Anyone can prompt AI.Can you make it work?
AI skills are becoming essential in operations, RevOps, and analyst roles. AgentMakerLab helps you build them through hands-on challenges using real business scenarios. Diagnose failures, improve AI agents, and build a portfolio that proves to employers what you can do.
Sponsored in part by Hourback.io — The leading agentic workflow adoption tool grounded in real world processes.
The framework
Four skills hiring managers actually test
Evaluate
Benchmark models and tools against real tickets before anyone ships.
Implement
Wire agents to tools with guardrails, policy tiers, and fallbacks.
Monitor
Read traces and catch silent failures before customers do.
Optimize
Trade off accuracy, latency, and cost with eval data, not vibes.
Agent Tool Radar
Tested hands-on, not copied from landing pages
n8n
tested Oct 28, 2026
+ Self-hostable, deep control
− Steeper learning curve
Open-source / per-execution cloud
Make
tested Oct 30, 2026
+ Visual scenarios, huge app library
− Costs spike with loops
Per-operation credits
Relevance AI
tested Nov 2, 2026
+ Agent-native, multi-agent teams
− Opaque credit burn
Seat + action credits
Gumloop
tested Nov 4, 2026
+ Fast no-code AI flows
− Limited observability
Tiered credits
Microsoft Copilot Studio
tested Nov 6, 2026
+ M365 & governance built-in
− Locked into MS ecosystem
Per-message capacity packs
Verified portfolio
Proof, not certificates
Every challenge produces a verifiable record of what you fixed, the trade-offs you made, and the eval delta you shipped.
