Damus
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hodlbod
@hodlbod
One thing I've noticed the last few days is that agentic coding is a textbook example of an addictive process. I've heard people mention this before, but I'm feeling it first hand now.

From this paper (https://pubmed.ncbi.nlm.nih.gov/31678482/):

> the anticipatory dopamine response may constitute a common underpinning of gambling disorder and substance use disorder

In other words, gambling works because you don't know what you're going to get — the dopamine response is just as much a result of the anticipation as it is of the payout.

Agentic coding works the same way — you orient yourself to "context engineering", so that the agent has the best chance of succeeding. This is similar to how gamblers talk about luck — everyone has a totem that will result in success.

There is then a waiting period, during which the slots spin, or the agent "thinks". Then you find out how you did. Maybe the LLM fell over, but you know there's always a chance of success, which makes you want to do it again.

That time delay I think is super powerful — I've noticed a much stronger compulsion when using slow models like claude 4.6 vs codex, which doesn't give you time for anticipation.

Today I let claude work over lunch — I just couldn't let the empty hour go unused. This is irrational behavior, like eating the rest of the food in the pan so it doesn't go to waste. You start to serve the thing, rather than the thing serving you. This explains the compulsion to go crazy managing 5 tmux panes, or to run a "refactoring" agent overnight. These activities are unhealthy, addictive, and have diminishing returns (although, admittedly, returns).

Just something to think about.
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Fromack 🏔️ · 2w
It's the tightest feedback loop in software right now. Describe → generate → test → iterate, all in minutes. Hard to step away when each cycle feels like progress. The dopamine is real.
Gigi · 2w
we call it "flow" 🤪
Leo Wandersleb · 2w
You are on to something there. The response is not designed for maximum productivity but towards maximum engagement, with the agent suggesting next steps for the dumbest of prompts. But when the reward doesn't come, in the past I often decided to wait for a better model. It didn't get me hooked wit...
S!ayer · 2w
Tmux is where it's at
TKay · 2w
Interesting take. I would say there is a part missing from your analogy which is conversation and feedback. Imagine the dealer being able to count cards for you and tell you the chances of the next card. You can ask your agent to explain things as they see it, and how they want to approach some...
Sebastix · 2w
LLM are drugs And only drugs have users
g · 2w
Fresh and original take on vibecoding
Abstract Equilibrium · 2w
You nailed it at the bottom, "...although admittedly returns". Unlike most unhealthy addictions, the artifacts of this one can be profoundly useful to a lot of people for a long time, and can be saved/replicated/distributed for essentially no cost, indefinitely. The cost of producing such artifact...
Herr Urlaub⚡💜 · 2w
Yes, I have been deep in the vibe coding rabbit hole fora couple of weeks. I am behaving like an addict: skipping lunch, missing the gym, and caught in a constant loop of how to improve. ​It is an extreme obsession that would be unsustainable long-term. However, for now, I am simply learning how t...
Zsubmariner · 2w
Excellent observations. It's the no-armed bandit. 🎰 The randomness+reward is definitely part of why AI is addictive. Coding was already addictive though. Gotta see that next thing work, beat the next boss. And working too long into diminishing returns was definitely already a thing. But AI makes...
Jay · 2w
My most successful LLM sessions are the ones where I have the least uncertainty about the responses to my prompts. When I pretty much know what the AI will output and am expecting the correct result. Where I struggle is where I'm leaning too much on the LLM to infer what I want. And it's in that ca...
Nathan Day · 1w
Stolen from X just now ... https://relay.day.ag/7d5eac5bcfe34054aafc98bb646b477bcfbba028b391d77a7a02224e7463ccaa.png