I’ve written about this approach to and it doesn’t work the issue is that even if the information is presented perfectly you don’t know how many iterations it might take.
Some information is better presented in artifacts, but some is better presented in text, f.e. abstract concepts.
You will run in the same issue even if the handover is optimized. I’m still trying to solve it for me, but perfectionizing the handover is just a part of it.
I’ve even had an ochestrator sessions to prioritize by a mix of easiness to approve/priority.
I think it’s better to focus on doing the right base line tasks instead of continious duct-taping. Clear resonsibilities, built workflows and all the good patterns that keep the amount of tasks and complexity down. The worst thing to happen is that all the agents overcomplicate your software.
I've learned that rather than juggle too much, I just accept that I'm still more productive than ever before, even if I'm "idle", it's important to take time to have a break and to recharge, refresh and reflect.
So I limit myself to at most 2 or 3 things at once, and if all of those are in long running sessions, well so be it, I know I'll be deep back in it soon.
But it's tempting to start "just one more session", especially something like getting it to better profile and improve performance. That feels super productive, but is often just to stop me feeling "idle".
My cycle with agents has become: spend several days doing detailed planning architecture documents. Codify all new plans into Jira cards as isolated features. Mass fanout on the cards whenever possible with up to 32 agents running at a time, basically becomes a question frenzy for a couple days. Stop and do testing and reviews for a week or two, I can generate up to 20 PRs per crunch day fairly reliably. Rinse and repeat. I feel lucky the type of software I'm producing is amenable to this process, some types aren't.
I like this approach. I do exactly the same: do less with more focus. I do feel more productive. Otherwise there are too many sessions open and I get distracted and lost.
I think the problem is context switching. "I can work on three different tasks at once thanks to AI" seems really empowering, but in reality, it's impossible to focus deeply on one task if your thought process is constantly interrupted every few minutes.
Every time I find myself idling in front of a screen, I feel the need to find something else to do, a distraction to fill those 54s before the agent sends a notification that needs my attention. This isn't healthy, and it's not how the human brain works.
Long, uninterrupted sessions of deep concentration are what helped humans produce their best work so far.
Why start several threads in parallel to begin with? If waiting is an issue, maybe you should break that one task into multiple steps. That would only produce more output at a lower quality. Nothing has changed about the human thinking capacity. Focus on one thing and get it done.
This feels like another software engineering truism that gets forgotten in the LLM age - if the ticket requires more than a two week sprint's worth of work (ie 8+ points), it should be broken down. Otherwise you bury so much context and tech debt while also making your reviewers deeply unhappy and cognitively depleted.
Have your LLMs treat you like you want to be treated as a code reviewer!
They're not, but the way we're filling our time while waiting for LLMs involves much more context switching than how it was with tools and human bottlenecks like manual coding. I think it's fine to work on two or three things at once, provided we don't let the LLMs decide when we should tend to which task.
I’ve tried this kind of format too but it didn’t stick for me as i was missing the rich context the sessions were able to provide for me. Specifically the lack of diagrams and other nice formatting that is possible in HTML files. I also tried linear as a broker in between for a while but it just blew up and became too tedious to navigate and ran out of sync fast. Also expensive on token overhead.
Currently what I task it to do is have one or multiple agent threads tied to a project work it and have this really token light skill laid out that leverages eleventy heavily and renders it as markdown file. Than paired with thisbit.ai (I made this and still am developing it) i just comment / voice over on all the bits from the article and have the agent take it from there again.
Also neither codex nor Claude code come even close to the lovely TUI renders of Gemini (Argon 4)
As an early adopter of AI coding, and someone who was working on Amazon's Kiro coding agent at the time, I wrote this a while back:
> AI does not feel anything. It has no existential dread, nor fear of the little death that comes at the end of every chat turn. You aren’t an AI, and you should never let yourself be treated like an AI. Give yourself space to be human. Rest, reflect, and resist the urge to match the pace of machines. You might just find that your productivity hits a new peak when you forget about productivity.
Absolutely, we need to fall back on being humans again. Read poetry/books, write, hang out with random people - the shine of AI and its ability to continuously outpace humans in any intellectual activity should not be a reason to idolize it, or even deify it. We proved ourselves, we created it - let's go back to what it means to be alive.
I’ve moved on from tmux to the apps that come with the agents at this point.
Mainly just for the overview of workstreams in flight and the ability to have a tree of tasks and subtasks (you can have a branching tree of agentic sessions) which are each their own session. These apps can remote into the tmux sessions too so it’s not even a change of workflow so much as presentation. Multimedia input/output is nice too.
Still not perfect but it’s pretty clear the dev environment of the future is going to be more and more focused on jobs management. What jobs do you have in flight? How do those jobs relate to each other? What needs your attention?
> Still not perfect but it’s pretty clear the dev environment of the future is going to be more and more focused on jobs management. What jobs do you have in flight? How do those jobs relate to each other? What needs your attention?
I liberated myself from the terminal/desktop and am now doing my stuff primarily via phone, so I can freely move around and handle stuff whatever I am. Feeling pretty fried right now because I started with 1 project, and over the session of that project 3 more got dragged in because dependency or tool issue, and they all have multiple features with multiple scenarios that I'm trying to review and unblock, ideally before auto-compact (I have a setup that kicks in after 40m of no activity) because then I have to instruct the agent to mine the previous session(s) for context and it still sometimes misses stuff and... I'm currently failing. I just let them compact now and take a break, and hope too much isn't missed when I get back at them. Definitely need to improve workflow here because it's a heck of a grind. Liberated, but not really.
My setup is similar but it is still imperfect. Keeping track of what I am working on, and where I am in the process, as MD files in the same repo as the code has been a help.
But I still find myself coming back to a terminal window, the final summary of a long run (20-90min) on display, and asking the agent "where are we? what is next?"
And I still get the burnout feeling after dumping, reloading, dumping, reloading context for the 3 agents I have running simultaneously. That leads me to sometimes avoid the 4 or 5 open PRs, each with 20+ file changes I have to review, the stacked result of the last feature I asked the agent to start before I went out for a walk, or to eat lunch, or to sleep.
Starting loops is so easy now, so low friction. But closing things out, that last 20%, is still a slog. And I have a lot more of it now that agents can generate so much.
I find it's useful to just ask Claude to help me. At least once a day, I tell Claude, "I've lost track of what's going on. Figure out what needs my attention right now and what should I focus on next." It almost always gets me back on track.
It's interesting watching everyone build their solutions to this new world of problems. Mine has been to double down on my markdown notes, extending https://app.etherpk.com so that every task (plain markdown) can be viewed under it's wikilink (or several) on a kanban board. An MCP server knows how to interact with the notes graph. I copy a reference to the task, hand it to an agent, and the agent works with blocks under the task from there. It basically means I can give the agent really rich context up front - images, excalidraw drawings etc and the agent can update the task as it goes. Having everything on a kanban board makes it easier to step away from a task to work on whichever really needs my attention and come back. Putting this together with herdr has been very productive. I still have to watch the brain fry, but it is helping. Don't know if I'm selling the idea but I feel like I'm on to something after experimenting with various systems similar to what the author is suggesting. I'm working on making a product of it. The onboarding needs some streamlining but it's available to use for free for local graphs.
Why inventing your own issue/work tracking system based on git? Wouldn't it be easier to work with, say, github issues the same way? You create it normally, agent picks up, works, updates the status on it or in the relevant wip PR, then potentially adding "needs more info" label. You'd get all the same tracking benefits and more: better UI, kanban, more tools.
I "accidentally" invented my own tracking system that lives in an org file because I've been using org-mode for project write-ups for years. It was only natural to provide tools for agents to access it all when the AI-centric workflow became a thing.
Didn’t invent it. Using open source solution board.md. The benefit of having the board in the repo next to the source code is in giving your agents convenient access to both business and tech contexts in one place.
I’ve seen so many teams having jira living one life that has nothing to do with real codebase.
So instead of tabs, I do cmux’s named tab groups. From there I rank them in my sidebar by priority and makes sure I’m always staying on top of the top prio tab group. The others I’ll only navigate to when I’m free.
I can usually have 3-4 tab groups running at one time. More than that I find to be counter productive
This is a temporary problem. A 10x-100x speedup will allow us to simply wait for the response, instead of finding something else to do in the meantime.
I wonder what the experience is of people here with the ultrafast mode (8x) of Codex.
I've tried to find a combination of a good-enough model, a VERY fast provider, and cheap enough serving to make this all doable. DeepSeek itself is quite fast, but I crave even more speed (and ideally something hosted outside of China).
Fireworks and Baseten seem to be the leading providers that are available to a solo dev like myself, and support any reasonably decent modern models (DeekSeek 4.x, GLM 5.x, etc). Fireworks has been a real dud, but Baseten in FAST mode has been absolutely amazing. Not cheap - but I find it substantially cheaper than Terra / Sol (low), etc. I haven't found Haiku to be smart enough to be useful.
DeepSeek (the provider) and beyond seem to hit the sweet spot to keep me mostly in-context, so I don't need 4 parallel work items to feel productive. So roughly 200tps or greater. Vanilla Baseten is ~400 tps, and FAST is 700-800 avg.
Price wise, Deepseek hosting is extremely cheap, Baseten is a step up - maybe 5x or more, and FAST mode is well beyond that. But I still find myself dual wielding Deepseek and Baseten FAST when I need the speed.
The other benefit: for my own work in very limited hours, I'm more than happy to pay for answers to come back faster.
Unless we get some kind of very different architecture I’m not sure we’re going to get a 10-100x improvement any time soon, api models will always preference throughput over individual task latency, so any improvement that sacrifices serial decode for better parallelism is going to be more economically viable.
Pretty expensive nowadays, but it’s hard to think that prices won’t come down eventually. AI is being used everywhere, so I’d expect hardware investment to grow exponentially, including in the custom chips that power ultrafast models. To me it feels like we are in the "telephones are for the rich" era of AI history.
I kind of enjoy the juggling between multiple tasks.
But the inherent goal is to reduce the human-interaction within a session. Telling the agent to make assumptions rather than asking and reduce any bump causing me to step in, making sure it does not happen again in another session. Soon you'll see you can juggle more balls but at a frequency which doesn't fry your brain.
Also, I don't read most of the verbose output anyway. I have configured the agent to visually highlight actionables or destructive actions.
My current issue is not brain RAM but MacBook RAM, so I'll need more metal. Anyone got experience with Tailscale with agents?
Claude Desktop should build this as an interface. It recently gained a lot of useful features that makes managing sessions and working on multiple things very easy. Only thing missing is the inbox now. A central place for summary of everything you are actively working on and what agents need from you.
Yes. Major labs will ship a good UX solution I believe when folks like us experiment enough so they can see where the public edge of the consensus leans towards.
Just like Hermes and OpenClaw are becoming replaced.
Setting a conversation title that you can see in the bar across the top and where you send the message, now you know what is each one... without that all of them are a square-ish box with letters
I also have this problem, started on a similar solution. Mine is a visual board with cards and discussion threads. Cards have context at an abstraction level I deal with (I don't review code) and agents ask me questions below it. Tooling is very early, very rough but I am feeling more productive than juggling 2-5 sessions.
Its funny that there isnt a word yet to describe these moments where one waits for the agent to finish its work, something which has taken over our whole work experience nowadays
I actually was thinking about this phenomena. I’m not a native speaker and feel that in English overtime I tend to pick up Clauds “speaking style” as that’s what I “speak” most English to.
Doesn’t happen with my mother tongue though
This is the second post on HN today where someone gave this reason for using Claude to write/draft a blog post.
In my opinion, a post that obviously reads as non-native English is going to be more readable than something that can be detected as Claude output these days, unless maybe the former is filled with mistakes. I would imagine native speakers have a higher chance to detect Claudisms than someone less familiar with the language.
This is such a short blog post. You read this line (an entire paragraph by itself) and thought "good job Claude, you really captured what I was trying to say here"?
The author's problem is that the are doing too many parallel agent things. It's very interesting that their solution space is "keep doing tons of parallel stuff, but with different tooling" instead of... "do less parallel stuff (and provide stronger attention)".
My perspective was that it seems like your problem is that you're exhausted from doing too much. This led you to a technical solution where you shuffle the order of things, but are still doing too much. Your result, as stated in the post: "I'm still exhausted". So is your solution actually solving your problem?
At some point, you will write your own holster and introduce User-Authority as an agent with a self-improvement gate. I refuse to stare into an abyss of my own creation.
With agentic development, we're saying every software developer is now managing a team (of agents). We already kinda know how to do that. Issue trackers, stand ups, design documents. I'm using GitHub issues to manage the queue and it works ok. I don't need to know all of the context for every task, so maybe an aggregated "stand up" would be better.
I still do LeetCode problems occasionally. It feels weird to write code and work through complex logic manually again, but I think it's more crucial than ever these days. It's like physical exercise. If you don't use your brain and keep challenging yourself, your problem-solving skills will eventually atrophy.
When I read things like this I have a mixed feeling of not knowing wether I’m sad cause I’d like to have time to do leetcode too, or wether I’m simply too anxious to let the productivity improvement spiral go and chill a bit.
People exercise for sport because we've automated away much of manual labour, so if you don't exercise, you look and feel like a string bean or a watermelon.
The AI age is trying to automate away our thinking, which runs the risk of making our brains look and feel like the same way as our bodies if we don't actively try to work them.
In the case of exercise, the majority of people don't pursue it in a somewhat post-labour era. I'm certain we'll see even less mental exercise in a post-thinking era. And it's deeply unsettling to think about how that will play out if we don't wake up and put a bit more mandatory/intentional thinking into the way we live with AI.
You use your brain for things like problem solving literally everywhere and there are myriad of possible high intensity brain exercises from video games to meeting new people.
The only thing that will 100% atrophy when not coding is coding skill.
I agree that coding problems are not particularly necessary for preventing atrophy, but it would be going to far to say that people are merely panicking.
I think maybe we're conflating strictly cognitive facilities, facilities that can be maintained through all sorts of means, with intellectual skills and habits that really are in danger of atrophy when we rely too much on AI.
> A lot of people are suggesting taking breaks, thinking before typing
While I think these are actually some of the best suggestions they really do require a massive overhaul of our work culture. The technology field has put speed ahead of all else, including profits. We've frequently shown that we're penny wise but pound foolish. The industry is overrun with FOMO.
I think so much of this is because everything is hype driven, from the core. To even get funding we have to promise hopes and dreams. While that started out reasonable it has escalated into selling promises that are obtuse at face value. Things that are more fantasy than Sci-Fi, or things that while they're even possible they're wildly impracticable simply due to the laws of physics (data centers in space?). Hell, people even propose things that would violate tons of international treaties AND have little to no practical value[0].
AI isn't the cause of any of this, but it is a catalyst. We need to have serious discussions about this now before the snake eats itself[1]. I don't know why we pretend that these things aren't foreseeable. Many of them are widely discussed long before they come to fruition. But I do also believe that this lust for speed forces blinders onto many. They don't have time nor energy to think creatively[2] or they fool themselves. AI increased speed, but that doesn't mean it increased velocity. That velocity still comes down to the engineers using this tool[3].
This new tool has forced us to come face to face with one of our oldest and greatest enemies: understanding. And I do mean old, Dijkstra wrote about it long ago[4].
We still can do great things in this age, but we're forced to take a step back and look at what has actually driven progress in the past. And if anyone claims to have a clear fool proof formula, well... that's just magic.
[0] Yes, giant mirrors in space are, in fact, space weapons. If you couldn't figure that out on your own you have some serious reflecting (pun intended) about your career choice as an engineer https://www.reflectorbital.com/
[1] At least fully. Google's latest earning reports already show that. And it isn't like years ago people called out Google's plan for AI search and how it would affect ad revenue. That discussion even started long before Gemini!
[2] Something that drives innovations and consequently, profits!
[3] It is still a tool. It is not magic. It never has been and it never will. Maybe you don't call it magic. Maybe you give it a "technical explanation" and conclude that it isn't. But actions speak louder than words and it isn't hard to see that people have treated code like magic since day one, it shouldn't be surprising that it's become more prolific with AI.
> It is still exhausting. But I don't feel distracted or lost.
So not really solving the issue, just feeling productive for the hell of it. To me, this sounds like those X posts of some techbros LARPing with multiple screen setups where agents are running wild and generating summaries of stuff and are stacked over each other etc, all in the hope of optimizing something (no one knows what exactly).
Just have decent workflow across agents and you won't have to reinvent JIRA hell.
Some problems are not solved in one go, but we rather iterate on them. I shared here my latest iteration.
It definitely improved my ability to focus. I still feel tired after a working session but by the moment it’s over I know I closed more tasks, have less half open tasks hanging and have a better overview of what’s going on.
And I need to keep iterating on this process improvement.
Perhaps a radical suggestion but you could also just write the code and use LLMs to check for errors, different patterns that might be better (I.e parse don’t validate). They don’t necessarily have to be code generation tools if you feel that it’s not better to do so. This will probably fall of deaf ears but personally I like doing it this way.
You could also use LLMs to help you understand things, rather than doing them for you and hoping you don't need to understand anything, which is typically a bad strategy.
LLMs can be pretty great to help you learn. You do have to watch out for when they're teaching you something wrong, especially if it's something like history, where it could just be making things up completely and it's harder to tell than with pure logic like computer science.
Agreed! I’ve been able to walk up to codebases and have them help explain parts that I would’ve had to gdb though previously.
I suppose my grand parent comment is unpopular but I really do think understanding is paramount in software that’s critical. LLMs are tools, use them to help not hurt :)
Some information is better presented in artifacts, but some is better presented in text, f.e. abstract concepts.
You will run in the same issue even if the handover is optimized. I’m still trying to solve it for me, but perfectionizing the handover is just a part of it.
I’ve even had an ochestrator sessions to prioritize by a mix of easiness to approve/priority.
I think it’s better to focus on doing the right base line tasks instead of continious duct-taping. Clear resonsibilities, built workflows and all the good patterns that keep the amount of tasks and complexity down. The worst thing to happen is that all the agents overcomplicate your software.
So I limit myself to at most 2 or 3 things at once, and if all of those are in long running sessions, well so be it, I know I'll be deep back in it soon.
But it's tempting to start "just one more session", especially something like getting it to better profile and improve performance. That feels super productive, but is often just to stop me feeling "idle".
Every time I find myself idling in front of a screen, I feel the need to find something else to do, a distraction to fill those 54s before the agent sends a notification that needs my attention. This isn't healthy, and it's not how the human brain works.
Long, uninterrupted sessions of deep concentration are what helped humans produce their best work so far.
Have your LLMs treat you like you want to be treated as a code reviewer!
Even pre-AI I would work in parallel while I waited for tests to finish, or deploy to go out or whatever.
Currently what I task it to do is have one or multiple agent threads tied to a project work it and have this really token light skill laid out that leverages eleventy heavily and renders it as markdown file. Than paired with thisbit.ai (I made this and still am developing it) i just comment / voice over on all the bits from the article and have the agent take it from there again.
Also neither codex nor Claude code come even close to the lovely TUI renders of Gemini (Argon 4)
I need to take a look at what Google ships. Not enough time to follow all new products. Feeling the singularity unfolding
> AI does not feel anything. It has no existential dread, nor fear of the little death that comes at the end of every chat turn. You aren’t an AI, and you should never let yourself be treated like an AI. Give yourself space to be human. Rest, reflect, and resist the urge to match the pace of machines. You might just find that your productivity hits a new peak when you forget about productivity.
Mainly just for the overview of workstreams in flight and the ability to have a tree of tasks and subtasks (you can have a branching tree of agentic sessions) which are each their own session. These apps can remote into the tmux sessions too so it’s not even a change of workflow so much as presentation. Multimedia input/output is nice too.
Still not perfect but it’s pretty clear the dev environment of the future is going to be more and more focused on jobs management. What jobs do you have in flight? How do those jobs relate to each other? What needs your attention?
Sounds like a job for an agent...
But I still find myself coming back to a terminal window, the final summary of a long run (20-90min) on display, and asking the agent "where are we? what is next?"
And I still get the burnout feeling after dumping, reloading, dumping, reloading context for the 3 agents I have running simultaneously. That leads me to sometimes avoid the 4 or 5 open PRs, each with 20+ file changes I have to review, the stacked result of the last feature I asked the agent to start before I went out for a walk, or to eat lunch, or to sleep.
Starting loops is so easy now, so low friction. But closing things out, that last 20%, is still a slog. And I have a lot more of it now that agents can generate so much.
I’ve seen so many teams having jira living one life that has nothing to do with real codebase.
I can usually have 3-4 tab groups running at one time. More than that I find to be counter productive
I wonder what the experience is of people here with the ultrafast mode (8x) of Codex.
I've tried to find a combination of a good-enough model, a VERY fast provider, and cheap enough serving to make this all doable. DeepSeek itself is quite fast, but I crave even more speed (and ideally something hosted outside of China).
Fireworks and Baseten seem to be the leading providers that are available to a solo dev like myself, and support any reasonably decent modern models (DeekSeek 4.x, GLM 5.x, etc). Fireworks has been a real dud, but Baseten in FAST mode has been absolutely amazing. Not cheap - but I find it substantially cheaper than Terra / Sol (low), etc. I haven't found Haiku to be smart enough to be useful.
DeepSeek (the provider) and beyond seem to hit the sweet spot to keep me mostly in-context, so I don't need 4 parallel work items to feel productive. So roughly 200tps or greater. Vanilla Baseten is ~400 tps, and FAST is 700-800 avg.
Price wise, Deepseek hosting is extremely cheap, Baseten is a step up - maybe 5x or more, and FAST mode is well beyond that. But I still find myself dual wielding Deepseek and Baseten FAST when I need the speed.
The other benefit: for my own work in very limited hours, I'm more than happy to pay for answers to come back faster.
But the inherent goal is to reduce the human-interaction within a session. Telling the agent to make assumptions rather than asking and reduce any bump causing me to step in, making sure it does not happen again in another session. Soon you'll see you can juggle more balls but at a frequency which doesn't fry your brain.
Also, I don't read most of the verbose output anyway. I have configured the agent to visually highlight actionables or destructive actions.
My current issue is not brain RAM but MacBook RAM, so I'll need more metal. Anyone got experience with Tailscale with agents?
Just like Hermes and OpenClaw are becoming replaced.
https://github.com/alainnothere/privibe
https://web.archive.org/web/20261108193851/https://sergeykuh...
Maybe vibe-idling? Videling? Vibeling?
This is the second post on HN today where someone gave this reason for using Claude to write/draft a blog post.
In my opinion, a post that obviously reads as non-native English is going to be more readable than something that can be detected as Claude output these days, unless maybe the former is filled with mistakes. I would imagine native speakers have a higher chance to detect Claudisms than someone less familiar with the language.
This is such a short blog post. You read this line (an entire paragraph by itself) and thought "good job Claude, you really captured what I was trying to say here"?
Not sure why people hate so much AI generated text if it makes sense.
I hope the irony is not lost on anyone else, lol
AI generates texts for articles just fine.
I’m not writing literature here.
I’m trying to communicate a thought. The thought was captured well.
If you can see it was captured with Claude - who cares, as long as it says what I want.
I joke. I know you care. It’s just that I don’t.
Come to think of it, it is indeed still 2005 outside
I still do LeetCode problems occasionally. It feels weird to write code and work through complex logic manually again, but I think it's more crucial than ever these days. It's like physical exercise. If you don't use your brain and keep challenging yourself, your problem-solving skills will eventually atrophy.
The AI age is trying to automate away our thinking, which runs the risk of making our brains look and feel like the same way as our bodies if we don't actively try to work them.
In the case of exercise, the majority of people don't pursue it in a somewhat post-labour era. I'm certain we'll see even less mental exercise in a post-thinking era. And it's deeply unsettling to think about how that will play out if we don't wake up and put a bit more mandatory/intentional thinking into the way we live with AI.
The only thing that will 100% atrophy when not coding is coding skill.
panic about “ai brain fry” is overblown
I think maybe we're conflating strictly cognitive facilities, facilities that can be maintained through all sorts of means, with intellectual skills and habits that really are in danger of atrophy when we rely too much on AI.
I think so much of this is because everything is hype driven, from the core. To even get funding we have to promise hopes and dreams. While that started out reasonable it has escalated into selling promises that are obtuse at face value. Things that are more fantasy than Sci-Fi, or things that while they're even possible they're wildly impracticable simply due to the laws of physics (data centers in space?). Hell, people even propose things that would violate tons of international treaties AND have little to no practical value[0].
AI isn't the cause of any of this, but it is a catalyst. We need to have serious discussions about this now before the snake eats itself[1]. I don't know why we pretend that these things aren't foreseeable. Many of them are widely discussed long before they come to fruition. But I do also believe that this lust for speed forces blinders onto many. They don't have time nor energy to think creatively[2] or they fool themselves. AI increased speed, but that doesn't mean it increased velocity. That velocity still comes down to the engineers using this tool[3].
This new tool has forced us to come face to face with one of our oldest and greatest enemies: understanding. And I do mean old, Dijkstra wrote about it long ago[4].
We still can do great things in this age, but we're forced to take a step back and look at what has actually driven progress in the past. And if anyone claims to have a clear fool proof formula, well... that's just magic.
[0] Yes, giant mirrors in space are, in fact, space weapons. If you couldn't figure that out on your own you have some serious reflecting (pun intended) about your career choice as an engineer https://www.reflectorbital.com/
[1] At least fully. Google's latest earning reports already show that. And it isn't like years ago people called out Google's plan for AI search and how it would affect ad revenue. That discussion even started long before Gemini!
[2] Something that drives innovations and consequently, profits!
[3] It is still a tool. It is not magic. It never has been and it never will. Maybe you don't call it magic. Maybe you give it a "technical explanation" and conclude that it isn't. But actions speak louder than words and it isn't hard to see that people have treated code like magic since day one, it shouldn't be surprising that it's become more prolific with AI.
[4] https://www.cs.utexas.edu/~EWD/transcriptions/EWD02xx/EWD288...
So not really solving the issue, just feeling productive for the hell of it. To me, this sounds like those X posts of some techbros LARPing with multiple screen setups where agents are running wild and generating summaries of stuff and are stacked over each other etc, all in the hope of optimizing something (no one knows what exactly).
Just have decent workflow across agents and you won't have to reinvent JIRA hell.
It definitely improved my ability to focus. I still feel tired after a working session but by the moment it’s over I know I closed more tasks, have less half open tasks hanging and have a better overview of what’s going on.
And I need to keep iterating on this process improvement.
Indeed it is far from solved.
LLMs can be pretty great to help you learn. You do have to watch out for when they're teaching you something wrong, especially if it's something like history, where it could just be making things up completely and it's harder to tell than with pure logic like computer science.
I suppose my grand parent comment is unpopular but I really do think understanding is paramount in software that’s critical. LLMs are tools, use them to help not hurt :)