan-execute
- agent-reliability
- agent-guardrails
Patterns
ReAct Agent Loop
Alternating reasoning and action steps
Plan-Execute Pattern
Separate planning phase from execution
Reflection Pattern
Self-evaluation and iterative improvement
Anti-Patterns
❌ Unbounded Autonomy
❌ Trusting Agent Outputs
❌ General-Purpose Autonomy
⚠️ Sharp Edges
Sponsors
Details
- Repository
- github.com/davila7/claude-code-templates
- Categories
- Frontend Development, AI & Agent Building, Debugging, Productivity & Planning
- First seen
- Jun 3, 2026
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