Syntaf

You’re making a straw man argument out of the nature of what jobs are for, of course they are to help a company make a profit.

I don’t think the CC’s teams have hidden motives to optimize for token inefficiency as the OP I replied to implies.

A reality where a secret cabal of CC engineers are trying to find the most token inefficient ways to build the best harness on the market sounds quite interesting to me, but not realistic.

I don’t feel like reality is so interesting that CC devs are sitting in a room theorizing how to extract the most profit from their users.

I’m much more inclined to believe they just don’t _care_ about cost, and profit is an ancillary benefit to their functionality above all else.

Just recently they released auto idle-compaction for large sessions about to miss the cache window. If they were so profit driven I can’t imagine they’d have built this to begin with, that’s free tokens from your perspective.

> they care about a product that works reliably.

I actually disagree here, what matters most is procurement & distribution. You can sell absolute dog water software (see: Teams[1]) and capture a market with the right procurement and distributions pipelines.

The sad reality IMO is that the quality of software matters much less than we (the engineers) would hope it does.

[1] https://web.archive.org/web/20260322032609/https://www.theve...

I heard some chatter about Warp some six months ago and decided to give it a try. Blew my mind that a terminal with an LLM wrapper side-panel raised $80M

I'm sure there's some impressive stuff in there that the warp team built but also the second my own _terminal_ tried to get me to subscribe to a monthly plan I uninstalled that shit so fast.

+1 to a lot of what you said here, especially this:

> I used to tell myself that plan mode mitigated that, but I usually ended up mentally glossing over the generated plans anyway.

At a certain point I realized I far preferred delegating the first implementation pass to agents and reviewing the _code_ instead of a plan up front. If you had asked me this question ~2 years ago I'd think anyone would be insane to hand off discretion like this, but frontier models are just so _good_ nowadays.

Let's say you launch 10 working sessions in a day, would you rather:

* Review 10 plans, and _then_ review 10 PRs, and _then_ maybe adjust the approach on 1-2 and merge the other 8

* Review 10 PRs, and maybe adjust the approach on maybe 4 and merge the other 6

The first option just feels like needless attention for the sake of feeling in control; but the reality is that these models are becoming just as good if not better as us humans and our reckoning is here. Our codebase has enough linters, hooks, and guards such that generally the agent just follows our blessed patterns already, so what is plan mode actually doing beyond giving me a false sense of security? I'm still going to read the code anyways.

Yeah if anything Opus 5 taught me how little benchmarks mean to the actual real world performance of these models.

"Better" in every sense of the benchmarks and absolutely horrible results in my day-to-day work.

The verbosity, goal post moving, tendency to leave work unfinished, over focusing on unrealistic root causes when debugging, etc... etc...

It was the first time I actually pinned my models back because I just could not work with 5 for the price and performance it gave me. Hoping 5.5 is better this time around....

Absolutely love temporal, but pretty shocked to see they have a $12.55B valuation.... feels nuts?

We're using temporal as the foundation for agents running on our platform doing accounting work for clients, it's proven extremely effective and I love how durable workflows are within temporal.

+100 on the technology, but realizing they are also VC funded makes me a little more cautious when it comes to vendor lock in.

> It's a place for assholes

Sounds like you're contributing to your own narrative here. The only self-centered douche canoe of a comment I see in this thread is from you.

HN has its share of good & bad, but I've generally enjoyed talking to some of the people on this site; much more than sites like Reddit which imo fit your description much much better.

Also.... who hurt you?

Yeah this article is quite shallow after having read it; delegating to a remote sub-agent sounds novel but how does it _actually_ perform?

I'm personally skeptical of optimizing for minimal token consumption, the closer to a vanilla setup I am the more confident I feel I'm always getting the best performance out of my models.

Just look at how JetBrains measured rtk and found that while an individual call saves tokens, agents on average perform *more* turns and use *more* tokens to accomplish one task[1]

[1] https://blog.jetbrains.com/ai/2026/07/rtk-claude-code-token-...

I've almost entirely stopped using Opus 5, at least with Sonnet I know what i'm getting -- Fable for the complex stuff and Sonnet for the precision changes.

The verbosity of Opus 5 isn't even my issue, it's consistency. For every 10 tasks Opus 5 accomplishes, there's at least one task that Opus 5 does just an atrocious job of, or a debugging investigation that it just completely goes off the rails on.

I think this article posted to HN last week did a better job explaining things IMO https://earendil.com/posts/what-is-a-harness/

One of my favorite articles posted here for this year, it's a great read and really gives you an idea of just how dysfunctional azure is.

I’ve been working on a harness for accounting agents at my job recently and it’s been a pretty interesting experience.

We originally started with building a CLI tool so our LLMs could more easily interact with our platform. I cannot recommend enough the value of having an internal CLI. It’s both fun to build and extremely useful for agents.

We paired this with skills initially, but found that the way folks built skills was often too prescriptive and limited to the authors own specific function in the company. A 2k line long skill suffers from the same gaps as we do, if an agent is just following a laundry list it’s less likely to reason about the request it’s doing.

So we instead asked ourselves: what if we just _let_ the agent reason about the work to be done and only provided the tools + guardrails to gather context and perform accounting work?

Turns out frontier models are GOOD at what they do, they outperformed our highly prescriptive skills and were able to work across a larger set of tasks even without instruction on how to do those tasks.

It’s a breath of fresh air from the decade of CRUD I’ve worked on, harness engineering is very neat.

With a whole separate LLM? FWIW you can also consider using something deterministic like vale.sh [1] , it's pretty easy to write prose violation plugins [2]

[1] https://vale.sh/

[2] https://github.com/Syntaf/vale-llm-slop

TL;DR `hop claude/57680` will cd you into the worktree for the branch.

I've wrote this tool so I can do things like `hop claude/57680 && vim index.ts` and quickly edit a file on a branch without having to ask claude to make small adjustments.

Found this pretty nice to work with when you have a lot of worktrees going and otherwise would need to be tracking down where to cd into a given worktree to find and edit a file on a given branch.

Totally agree with your framing here, but that is also what I fundamentally consider "good" code -- it's code that solves the problem that your customers/business needs without making it _harder_ to solve the next problem.

There are valid situations where the best code you can write is code you never look at and throw out the next month; there are equally valid situations where the best code is well thought through and reasoned abstractions for an area you expect to become core to the business in the near future.

Fair point! I edited my comment, A&D -> Architecture & Design

> bad engineers were always a liability

This part of the article hits home for me. With AI, "bad" engineers can now amplify their "bad" engineering x10 across the organization. The most egregious of these cases for me is often long tenured engineers who have lost interest in the craft, creating a dangerous combination of having enough merit to ship but not enough interest to make what they ship _good_.

I am still a firm believer in garbage in -> garbage out, AI is only as good as the abstractions and contracts you put in place for it. I don't subscribe to the idea that AI generated code is fundamentally bad, just that people lack the right skills today to wrangle agents into writing good code.

Earlier in the year I put together a talk for my company on what the future of architecture & design means for us in the career, I'm very proud of it and will share here in case folks have their own thoughts to share on the topic: https://youtu.be/SIZrt9Rt05Q?si=W57eirniWmoSFeBu

My company is migrating repositories over to a self-hosted forgejo instance, currently very jealous of the engineers working on those migrated repos.

There was a great article awhile back that shed some light on just how dysfunctional azure is as a platform: https://news.ycombinator.com/item?id=47616242

If I had to guess it's because Github is sitting on top on infrastructure held up by toothpicks and duct tape

Hey HN, recent hype around the ASD-STE100 standard inspired me to think about a more deterministic way to lint my agent's prose. This vale style is inspired by the english standard and is an attempt at providing a standard for teams to lint their agent's prose against.

So let me get this straight, in this article we have:

- One guy selling shovels (AI “tools”) to clueless people

- Another guy who started and then folded his business in two months

- A chatGPT wrapper (it’s literally called chatPRD)

This is our evidence of the rise of solo million dollar companies? There are surely businesses out there but is AI really the driving reason here?

I’m convinced there is an entire sector of AI now built on scamming clueless people into thinking they can build their own AI B2B SaaS and purchasing tools & “things” without realizing building the product was always the easiest part.

Does this actually work for you? I've tried adding rules in my user profile as well as adding instruction in my CLAUDE.md but my models always eventually go off the rails and start spewing technical jargon in doc strings & descriptions.

At this point I'd do anything to get claude to dumb down and simplify it's explanations in my code, so I'm looking forward to giving this a try and seeing how it goes.

It’s the pineapple on pizza of ops, people just like to fit in sometimes.

I’ve been running my own personal k8s cluster on digital ocean for the last 5+ years now and it’s dead simple.

Takes me 30 minutes to create a new namespace a deploy an app, love the bonus of having complete flexibility on my stack too — PVC + SQLite ftw

There’s got to be more to this story, what exactly were you up to with these models?

Ok long time Claude Code user here; lately I've started to realize there's other great models out there I should be trying, but I'm hesitant to leave Claude Code behind for something new.

What's the consensus today on codex vs claude code, does it really matter anymore?

Both very fair observations.

> Whether this mode of working is going to be long-term viable is going to depend on how important it is for you to be aware of what has happened for the system in question

This is the million dollar we'll see answered in our lifetime. Software engineering exists to automate work, are we arrogant to think we are not destined to the same fate? Is this truly a job befitting of a human over an agent?

Ever since I discovered my dad's C++ book in highschool I've absolutely loved coding, but i'm not convinced I have a long stable career ahead of me in SWE -- I'm 30 now and have already seen so much change in the industry during my professional career.

> how viable the economics are for the LLM usage at this level of assurance and how much ownership you exert over the LLM used or another similarly powered one

This piece scares me the most, a world where the next generation models are capped behind capital infeasible for the common person to access, further separating the ultra wealthy from what little remains of the middle class.

My hope is that open source models will fill the moat all of these AI companies so desperately want to dig, aready models like Qwen and Kimi are unfathomably better than what we had just a year or two ago.

Does Joel still disagree today?

Worth noting that this article is 25 years old. The world was very very different back then, especially when it comes to software engineering.

Context switching is a problem when the cost of switching contexts is non-negligible -- but in the age of agentic development is that still really true? Surely yes for some problems, but for many others I would argue it no longer is.

A personal anecdote for you:

At my company we have a local development CLI our devX team built, it allows for agents to interact with standing up, tearing down and managing local stacks for our software suite. When I receive customer feedback about a broken button, or a poor UX experience, I simply start up a prompt:

/metal user X reported an issue on the trial balance page, they encountered a blank page when using the inception to date filter. We need to investigate the root cause, spin up a new stack, and resolve the bug.

Then off to the next task, maybe some few hours later I'll check back in on the session and I'll see:

> PR created: https://github.com/company/repo/pull/12758295 > QA URL: http://localhost:8400/<url> > Summary of root cause and fix: lorem ipsum lorem ipsum

After a quick QA session I validate the fix, confirm that our claude reviewer has approved the PR and merge the PR to deploy. The mental burden of switching to this task is quite low, orders of magnitude lower than it would be 25 years ago.

I used the chrome MCP to profile a slow react page at my company, set a /goal and had it iterate until it achieved under 100ms responsiveness to actions.

Claude was able to identify the slowness and use various react tricks to fix the specific issues, all without my input.

I don’t think the playwright MCP can do this, unless I’m mistaken

6.x feels much more efficient with respect to token usage to be fair.

I picked up superpowers back when it first started gaining traction; the first iteration felt like an “oh shit” moment for me, then the sheen quickly wore off. Higher spend, slower throughput and mediocre results made me eventually drop it and go back to plan mode, which had improved significantly during that time.

Coming back, 6.x does feel different and I’m back on the superpowers train. I’m finding it great at taking discrete tasks from beginning to end with very little hand holding.

I run every session with a /goal as well: “Spec + Plan is written and you have implemented the plan without my involvement. You have validated that the implementation is complete and ready to merge”

It’s also great in situations where you may need to complete a plan over multiple sessions, because you get a whole ton of state with superpowers that new sessions can pickup on.