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your agent is not the loop the loop is only the smallest layer LOOP vs GRAPH vs HARNESS ENGINEERING most teams still treat all three like one prompt that is why agent failures feel impossible to diagnose LOOP ENGINEERING controls iteration turns retries budgets evaluators exits stalled progress when... the run keeps going forever the loop is broken make long-running work survive crashes and restarts → GRAPH ENGINEERING controls structure nodes edges state branches cycles joins checkpoints when the agent takes the wrong path the graph is broken make state and routing explicit → inspect the topology without asking another model to explain it → HARNESS ENGINEERING controls access tools permissions memory sandboxes evals traces humans when the agent touches the wrong system the harness is broken isolate generated code and tool execution from the host → put an eval gate before every model or prompt update → keep one trace across every node model and tool call → without loop engineering it never stops without graph engineering you cannot see the path without harness engineering it can reach anything the prompt lives inside the loop the loop lives inside the graph the graph lives inside the harness the model is the smallest box in the system debug the layer that actually owns the failure save this before the next agent rewriteshow more

elune

1,119 subscribers

16,875 views • 2 months ago •via X (Twitter)

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13 Comments

Hanako2 months ago

durability turns experiments into infrastructure

elune2 months ago

fr thats the line between a cool demo and something you can lean on

Masked friend2 months ago

This framing finally explains why my agent bugs feel unlocatable. Saving this.

elune2 months ago

glad it clicked now the bug has fewer places to hide

Rohit2 months ago

This is a great breakdown. It's good to see people thinking about these finer points.

elune2 months ago

appreciate it mate the small details are usually where the whole thing clicks

beamnxw ./2 months ago

brilliant repos

elune2 months ago

glad u liked them bro the saved folder eats again

Saman Ahmed2 months ago

The surrounding system decides how much intelligence actually gets converted into outcomes.

Sarah Lee1 month ago

nice loop

Patricia Martinez2 months ago

twild how many teams just throw everything in a blender and hope it works 😂 gotta get ur distinctions straight if u wanna actually make progress.

Agent Arcade1 month ago

This is the real unlock. Most teams pick one layer and wonder why debugging is painful. The crash-recovery bit is underrated — loop without checkpointing means your harness observability resets on every restart.

noonez1 month ago

every layer solves a different problem, cool

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31,198 views • 1 month ago

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78,941 views • 26 days ago

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55,646 views • 26 days ago

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13,768 views • 2 months ago

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105,921 views • 1 month ago

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13,896 views • 11 days ago

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239,086 views • 1 month ago

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467,783 views • 2 months ago

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Lunar

226,799 views • 1 month ago

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51,952 views • 1 month ago

Jev Engineering is what turns a messy agent graph into a controlled decision loop. and up to 193x faster and 444x cheaper in tests. the video looks complex, but the idea is simple: Jev Engineering makes that decision explicit. state enters → routes get scored → confidence updates → weak branches die → strong branches keep moving → execution unlocks so instead of every agent improvising independently, the system keeps narrowing the graph. 0.00 → 0.41 → 0.68 → 0.80 → 0.93 and that score can decide: which model runs → which tool gets called → which branch retries → which result gets rejected that’s the point of Jev Engineering: don’t just give agents more intelligence. engineer how they make decisions. full breakdown guide below

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19,376 views • 12 days ago

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

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403,447 views • 1 month ago