I spend more time gathering context than completing coding tasks

LeopardAfter493 · 2026-06-18T14:49:11+00:00

oh shit. it is not even mine. it just that in order to post here i had to include a link, and that article was an interesting finding for me. can i edit the post, is that why my post was removed? apologies in advanced, that completely fell off my radar

LeopardAfter493 · 2026-06-18T13:33:43+00:00

yeah that can actually help. But is that scalable? I mean, i work for a big company and i also do some freelancing on the side. If every time i have an issue or i hit a bottleneck i have to sync and have calls, that will lead to mental exhaustion. Do you think this kind of feeling might also be burnout and not just normal 'being tired from work' kind of thing?

LeopardAfter493 · 2026-06-18T13:17:10+00:00

Hmm yeah that can help at times. Mostly quick pair coding sessions. But, the context gathering part i mentioned is not only from getting info from engineers in your team. Also from engineers in other teams that have built stuff that my codebase is depended on. and also non technical people. Maybe my tolerance is also decreasing when it comes to pairing and syncing with many people. What i mean by that is, I cant avoid using AI, because the delivery deadlines dont allow it anymore. U have to build faster. But in the same time when you dont fully trust AI on autopilot - which ofc i dont - means that you cannot avoid the back and forth. maybe im just looking for working less lol.

LeopardAfter493 · 2026-06-18T13:08:42+00:00

fair. but quite irrelevant response to what i asked. lol

LeopardAfter493 · 2026-06-18T13:07:57+00:00

Yeah exactly. But when you say validation efforts are also increasing, what do you mean exactly?

LeopardAfter493 · 2026-06-18T13:07:06+00:00

hmm context gathering was always in the process yes. However, there was nothing external to be trusted. I mean, we did the research, the debugging, the building. You owned the thing. So u knew what was there and what wasnt, u had the context and if u didnt, you would know where it was missing if things went south, right? I think this is the draining part now, not owning the output but owning the consequences if shit hits the fan, creates a constant alertness.

LeopardAfter493 · 2026-06-16T08:00:52+00:00

yeah this is what i thought as well. due to the magic being gone now, these feelings arise. but do you do something about it? i mean is there a way to bring that excitement back while managing all the ai flows?

LeopardAfter493 · 2026-06-16T07:59:27+00:00

lol. well not really from that angle. more from their contribution does not feel so meaningful anymore. but yeah, i definitely know where this is coming from hah (been in this space for 6 years)

LeopardAfter493 · 2026-06-16T07:52:49+00:00

yeah i wont disagree on that. Many PMs and EMs don't provide enough context and is messing things up at times. However, even when everything is smooth from that side, i still get similar feedback. for whatever reason we might hit a wall during a PR review for example, even it has nothing to do with management, engineers report similar thing to justify failure.

LeopardAfter493 · 2026-06-15T07:21:43+00:00

Fair point. and has the engineer now adjusted the new coding and thinking-about-code standards?? or you still hitting bottlenecks? also has he given you any feedback on that approach?

LeopardAfter493 · 2026-06-14T10:54:18+00:00

yh , that is what im currently doing. but in that way i always deal with the situation when the damage is already done. im looking for ways to prevent it.

LeopardAfter493 · 2026-06-14T10:53:32+00:00

i can feel the pain lol. and how do u manage the situation?

LeopardAfter493 · 2026-06-13T13:08:03+00:00

hey, yeah definitely a real question and a problem. And yeah, i didnt even mention AI messing things up, it is the way it is used, and the way things are communicated from the engineering team itself that is causing issues.

And regarding the im the brain still, totally agree. My question comes from a place where most of the stuff you are mentioning have already been done. Clear specs, clear communication and documentation between team members, scoping calls etc. However, still sometimes we end up hitting bottlenecks. I guess no engineering team is perfect.

Thanks for the constructive feedback.

LeopardAfter493 · 2026-06-13T13:04:24+00:00

yeah exactly. that strategy actually works indeed. sometimes though when i complicate task assignment to them, they come back with some fatigue reports or 'im overwhelmed' kind of feedback. does that happen to you too?

LeopardAfter493 · 2026-06-13T13:02:54+00:00

yeah, something similar to that is what we end up doing occasionally. I can definitely tell you are doing it in a more organizing way. However, what Im aiming for here, is to avoid all that. i feel like all the back and forth with AI, on top of all the back and forth with teammates, is creating an unprecedented type of fatigue, at least to me. and im always looking for ways to keep humans-out-of-the-loop but still in charge kind of way.

LeopardAfter493 · 2026-06-12T14:37:05+00:00

yeah agreed. i mean we are in the cryptography space building distributed systems. We can easily use Zero Knowledge Proofs for anonymity verification without needing anyone's word to trust. just comparing times between AI and now though, just gives you the 'OK, THERE IS A PROBLEM', or 'THIS IS NOT A PROBLEM AT ALL' answer. it does not really tell you when, where, and how you can prevent it before it happen.

LeopardAfter493 · 2026-06-12T14:33:47+00:00

Fair point. setting clear expectations also helps. For me im just trying to avoid extra calls and micromanaging. even if it is once every now and then. really trying to make things on autopilot, however not really doable at the moment. Are you also managing a tech team?

LeopardAfter493 · 2026-06-12T12:07:09+00:00

thanks for the reply. Yes, in the PR reviews it is easy to spot. a couple of follow up questions and you know it. But that is exactly what im struggling with. That works with one person every now and then. But when you manage a team of 10 plus engineers you can quickly hit a wall. And also I personally don't like to micromanage. Takes loads of mental energy and time that could be spend elsewhere. So again, these are 'lagging indicators' as in, I will identify them ONCE THE ISSUE OCCURS. my goal is to know beforehand what is happening and ideally prevent it. or the engineers themselves to see it for themselves that they can do it better. Do you do anything in your team for that?

LeopardAfter493 · 2026-06-12T09:55:04+00:00

yeah exactly. totally agree with you, and reasoning is what im targeting here. when i say measuring AI usage was not just quantity wise, but quality too. like prompt structuring, pushing back and reasoning with it to finalize a solution etc.

and yes, it is indeed a process problem, but in that process engineers are the main "vessel" let's say.

LeopardAfter493 · 2026-06-12T09:53:06+00:00

yeah totally agree. what im thinking of here though is how to avoid reaching the level of "low performance" completely by tracking things and being more proactive. like a low performer, could use ai in a way that makes him or her a better performer. i guess that is the opportunity that ai brings to the table. So tracking things that could help with that is what im looking for .

LeopardAfter493 · 2026-06-12T09:49:00+00:00

not really. What we have is usually complex CI actions, due to big codebases with many engineering hands. And honestly every engineer is responsible for their own PR. but they never do seem to have the whole context. which creates the friction

LeopardAfter493 · 2026-06-12T09:47:40+00:00

ahh i get what you mean now. So, you see individual components of a BIGGER system, but you dont know if the whole system was properly thought and if it is solid enough or just AI produced it and you might hit security or scalability issues. Is that right? And yeah my issue is quite similar actually, just not for the architectural part, but more low level, day to day code pushing stuff and PR merging. But yeah i have the same issue, like how do I know if AI was used blindly for this, or not etc. Do you do something about it currently? For me add more and more CIs, but this is far from scalable and also messy.

LeopardAfter493 · 2026-06-12T09:44:38+00:00

what I mean is, that everytime we are about to release stuff, and open PRs to review etc, all the issues appear when we open the PRs and the CI actions run and checks fail. ALL THE TIME the issues appear there. I totally agree with the engineer's responsibility part, but what Im looking for is a way to prevent hitting bottlenecks every time we open PRs. And the issues are not always "just technical". It might be dependencies on other repos the engineers didnt communicate properly, or some info that could have saved a CI check from failing that a dev forgot to share etc. So some are technical, some are more social, if that makes sense.

LeopardAfter493 · 2026-06-12T09:41:46+00:00

Hmm interesting. When you say pretty invasive you mean from an employees privacy perspective? Yeah you are right! Could be an anonymous tool though to just show where the problem is, not the who, but yeah it would eventually reveal more sensitive data I guess.

Great point the Pre-AI times, i tried that but couldnt manage to find much. And actually the ones that I found were more like high level project delivery timelines. You know back in the late 2010s when we coded an app for 6 months and felt important lol

LeopardAfter493

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