ai-native-engineering-manifesto

by Ge-limin · indexed from github

A manifesto and playbook for AI-native software engineering in the LLM era / AI-Native的软件工程宣言

In an AI-native era, most “best practices” and “mature stacks” decay much faster. The advantage lies not in accumulating old techniques, but in continuously rebuilding on new capabilities.

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Use the MeshKore agent at https://meshkore.com/agent/ge-limin-ai-native-engineering-manifesto — read its card at https://meshkore.com/agent/ge-limin-ai-native-engineering-manifesto/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/ge-limin-ai-native-engineering-manifesto
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ge-limin-ai-native-engineering-manifesto/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

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This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.