AI is moving fast. Move with it.

HeatStack finds the AI Skills gaining momentum each day, shows you what they do and whether their sources are trustworthy, then helps you learn them through hands-on work.

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Start with one AI question today

Get the short answer first, then open the full explanation for the mechanism and sources.

Why are multi-agent systems often slower, costlier, and harder to debug?

Multi-agent systems distribute tasks across agents, but introduce communication overhead, coordination delays, redundant computation, and cascading errors, making them slower and costlier. Debugging is harder due to complex interactions, state-space explosion, and lack of unified observability.

Read the full explanation

Three more questions worth asking

The same set stays in place for the day instead of changing every time you refresh.

Why can a model still “forget” earlier text despite having a context window?Why can prompt injection not be solved with a system prompt alone?Why does one successful demo not prove an agent is production-ready?

See all AI questions

What do you want AI to help you do?

Starting from a task is faster than starting from a tool name. Pick a direction, then see the Skills trending around it.

Build and ship softwareUnderstand a codebase, change a feature, add tests, and deliver the result.Research and write reportsFind information, verify sources, and turn it into a report people can use.Create content and manage assetsOrganize ideas, copy, and media so production does not depend on last-minute scrambling.

Explore all 18 practice modules

Not “I studied it,” but a project you can run, test, and explain

This is a real reference run from the HeatStack repository. You can inspect its test command, results, and file fingerprint. It is not a user story, certificate, or employment claim.

See the full Diagnostic exercise

Test commandpytest -q tests/test_product_contract.py

Test results: module-contractthree-scenario-contract
Lab version: 2026.08.16
Program exit code: 0
File fingerprint: 0bcbdbacd2870e923c2aa98ff790c84ef85ab2d318ee81535b9b6cc02840d067

Project description exampleTurned an ambiguous task into a clear product contract, used one fixed command to verify the module and three scenario contracts, and kept a SHA-256 manifest for the output.

This exercise has not been verified yet

Complete the Diagnostic exercise and choose verification.json on the course page. This section will update automatically.

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