rasiim kyan bey

the internal software quality of a code base correlates to the level of emotional intelligence shared among stakeholders. EQ leads to ISQ

@sigfualt nope. and the streets saying they bout to pull the switcheroo on us with pricing. soon as enough of us are hooked lol

@refactorfiend Yeah I am already looking to limit the cost of ai tokens are not cheap like they use to be

i care about - how much this agent can do. i care more about - how much can i afford to not know about what this agent is doing. and for how long.

@sigfualt 😂 some we feed food and the others we feed tokens

@refactorfiend Yeah I am getting that vibe. I have the kids I live and robot kids now.

@TheJobfather__ same thing i be sayin

Corporate life is realizing the job requires more emotional regulation than technical skill.

the internal software quality of a code base correlates to the level of emotional intelligence shared among stakeholders. EQ leads to ISQ

@kerckhove_ts scratch tdd-ing and refactoring for me

I keep hearing that developers write code too early in the whole "getting things done" process but my experience says the exact opposite. The only real way I've found to figure out requirements IS to start writing code and see what I bump into.

@sigfualt thats good material... yea not long indeed. from what i can see day to day, t seems like we'll be in this micromanaging relationship for a lil while with the robot.

@refactorfiend Not long it seems, I am about to read a white paper on this topic later today.

sitting on a 2-hours long chunk of edits im making. i was lazy to microcommit. and now i need to rollback cus the thing i didnt tell the agent to do was an unknown unknown. and im slightly pissed at myself for not taking making savepoints. lesson reinforced

Failure is the frame, not the picture.

@tlark8 heck yea. the intuition the knowing what's a feature vs a bug vs bughancement. that type of stuff. will save a lot of expensive churning time

@refactorfiend I’ve found AI to excel at greenfield and underperform on brownfield. I’m sure they’ll fix that in the future, but being a domain expert on code/systems is still valuable

the ai is great at coding for the most part. also at looking right and being like 5.428% ...off... just enough to be not right lol. is knowing that 5% like 100% of our value now?

@deirradecoded no limit to the madness smh

It’s getting weird…er 😭

@explorersofai weee as we slide down the human slippery comfort ease hedonism slope (not to be pessimistic or nothin ). i think we'll make it work when it's all said and done tho. right?

@explorersofai i 1000% see the difference and i feel you. most of us will rush to choose the path of least (shortest term and most visible) resistance

I finally realized that a lot of people are not using their brains to think anymore. The reason is AI. Problems that were easy to solve are now being passed on to AI. Super complicated workflows are being created for no logical reason. What was free and effective before now costs at least 1M tokens. Oh well.

@dexhorthy this feels like it should be a bug ticket that should be submitted to anthropic. or maybe it has and will be addressed two minutes from now in their next update

we've been trying a bunch of stuff. this one kinda works.

agentic development - managing a workforce with 10x DeV sPeEd, zero institutional memory, and no shame about being wrong

@tomfgoodwin start with one. then when it starts doing too much, add another

I’m surely being stupid. But if AI is rather unconstrained by expertise or capacity or to some extent speed Why do we need to divide tasks or departments to 9 agents ( the marketing agent, the optimization agent etc ) to each do one thing. And then another agent to manage the swarm. Cant one agent just be doing it all you know. It seems very skeuomorphic. Will we have HR agents to make sure the agent agents are being looked after ? A office canteen manager agent to feed the agents ? Seems daft

@SergioRocks x.com/refactorfiend/…

Sam Altman is right about one thing: - Writing software used to be harder. But there’s an assumption hidden in that statement: - That because it’s easier now, engineers matter less. It’s actually the opposite. AI made it easier to write code. It did not make it easier to build robust software systems. If anything, it made it easier to build fragile ones. Today you can generate: - API integrations - User interfaces - Backend data flows - Entire features In hours. But what happens when: - The same request is processed twice - Data arrives incomplete or out of order - A dependency fails halfway through - Real users behave in unexpected ways That’s where software breaks. It's not about the code. It's about how the system is architected. And that’s where engineering experience shows up. Understanding failure modes. Designing for edge cases. Building systems that don’t collapse under real usage. AI didn’t remove the need for engineers. It removed the barrier to writing code. Which means more systems will be built. And more of them will need to be designed properly. The engineers who can do that are not less important. They are more critical than ever.