For home, I'm using Deepseek-v4.1-flash via both a direct subscription and OpenRouter. The price is unbeatable, and the latest versions are advancing in leaps and bounds. OpenRouter is for those times when I want access to a different model, but 90+% of the time I'm using Deepseek
For work, we have a custom setup that gives me access to just about any model from any provider.
For coding, I'm using Opencode/Openchamber. There's probably better options around nowadays, but it's working really well for me so I haven't bothered looking further. Big fan of /ponytail and /gsd skills
I'm a big user of Hermes, both at home and for work. Most of what I do with it is research, identifying pros and cons of different approaches to problems, product comparisons, proofreading my own docs before they get sent out. I've built skills that have different subagents debate the pros and cons of various options or ideas before coming to a consensus view, but with all those pros and cons spelled out - that's really handy when I have to present some complex concept to a bunch of stakeholders with conflicting views.
At home, Hermes works as a personal assistant via Telegram, doing all sorts of stuff; I've got different personas set up for managing different aspects of my life.
Probably 70% of the time I'll kick off Hermes late in the day to research or build something complex overnight, then pick it up the following morning. That alone feels like a superpower - having it research and distill a bunch of info while I sleep into a neat package I can consume at the start of each day gets my day off to a flying start
It seems inconceivable in 2026, but in the late 1960s my parents dropped me off for an unaccompanied ~10-hour train trip from Melbourne to Sydney. That trip included multiple stops at different stations along the way, plus a change of trains as we crossed the state boarder. As far as I'm aware, there was nobody on the train who was watching over me.
What are peoples' current suggestions for using Claude Code with a locally hosted LLM running on regular consumer hardware (for the sake of discussion, assume you're spending $US500-ish on a mini PC, which would get you a reasonably decent CPU, 32Gb RAM and a cheapish GPU)?
I get that it's not going to work as well as hosted/subscription services like Claude/Gemini/Codex/..., but sometimes those aren't an option
You can run something like Qwen 2.5 Coder on a regular machine (https://huggingface.co/Qwen/Qwen2.5-Coder-7B) but it's really not in the same universe with Claude Code, it will be slow and generate bad code.
It might make sense to run a small LLM locally for general conversation or very specific tasks, but they're not a serious option for agentic coding.
As someone who's been coding for several decades now (i.e. I'm old), I find the current generation of AI tools very ... freeing.
As an industry, we've been preaching the benefits of running lots of small experiments to see what works vs what doesn't, try out different approaches to implementing features, and so on. Pre-AI, lots of these ideas never got implemented because they'd take too much time for no definitive benefit.
You might spend hours thinking up cool/interesting ideas, but not have the time available to try them out.
Now, I can quickly kick off a coding agent to try out any hare-brained ideas I might come up with. The cost of doing so is very low (in terms of time and $$$), so I get to try out far more and weirder approaches than before when the costs were higher. If those ideas don't play out, fine, but I have a good enough success rate with left-field ideas to make it far more justifiable than before.
Also, it makes playing around with one-person projects a lot practical. Like most people with partner & kids, my down time is pretty precious, and tends to come in small chunks that are largely unplannable. For example, last night I spent 10 minutes waiting in a drive-through queue - that gave me about 8 minutes to kick off the next chunk of my one-person project development via my phone, review the results, then kick off the next chunk of development. Absolutely useful to me personally, whereas last year I would've simply sat there annoyed waiting to be serviced.
I know some people have an "outsourcing Lego" type mentality when it comes to AI coding - it's like buying a cool Lego kit, then watching someone else assemble it for you, removing 99% of the enjoyment in the process. I get that, but I prefer to think of it in terms of being able to achieve orders of magnitude more in the time I have available, at close to zero extra cost.
> 8 minutes to kick off the next chunk of my one-person project development via my phone, review the results, then kick off the next chunk of development.
Basically with Termius I "tunnel into" my host machine, and then I start a session with `claude` or `codex` or whatever and chat with one of those agents on my phone.
claude can deploy to github spaces and modify code for deployment to those by commits and pull requests to the repo exclusively
claude via browser and claude mobile apps function this way
but alongside that, people do make tunnels to their personal computer and setup ways to be notified on their phone, or to get the agent unstuck when it asks for a permission, from their phone
Just wanted to +1 this as a deep thinker who disagrees with the blog post's conclusion. I remember back on the years and decades I wasted dealing with the conceptual flaws inherent to nearly all software, and it breaks my heart.
90-99% of programming is a waste of time. Most apps today have less than a single spreadsheet page of actual business logic. The rest is boilerplate. Conjuring up whatever arcane runes are needed to wake a slumbering beast made of anti-patterns and groupthink.
For me, AI offers the first real computer that I've had access to in over 25 years. Because desktop computing stagnated after the 2000 Dot Bomb, and died on the table after the iPhone arrived in 2007. Where we should have symmetric multiprocessing with 1000+ cores running 100,000 times faster for the same price, we have the same mediocre quad core computer running about the same speed as its 3 GHz grandfather from the early 2000s. But AI bridges that divide by recruiting video cards that actually did increase in speed, albeit for SIMD which is generally useless for desktop computing. AI liberates me from having to mourn that travesty any longer.
I think that people have tied their identity to programming without realizing that it's mostly transcribing.
But I will never go back to manual entry (the modern equivalent of punch cards).
If anything, I can finally think deeply without it costing me everything. No longer having to give my all just to tread water as I slowly drown in technical debt and deadlines which could never be met before without sacrificing a part of my psyche in the process.
What I find fascinating is that it's truly over. I see so clearly how networks of agents are evolving now, faster than we can study, and have already passed us on nearly every metric. We only have 5-10 years now until the epiphany, the Singularity, AGI.
It's so strange to have worked so hard to win the internet lottery when that no longer matters. People will stop buying software. Their AI will deliver their deepest wish, even if that's merely basic resources to survive, that the powers that be deny us to prop up their fever dream of late-stage crony capitalism under artificial scarcity.
Everything is about to hit the fan so hard, and I am so here for it.
> 90-99% of programming is a waste of time. Most apps today have less than a single spreadsheet page of actual business logic.
I would very much like to know the kind of app you’ve seen. It’s very hard to see something like mpv, calibre, abiword, cmus,… through that lens. Even web apps like forgejo, gonic, sr.ht, don’t fit into that view.
Fair enough. I meant social network websites and social media apps like Facebook and TikTok that could have been made in a weekend using HyperCard, FileMaker, Microsoft Access, etc, if we had real reactive backends similar to Firebase, Airtable and Zapier, which come so close to almost working for normal people but miss the mark fundamentally somehow.
I know that programming has gone terribly wrong, but it's hard for me to articulate how, because it's all of it - the entire frontend web development ecosystem, mobile development languages and frameworks, steep learning curve languages like Rust that were supposed to make things easier but put the onus on the developer to get the busywork right, everything basically. It's like trying to explain screws to craftsmen only familiar with nails.
In the simplest terms, it's because corporations are driving the development of those tools and vacuuming up all profits on the backs of open sources maintainers working in their parents' basements, rather than universities working from first principles to solve hard problems and give solutions away to everyone for free for the good of society. We've moved from academia to slavery and call it progress.
> For me, AI offers the first real computer that I've had access to in over 25 years.
That's such a weird perspective. No matter your dissatisfaction with the software available, the computers we had were perfectly fine for writing whatever software you wanted to write.
Totally agree. I can spend an afternoon trying out an approach to a problem or product (usually while taking meetings and writing emails as well). If it doesn't work, then that's a useful result from my time. If it does work, I can then double-down on review, tests, quality, security, etc and make sure it's all tickety-boo.
Completely agree, there’s so many small projects I’d never been able to even start in my free time, because I’m NOT a full-stack dev and I’d rather not spend all my evenings fixing or working around all the small changes and quirks of the $currentjsframework
I think this is the other side of the same coin, and it's a really important one. When time is scarce, especially with family and a life outside work, the ability to turn tiny, fragmented moments into forward progress is huge
Exactly, it kills me to see a people a lot younger (I’m 51) pining about the good old days while the coding part of my day to day life now is using AI tools to their fullest extent.
I work in a space where I get to build and optimise AI tools for my own and my team's use pretty much daily. As such I focus mainly on AI'ing the crap out of boring & time-consuming stuff that doesn't interest any of us any more, and luckily enough there's a whole lot of low hanging fruit in that space where AI is a genuine time, cost and sanity saver.
However any activity that requires directed conscious thought and decision making where the end state isn't clearly definable up front tends to be really difficult for AI. So much of that work relies on a level of intuition and knowledge that is very hard to explain to a layman - let alone eidetic idiots like most AIs.
One example is trying to get AI to identify security IT incidents in real time and take proactive action. Skilled practitioners can fairly easily use AI to detect anomalous events in near real time, but getting AI to take the next step to work out which combinations of "anomalous" activities equate to "likely security incident" is much harder. A reasonably competent human can usually do that relatively quickly, but often can't explain how they do it.
Working out what action is appropriate once the "likely security incident" has been identified is another task that a reasonably competent human can do, but where AIs are hopeless. In most cases, a competent human is WAAAY better at identifying a reasonable way forward based on insufficient knowledge. In those cases, a good decision made quickly is preferable to a perfect decision made slowly, and humans understand this fairly intuitively.
I started coding in the 70s, loved it then, still love it now and LOVING the emergence of Gen AI tools.
For perspective, the IT industry went through a similar change with the emergence of search engines ~30 years ago. At that time, a big part of the value of a software "expert" was in their ability to remember and recall lots of info (most of it of dubious value, to be fair). These experts usually had shelves of well-thumbed books on all sorts of topics, and could recall obscure info from these books seemingly at will. With the emergence of AskJeeves, AltaVista and eventually Google, suddenly nobody needed to remember anything OR even know where to find it - with a simple search, you could get nearly all the info you needed.
I can still remember the panicked response to this brutal change from the senior IT people I worked with at the time...
Did the demand for skilled developers dry up? No
Nor did it end with
- introduction of COBOL (designed so that non-coders could write code),
- PCs (surely leading to the end of systems programming as a career),
- spreadsheets (so accountants no longer needed programmers),
- 4GLs (designed to greatly simplify coding; report writing in particular),
- Visual BASIC (so the world would no longer need C programmers; anyone could learn to write BASIC),
- Microsoft SQL Server (nobody would need mainframe databases any more, so all those mainframe jobs would disappear)
- object oriented coding (all those code reuse possibilities! Very quickly programming should devolve to just glueing together other peoples' code),
- open source (because inevitably any tool of value would soon have a competitor that was free, destroying the value proposition of companies that wrote software to sell),
- Linux (how could Windows compete with free? Shed a tear for all those soon-to-be-unemployed Windows experts)
- NoSQL (because the need for "legacy" databases like Oracle, DB2, Postgres, MySQL etc. would surely go away)
- etc., etc., etc.
The reality is that you still need a grounding in software development to do coding well, even with AIs. I'm absolutely loving how quickly I can create solid code with the assistance of Gen AI - lots of tasks that used to take me a week I can now knock over in a few hours.
I also notice how many people are struggling with how to use Gen AI tools for coding tasks - my take is there's 2 distinct skills you need: knowledge of how to do software development well, and knowledge of how to use Gen AI tools for coding. Having the first doesn't automatically lead to the 2nd - you have to put in the time to learn about Gen AI, THEN work out how to fit Gen AI tools around your current workflow, THEN work out how to optimise the way you work with your new idiot savant buddy that has perfect recall.
That whole process (new tool appears -> learn about it -> work out how to fit it into my current workflow -> optimise my workflow) has basically been my entire career in a nutshell.
People have been predicting the demise of programmers for my entire career (40+ years now), and so far they've been wrong every time. For each new disruption that appears, the key has been to embrace it and adapt how you work accordingly.
Gen AI may indeed be different and kill off all programming careers overnight, but so far I'm not seeing it
> Gen AI may indeed be different and kill off all programming careers overnight, but so far I'm not seeing it
Well, we're only ~5 years into the current hype cycle, so it's difficult to predict the long-term impact of the technology.
That said, I do think it is substantially different from the examples you mentioned.
For one, it is generally applicable. It's not an iterative or generational improvement over what came before—it is a paradigm shift in many ways: how software is produced, by whom, the quality of the product, the time, effort, and cost needed to produce it, etc.
Secondly, while it might not lead to the demise of all programming careers, and certainly not overnight, it will significantly impact the market value of traditional programming in the short-term, and, like any new technology, it will also open doors to new careers and specialization for humans. We're seeing this play out today.
But there are a few problems with this:
- Since software is turned into a commodity and the skills and resources required to produce it are much lower, there will be a flood of poorly made software, and the average quality will go down. Picture SEO scams and spam dialed up to 11, and encompassing every part of our existence, not just on the web.
- Those new careers for humans are highly specialized. All jobs will essentially involve being an assistant to the "AI", and specializing in related technologies. A "systems engineer", "frontend developer", "designer", "data analyst", etc., will all boil down to a role revolving around "AI" instead. People who don't like this type of work? Tough luck. Go sell your artisanally made programs to the niche group of people crazy enough to care about it, and good luck making a living out of it.
- Those new careers for humans are only temporary. Once "AI" gets capable enough to require less manual steering and intervention from humans, the market value for that type of work will collapse as well. The only human jobs then will be to actually create "AI". And once "AI" is self-sufficient to improve itself, we get the singularity, and then pick your favorite sci-fi scenario from there. It's debatable whether this will come to pass, and whether we're on the right track for it with the current tech, but that's certainly the goal we're aiming for.
So, yeah, I don't buy the argument that this is the same as any other tech. It's much, much, different, and it's frankly troubling that it's getting downplayed as just another step on the technological ladder. The long-term impact of this is something that should concern us all, and the worst thing we can do is to give free reign to companies to decide that future for us.
> Most authors do not support a way to pay them directly.
I think this is the problem that should be addressed.
Musicians went through a similar process in reverse order: first Napster ("piracy") then streaming services (analogous to Kindle/Amazon, where a huge 3rd party inserts themselves between content creator & consumer). Eventually some musicians twigged that they were getting screwed every way, so they set up ways for fans to pay them directly or via a less money-hungry intermediary (e.g. Bandcamp).
Not a perfect solution by any means, but if book authors feel their situation is bad enough, they could look into how musicians are dealing with it.
I'm probably not alone in thinking I'd far rather pay an author directly than Amazon or book publishers.
As with music, the final product you consume involves a lot more work/expertise/people than just “writing it“. You can see the quality differences when you compare self-published print on demand to quality publishing.
Naturally. And the editors, typesetters, designers, proof readers, etc. should get paid for their work.
It is just a question of ownership and power imbalance.
The problem with the current mainstream system (both in books and music) is that the publisher often effectively owns the work - not the author.
While I've done more than enough Powerpoint presentations telling clients what they already knew but didn't want to say out loud, there are some circumstances where bringing in a consultancy is a very good option.
Some examples:
As a software/cloud/data/AI/cyber guy (I wore a few different hats over the years...), I regularly caught up with buddies working in legal, tax, audit, retail, space travel(!!) etc. for coffee chats. It's surprising how often those of us who specialise in one domain had breakthrough moments from offhand chats with specialists in other domains. Very few people get the opportunity to have these sorts of conversations, and it's amazing how often you learn something relevant for your own work situation over a quick coffee.
When I needed expertise in one of those domains into one of my projects, I could send a message and almost always get someone on a call within a few hours. Very few organisations could get e.g. a high-ranking ex-NASA official on a call quickly to pick their brains, but I could.
Lots of times organisations don't have the deep expertise and/or available people to deliver on their internal projects. When a major rail transport provider needs to work out how to going to deal with new government critical infrastructure regulations for their IT systems, it's consultancies who can pull all the right skills together to help them out.
When there's a critical shortage of available IT skills in the marketplace, companies use consultancies to top up their workforce. Here in Australia, there were nowhere near enough GCP experts to go around for the last 4-5 years, so companies could either try to hire the very few people around at exorbitant rates, or tap a consultancy for resources.
Big 4 consultancies in particular throw high-quality training at their technical staff like nowhere else I've seen. One reason: quality training = billable hours. I had people around me burn out from too much training, and I'm pretty sure regular companies don't have that problem. For all the pointless Powerpoint presentations we did, there's a sh1tload of technical expertise sitting in Big 4 consultancies, waiting to be tapped.
Companies are always struggling with how to use the latest IT shiny tools properly. Right now it's AI - how can I use it to save costs or increase productivity? What are the ethical and legal implications that come with AI, and how can we deal with them? How can we deploy AI solutions securely? Which of our business problems are the best fit for AI solutions? How do we train our ops staff to keep these AI solutions running? - the list goes on and on.
Now a lot of people here in HN know how to do these things, but how does a regular business tap into that expertise and filter out the bullshitters? The answer is they go to a consultancy that (they feel) they can hold accountable.
On that point, sometimes execs in a company simply need someone to shield them from blame for unpopular decisions like mass layoffs. It's pretty well know that consultancies do a lot of that type of work, and they (justifiably or otherwise) cop a lot of crap over it so some exec can say "I didn't do it".
I'm probably coming across as a huge fanboy of consultancies, but remember - I'm an ex Big 4 guy. I think their influence is too large, particularly in government policy making; I've encountered way more sociopaths in Big 4 leadership roles for it to be down to chance; by any measure staff turnover and burn out is very high, and I'm convinced that's by design.
> A Sony Walkman-style device that you can give to children so they can ask questions to an LLM. It should be voice-first, and focused on explaining things. There shouldn’t be a single screen on the device. Offline-first would be a plus.
My grandkids (5 and 3) spent about 2 minutes learning how to use it, then bombarded it with "tell me a story about a unicorn named Bob", "can dogs be friends with monkeys?" and so on. In every case it gave a reasonable answer within a few seconds.
I'll be amazed if these things don't wind up embedded inside toys by Xmas. When they do, I'll be in the queue to buy one
For work, we have a custom setup that gives me access to just about any model from any provider.
For coding, I'm using Opencode/Openchamber. There's probably better options around nowadays, but it's working really well for me so I haven't bothered looking further. Big fan of /ponytail and /gsd skills
I'm a big user of Hermes, both at home and for work. Most of what I do with it is research, identifying pros and cons of different approaches to problems, product comparisons, proofreading my own docs before they get sent out. I've built skills that have different subagents debate the pros and cons of various options or ideas before coming to a consensus view, but with all those pros and cons spelled out - that's really handy when I have to present some complex concept to a bunch of stakeholders with conflicting views.
At home, Hermes works as a personal assistant via Telegram, doing all sorts of stuff; I've got different personas set up for managing different aspects of my life.
Probably 70% of the time I'll kick off Hermes late in the day to research or build something complex overnight, then pick it up the following morning. That alone feels like a superpower - having it research and distill a bunch of info while I sleep into a neat package I can consume at the start of each day gets my day off to a flying start
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