10 entries
Keyword: graph-engineering
X post:Shoopy
Boris Cherny, creator of Anthropic's Claude Code, revealed that users approved destructive commands almost every time during tests. Anthropic now relies on an isolated second model with zero conversation context and neuron-level monitoring to enforce security.
131bookmarks60.4kviews
X post:nicco
A post by nicco highlights remarks by Andrej Karpathy asserting that prompting is an ephemeral interface and that graph architectures represent the true architectural layer for agent workflows. It pairs this with a practical guide by seeco on replacing sequential agent chains with explicit graphs.
529bookmarks58.5kviews
X post:nicco
Citing a Stanford lecture by Andrew Ng, author nicco highlights why zero-shot prompt engineering is reaching its limits and being replaced by autonomous execution graphs, supported by a guide on moving away from linear agent chains.
275bookmarks25.1kviews
X post:Mahax
Mahax cites Andrej Karpathy's claim that prompting is disappearing in favour of graphs, and provides a practical guide on graph engineering with Claude to optimise AI agent workflows.
2.4kbookmarks240.8kviews
X post:Mahax
An X post by Mahax highlights a one-hour lecture by Jeff Dean spanning LLM basics to coordinating 100 AI agents. The post also references an accompanying guide on graph engineering using Claude.
3.8kbookmarks273.9kviews
X post:Mr. Buzzoni
Mr. Buzzoni (@polydao) outlines an append-only graph engineering architecture where dedicated agents extract and connect claims without updating existing rows. Using daily sealed log files, DuckDB, and human approval for merges, the system preserves complete auditability.
1.1kbookmarks75.8kviews
X post:CyrilXBT
In a detailed thread, CyrilXBT outlines a curriculum for prospective Graph Architects, combining structured knowledge graphs with state-machine graphs for AI agents to improve on basic RAG and opaque reasoning loops.
725bookmarks67.3kviews
X post:Kirill
Kirill describes an architectural shift in agent development from fragile single-agent loops to Graph Engineering. He argues that system reliability depends not on larger models or more agents, but on deterministic structures using nodes, edges, state verifiers, and knowledge graphs.
27.3kbookmarks2.7mviews
VideoVideo:Greg Isenberg
Greg Isenberg breaks down graph engineering as the layer above prompt and context engineering. Rather than running complex tasks through a single chat prompt, work is structured into discrete jobs, parallel paths, independent checks, and human approvals. In addition to distinguishing knowledge graphs from agent graphs, he demonstrates practical workflow patterns and three implementation levels ranging from manual runs to tools like LangGraph and n8n.
X post:codila
Codila highlights a free two-hour Google course on graph engineering for multi-agent systems and outlines how to evolve beyond linear agent sequences into networked parallel graphs. Using Dynamic Workflows in Claude Code v2.1.154+, the guide demonstrates orchestrating hundreds of agents simultaneously without exhausting context windows.
6.8kbookmarks465.4kviews
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