That's at least what every tech bro is saying right now on Twitter.
The next wave, apparently, is graph engineering.
Okay, So What the Heck Is Graph Engineering?
If you picture a normal AI agent, it's typically one model looping through an entire task by itself, over and over, until it decides, yeah, this is good enough.
Graph engineering breaks that into smaller pieces called nodes.
A node is just one specific job, a researcher, a writer, or a fact checker. Each has its own model call or its own agent.
Nodes connect through edges, and an edge decides what happens next based on what the last node just did.
So say, for example, the fact checker finds an error. The edge flags it and sends the task back to the writer node with the error attached, so the writer knows exactly what to fix. Only once the fact checker approves it does the edge let the work move forward.
That's the core of graph engineering.
My Take
It's not really a new discipline. It's the same orchestration that myself and other people have been doing with tools like LangGraph for over a year, with a little sprinkle on it.
The term just went viral this month. But before it, it was loop engineering. Before that, harness engineering. Before that, context engineering.
Same idea, just slight changes. And every time, someone keeps declaring the old term dead when really it just got a slight improvement.
So No, Prompting Isn't Dying in Six Months
What's actually dying is the idea that you can duct tape one model to one clever prompt and call it a finished agentic system.
Follow and I'll keep you posted.
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© Muhammad Usman
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Top comments (1)
The idea that prompting evolves rather than simply dies makes a lot of sense.