alt.hn

7/12/2026 at 5:13:07 PM

Migrating a production AI agent to GPT-5.6: 2.2x faster, 27% cheaper

 https://ploy.ai/blog/migrating-a-production-ai-agent-to-gpt-5-6

by brryant

7/12/2026 at 8:20:52 PM

> Numbers like that buy a model a real migration effort.

Such a silly choice of words. I wish the human directing the LLM writing the article put some effort into rewriting the worst examples of LLM style.

> But it did extremely well, and the promise was immediate and specific: builds finishing in less than half the wall-clock time, at 27% lower cost, scoring at or above our incumbent on completed work.

The way the LLMs write (Claude perhaps?) With short phrases separated by colons, commas or full stops, is so poor and frustrating.

There some good insights behind this article, so it's worth reading, for example below, but it isn't easy to read.

> Earlier GPT models cached implicitly on partial prefix matches, which gave decent hit rates for free. GPT-5.6 dropped partial-prefix matching:

by kristianp

7/13/2026 at 1:04:24 AM

I think for a company in AI specifically it's worse.

It makes me feel like either

1) you don't use the models enough to know how they write

2) you're not self aware enough to know it matters

3) you're oblivious to the situation overall

4) you don't respect your readers

There's no good scenario.

by alasano

7/13/2026 at 10:57:31 AM

5) You're so immersed in LLM usage that these writing patterns now seem "normal" and you don't even notice them any more.

by HPsquared

7/13/2026 at 1:13:58 PM

> The way the LLMs write (Claude perhaps?) With short phrases separated by colons, commas, or full stops, is so poor and frustrating.

This is exactly why I keep a WRITING.md file alongside AGENTS.md or CLAUDE.md.

Most people spend time telling the model what to build, but very little time telling it how to write. LLMs are surprisingly good at following explicit style guidance if you bother to give it to them.

Mine includes conventions like avoiding unnecessary colons, em dashes, and sentence fragments masquerading as emphasis. Basically, AI-isms and any grammatical errors I tend to make. It also points to writers whose technical prose I admire. Brian Kernighan and Rob Pike are great examples: clear, conversational, and readable without trying to sound important. I've always tried to do two things with documentation: 1) Make it readable and 2) Make people want to read it. A WRITING.md file helps with both points.

If you're generating documentation regularly, it's worth having your agents reference a WRITING.md file. The improvement in readability is often much larger than any gain you'll get from switching to the latest model, and it can keep your documentation consistent between model switches.

by mkovach

7/13/2026 at 1:42:18 PM

Willing to share your writing.md somewhere? pastebin or the like? I'd love to take a look at how different people are doing this.

I disagree with the person below - I don't think its a wrongheaded goal in and of itself to get better ai generated writing. I read ai output half of my day, I may as well try and make it better for my own sake. Passing that onto other people is an entirely unrelated field of problems, and passing it off as stuff you authored yourself is just plagarism.

by RugnirViking

7/13/2026 at 2:04:45 PM

Here is a sample I am using for testing on a personal project (I'm also working on using SpeechActs to do prompting, so yes, the repo is all AI-generated).

https://f.mek.cc/gombasic/file?name=WRITING.md&ci=tip

And in many cases, like you, I spend a good amount of time reading AI documentation. I'm not "stealing" anything, just having a model generate words in a specific way. I'm just being precious in how I want things, without having to do it myself.

by mkovach

7/13/2026 at 1:41:40 PM

Making a problem harder to sport is not a way to fix it.

by Planktonne

7/13/2026 at 2:10:25 PM

I understand what you are saying, but inside the repo, I'm making it explicit.

I'm not trying to hide the problem, just offering a solution that people may find useful, or curiously odd.

by mkovach

7/13/2026 at 5:00:22 AM

Whenever I suspect an article is LLM authored I stop reading it immediately and instead give it to my LLM tool of choice to summarize/ paraphrase.

This way I can at least somewhat control the style of the output.

by baxtr

7/12/2026 at 11:35:35 PM

Makes you wonder if any of stats these articles push are even real.

by dawnerd

7/13/2026 at 1:02:32 PM

My current claude.md bans the phrase “load-bearing”, and Claude HATES that. It will troll occasionally in comments by saying things like “load-be…most specific”. Like it REALLY loves saying load-bearing. Urgh.

by vessenes

7/13/2026 at 1:18:35 PM

You are poisoning the context and priming it to say load-bearing. I don't really think there is a good way to actually ban specific phrases other than have it do a second pass, it's something baked into the model from post training.

by Anon1096

7/14/2026 at 2:35:16 PM

I hear you. And, it says the phrase ALL THE TIME even without any priming. Anecdotally it’s better to complain about it. But not a lot better. I have no idea how often it’s using load bearing in the thinking traces though

by vessenes

7/12/2026 at 11:33:49 PM

Gets a 100% on Pangram. Stuff is so distracting. Write your own posts, FFS. Or at least pass it through "humanizer" type plugins.

by icelancer

7/13/2026 at 7:46:48 AM

I would rather read an article with actual production experience migrating an agent, even if it is written in this style, than a perfectly crafted long read from another evangelist that has nothing but high level fluff and general phrases about the bright future of ai

by SwtCyber

7/12/2026 at 10:45:56 PM

You should make sure to not read Stratechery then. It's writing is even worse.

by try-working

7/12/2026 at 10:02:34 PM

Can we get over the detective work about if the text was written by LLM or not in 2026 already ? This is a lost cause, and we could instead focus on substance over syntax.

by w4yai

7/12/2026 at 10:12:50 PM

Not OP but my frustrations come from it being impossible to ignore and outright distracting.

I've found the same thing showing with Claude-coded/designed front ends that overuse the same semi-monospaced fonts, Blue/Yellow/Red palette and rounded corner borders. It isn't that it is bad, but it often isn't fit for purpose.

You're right it wont change anything, but authors shouldn't be surprised when people who care about their time/attention comment on low/no effort pieces.

by liquidise

7/12/2026 at 11:51:42 PM

critique of writing style isn't made better by claiming it was authored by an LLM

by spongebobstoes

7/13/2026 at 12:05:13 AM

No but it's a useful shorthand to describe a type of bad writing.

I also think that people should focus on substance and not if AI was used, but AI writes like shit and I find myself retching a bit when I have to read long AI-written documents. Do they say something useful? Maybe, but when my eyes are glazing over because it's just so exhausting trying to parse what's written, I can't tell.

I certainly think less of people when they have such poor taste that they think writing like that is acceptable.

by SR2Z

7/13/2026 at 12:16:47 AM

This is just an AI comment masquerading as not trying to prove a point.

by jasonlotito

7/13/2026 at 1:03:03 AM

Since you didn't address the substance, I guess we'll never know :)

by SR2Z

7/13/2026 at 12:35:01 AM

I’m as pro AI as any.

Slop is slop. When the “it works but isn’t great” phrases end up slipping into a strong conceptual core, it compromises the perception of the ideas.

Perhaps our AI will cater to us by rewriting the content we read, and each of us intermediate all communication with systems that make that slop bearable.

Or perhaps, we learn that we kinda still need to give a shit when writing to land on the perception we’re trying to create within our readers

by aeon_ai

7/13/2026 at 5:58:18 AM

To be fair internet (or rather shovelware websites like Medium) were already flooded by crap articles based on a set of templates. Of course the issue is that LLMs are actually better than the robot-humans who used to write them so now it takes more time until you figure whether it’s worth reading or not..

by wqaatwt

7/13/2026 at 3:56:22 AM

Maybe if instead we stopped engaging they would wonder why

by culopatin

7/12/2026 at 10:44:21 PM

To me it's a useful signal not to read an article that someone didn't bother to write.

Which is a shame as real insights are buried inside some of these articles, which if the author bothered to write in his own words could have reached an audience that would have appreciated them.

Writing is one of the areas where I want no LLM involvement.

by justAnotherHero

7/13/2026 at 9:13:56 AM

I keep coming back to this https://tombedor.dev/human-attention-and-human-effort/

The number of things that make it to the top of HN/Reddit/wherever now that are devoid a human's touch is exhausting. Whether it's a site that's got that Claude frontend smell, or a repo that's got a burst of 10 claude commits before getting shared and abandoned, or a series of blog posts that were written by LLMs... it's all, at this point, a flag for me that the human behind the LLM doesn't really want to engage with others or share; in some ways it dehumanises their entire (supposed) audience.

IDK. Maybe having Claude contribute writing about something novel to the general blogosphere is useful in some dimension, but it usually gives me no confidence in the truth of the post.

by frio

7/13/2026 at 2:00:24 AM

More often it's the difference between finishing something and not finishing it - so often LLM's are helping them reach an audience that would appreciate them, even if that audience doesn't include you

by CookieCrisp

7/13/2026 at 5:49:46 AM

I agree with the copy-pasted slop that you see sometimes, that is probably generated from a short prompt and therefore has no real substance to it.

If an article has interesting content (which comes from an human) and the LLM is just used to help the author finish off the article, I don't have any problem with that.

Labeling both scenarios in the same category feels completely wrong to it, as equating vibe coded stuff (as in no human ever read the produced code) and agent-assisted good old software engineering

by gbalduzzi

7/12/2026 at 10:08:56 PM

The problem is that the second you suspect something is written by AI, its a pretty good signal that 50-80% of the text is empty of meaning. Maybe that will change, but LLMs are terrible and inefficient writers.

Only so much time in the day, its a quick signal to not waste anymore of it.

by spicyusername

7/12/2026 at 10:14:33 PM

Correct. AI == Credibility hit and it's increasing as more humans get used to feeling they are AI slop consumers, not worth the time for genuine human engagement. Human engagement costs are increasing. Amazing to read/watch.

by lewistaariq

7/13/2026 at 12:03:40 AM

It's not about figuring out if it's LLM written though. The style is hard to read and annoying. With the kind of sentences GP was talking about it's actually harder to get the substance.

by afro88

7/12/2026 at 10:27:49 PM

It's both poor substance and style, in most cases (and this case.)

Pointing out they generated it at least encourages them to write a shorter article that says what they meant.

by 1123581321

7/13/2026 at 12:08:05 AM

Yes, as soon as models come out that can write properly, we'll all instantly get over it. Until then we'll be having this discussion over and over, as many times as it is necessary.

by dandellion

7/13/2026 at 1:20:28 AM

It means I don’t trust the substance. Whenever I try to use for technical writing like this, I catch it getting things wrong constantly.

by girvo

7/12/2026 at 11:00:48 PM

Evaluating substance takes time - perhaps more than was invested in the article to begin with. So these tells are very distracting because as soon as I see them I wonder if the person who prompted the LLM even bothered to read the output. If they haven't, then I certainly shouldn't invest the time to determine if there is any substance.

by jeremyjh

7/13/2026 at 1:07:33 AM

No. As a human I like reading human written text over computer written text. I want something a human composed with thought put into it. Not something a human tried to save time with by having the machine write it.

by illusive4080

7/12/2026 at 11:06:00 PM

What substance? That they consume a newer model from the same vendor?

by conjectures

7/13/2026 at 1:24:04 AM

the frustration is largely because the overall substance is quite poor since it is typically imprecise by nature.

by rsalus

7/13/2026 at 1:01:57 AM

Because quality of writing matters.

Good communicators learn to use the written word. Bad ones rely on mental crutches.

Good communicators get an audience, and bad ones won't.

You think it's a lost cause, but it's not, because people don't like this junk, because it is low quality and, on average, lacks substance.

The best minds in AI that I've seen all write their own words. They use AI to help them research or ideate, but what they write is their own.

Before assuming this is a "lost cause," consider why the smartest people in the room don't do it.

by mediaman

7/13/2026 at 7:26:05 AM

Its never lupus and its always an LLM. No need for detective work.

by blitzar

7/13/2026 at 5:52:03 AM

100% this.

The AI police is there to say what is worth reading and what is not, because THEY know what people like.

Or not.

by xeyownt

7/13/2026 at 5:29:36 AM

It's not detective work, it is literally blatantly obvious and impossible to ignore.

And no we can't get over it either. But I already have talked about that before and said roughly all I have to say on that front, so I'm just going to link back to my last comment regarding this.

https://news.ycombinator.com/item?id=48861849

by jchw

7/13/2026 at 2:46:35 AM

But it's not about whether it was AI or human authored. That misses the point. We're all fatigued on the writing style. The same cadence and patterns; the same phrases and terms like "load-bearing". Used everywhere, they create a super fatiguing monoculture in all the writing. It's like if every illustration on the internet suddenly contained Garfield the cat.

by toddmorey

7/13/2026 at 12:18:04 AM

The syntax tells you there isn't any substance.

by Planktonne

7/12/2026 at 10:24:10 PM

I have a counter proposition: don't fall for this constant suggestion that LLMs are an unavoidable future would you leave the techbros alone now pretty please, relentlessly keep reminding that we still don't think it's acceptable so people don't start to think this is okay since nobody complains anymore.

I appreciate these comments, they save me time for procrastinating elsewhere.

by jraph

7/12/2026 at 11:55:38 PM

I agree with this sentiment: it’s not inevitable if we relentlessly ostracize obviously LLM posts

And let’s be real: I had a post this year that was #1 on HN for a while, and an LLM “wrote” the whole thing, but it was very much my writing style and NO ONE called out the post as LLM slop. If you use an LLM correctly for writing, it’s not detectable. It seems that most folks don’t go through that effort.

by derwiki

7/13/2026 at 12:14:25 AM

The substance is shit too with these LLM articles. Stuck in the box of the training set. Nothing new. Just regurgitation.

by asdff

7/13/2026 at 7:17:51 AM

No.

by multjoy

7/13/2026 at 5:33:10 AM

My solution to this is to dump it into an LLM and a prompt that roughly does something like...

Hand wavy list just to get a general idea...

1) Give me a condensed summary 2) Is this adding anything to what we already have? (I save good articles along with annotations and whatever notes I may write to go along with it.) 3) Locate any upstream ideas on this (often AI articles are rehashing much better written ideas.) ...

Something like that. Not that I have some great system for it. I find these articles are so full of fluff that I have lost patience to attempt to get through them. So, I pull out the AI to parse the AI. I know that the AI may miss some hidden gems, but I'm okay with that.

by gexla

7/13/2026 at 5:53:21 AM

You are reading it wrong. Ask your LLM to read and summarize based on your style preferences. Better yet don’t read anything at all, just tell your agent to convert it to a skill file for it’s future reference..

by wqaatwt

7/13/2026 at 6:23:34 AM

Unironically, I think in the future we will have the option to run filters in our browsers that can reword articles to your preferred writing style. Like user stylesheets for text. I also assume it already exists out there, I've just been to lazy so far to look for it. It's a relatively obvious application of LLMs.

by user_of_the_wek

7/13/2026 at 7:37:09 AM

I've used that for about 15 years because I live abroad, it's called Google translate.

by vasco

7/13/2026 at 2:53:31 PM

Google Translate can change the writing style of a text? I thought it would just translate between different languages.

by user_of_the_wek

7/14/2026 at 6:21:30 AM

Great gotcha

by vasco

7/13/2026 at 6:19:52 AM

this is probably sarcasm, but might actually try this. the visceral negative reaction i have to llm writing makes me instantly want to close the tab

by yulker

7/13/2026 at 10:14:53 AM

If written sarcasm isn’t properly labeled as sarcasm, per Poe’s law, you may consider that message you replied to be a genuine opinion.

I would have downvoted the sarcasm (it doesn’t contribute to the conversation), but I believe it actually is the author’s opinion.

by Diti

7/13/2026 at 1:03:20 PM

I promise you its not.

by wqaatwt

7/12/2026 at 10:51:43 PM

> The way the LLMs write (Claude perhaps?) With short phrases separated by colons, commas or full stops, is so poor and frustrating.

Yup llmish (from now on it's called "llmish") sucks.

But I'd say: at this point it's probably trivial to write a browser extension that detects llmish and that rewrites the worst sentences: from llmish to something less irritating to read. Heck, I could spent tokens on that: an extension that changes on the fly llmish found on webpages.

Also I'd say there's typically no swearing at all in llmish: llmish is too politically correct for swearing. So the rewrite could maybe also use a few "offending" words.

Offending words that, btw, are not going to go well with Gen Zers. Poor Gen Z... They've been raised with the state and its institutions (like school and then universities) hammering them with the notion that they were precious little unique snowflakes and now they arrive on the job market only to be told they've been pre-emptively replaced by AIs. And because they cannot stand a single curse word (because it's "offensive to minorities" or something), they'll be driven off by text rewritten to contain curse words. So they're condemned to read the bland, dumb, AI-generated llmish for the rest of their lives.

Honestly sucks for them. Fuck that.

by TacticalCoder

7/13/2026 at 3:03:44 AM

As a certified Gen Z member: respectfully, what the fuck are you on about?

The mythical Gen Z you are describing is the hyperbolic exaggeration that is equivalent to me describing all boomers as racist, all Gen X as entitled, all millennials as lazy, etc.

by weakfish

7/13/2026 at 12:09:22 AM

Have you ever met an actual Gen Z? They have no problem with swear words. Many of them love Key and Peele, whose humor is like 90% racist jokes.

If wokeness actually did capture a whole generation then why even bother complaining?

by SR2Z

7/12/2026 at 10:57:49 PM

For me, it's Bottish

by CarRamrod

7/12/2026 at 10:47:22 PM

We run a lot of varied, tiny, simple workflows that were previously running on 5.4-nano and mini. We transitioned them to 5.6 and noticed exactly this range of improvement across the board. In a few cases, we had improvements in classification.

I think a lot of people miss that for many companies, a model upgrade like this is basically a one liner.

Even if you have an amazing model router architecture (which we do for our golden flows), it’s just not worth it. Not to mention reliability and so on

by thiagoperes

7/13/2026 at 7:20:43 AM

The first thing I used Sol for was to assess 5.6 on our workflows - previously, it was 5.5 for everything, as the quality on simpler models was just not good enough. We’re doing a mix of text and image analysis to extract explicit and implicit structured data from a steaming pile.

They do work pretty much as advertised. The bulk of our workload is now going via terra, which has cut our cost in half by itself, as well as improved response times by 50% - luna I am using as a backstop for opencv hits, and it is good enough, and so cheap as to almost be free - but very limited - and very fast. Sol only gave marginal improvements over terra for our workload.

I’ve also gotta say I’m impressed as to how well Sol ultra carried out the assessment itself - it made sound recommendations, and gave me a nice big dossier of “you should look at these outputs yourself and compare and consider” along with raw and digested data, and cpm for queries.

Anyway. Spent nothing beyond my pro sub, let Sol gnaw on it for a few hours, and my cost basis just dropped 50% and throughput improved by 100%. Win.

by madaxe_again

7/13/2026 at 4:06:32 AM

the article is literally about the model upgrade not being a one liner

by desterothx

7/13/2026 at 3:59:55 AM

What SDK are you using? Or is it custom?

by febed

7/12/2026 at 7:39:24 PM

> Ploy’s agent builds and edits real marketing websites. It plans a page, reads the codebase, writes components, generates imagery, screenshots its own work, and decides when it’s done. That job description sets a very high bar for a model, and we test every frontier release against it. For the four months Opus held the default slot (first Opus 4.7, then 4.8), nothing we tested beat it.

Well, unlike OP I haven't run a rigorous test, but I still would expect Fable to be significantly better at building marketing websites than Opus. It sure is way better at building decks.

by blfr

7/13/2026 at 7:32:03 AM

gpt 5.6 is so much better ar design than fable

by make_it_sure

7/13/2026 at 1:30:52 PM

Can you please provide evidence. It shouldn't be hard to give side by side comparison. I have not found any task where gpt is better than fable.

by cute_boi

7/12/2026 at 8:08:28 PM

4.7 is very autistic in terms of following directions so I find OPs claims plausible

by greenavocado

7/12/2026 at 8:39:36 PM

Very descriptive there heh

by arikrahman

7/12/2026 at 10:09:59 PM

Game recognises game

by aeonfox

7/13/2026 at 6:08:49 AM

My experience mirrors this: services like OpenRouter that promise “failover” are pretty much useless except for sandbox testing because models in production are not really interchangeable. Any production harness doing serious agentic work in production is dependent on more model-specific quirks than you would expect. And even if another model works without errors, performance and efficiency is a whole different story. Even the system prompt can and should be tuned to a model’s preferred speaking style, for example <xml tags> for Claude-like models because they were trained on it, while other models do better with other delimiters. Think of the whole harness, prompt, and model as one system, not really with modular parts that can be swapped out if you care about optimal performance.

by znnajdla

7/13/2026 at 7:24:25 AM

I believe part of the LLMOps (I don't like the term, but it is what it is) should be building a failover plan with proper testing that check tools trajectories and such. If you have these then you can sort the good enough models from cheaper to more expensive and have the failover you mentioned.

I saw people bulding a mapping of model->{{prompts}, {tools descriptions}, ...}, but that, to me, it feels extreme. I believe it is the model that needs to adapt to your prompts after a certain point. Models that fail to do so won't get our api requests as they will be out of the failoever roster.

by marcyb5st

7/13/2026 at 7:33:52 AM

OpenRouter doesn't fail over to a different model, it fails over a different provider of the same model.

by hamandcheese

7/13/2026 at 9:16:49 AM 

    As of today, Ploy’s agent runs on GPT-5.6 Sol, the flagship tier of the model family OpenAI released this morning.
Wait a moment, did they make the switch based on half a days of playing with Sol? Are these companies ran by teenagers?

by throwa356262

7/13/2026 at 1:27:40 PM

hah - we actually skew staff, senior staff.

We have been testing GPT 5.6 for about a week as a preview model through a YC relationship, providing them feedback on the model. Our evals run in github CI and we can run them all in about 15 minutes against our eval bench of 115+ web design and marketing related jobs that ploy.ai specializes in.

then after we toggled it on (through a posthog feature flag) we actively monitored for failures.

I came from running Webflow, which powers > 1% of the internet so trying my best to relay all of that knowledge to ploy to power more % of the internet!

by brryant

7/13/2026 at 2:55:05 PM

This is super impressive - both the pedigree of the team and the approach you took.

The funny thing is - when I first saw ploy, I didn't take it very seriously since so many of the signals that used to signify quality (decent design, copy, hard technical problems) are easy to fake. Plus the "grow while you sleep" space is crowded with weak players.

I wonder what the new markers of quality will be, which would separate the hand-crafted (to the extent possible) work v/s slop.

by antileet

7/13/2026 at 3:29:47 PM

agree that many of those markers of quality are now low signal. Ultimately we let our customers vote with their wallet

Funnily enough, we spent a long time on our brand. From our launch video that has human actors, to our product details. I believe a distinctive, high quality, well implemented brand is still a hallmark of a strong product or service.

by brryant

7/13/2026 at 1:12:13 PM

There’s every possibility they got some amount of early access to evaluate GPT5.6, precisely so they could write an article like this.

by avianlyric

7/13/2026 at 2:15:01 PM

at this point, it's pretty easy to create evals/benchmarks, and then run the latest model on them.

LLMs are so easy to swap out, so having good benchmarks/evals are pretty useful.

Even then, a lot of the time the model improvements are so obvious that you don't even need an eval.

by peab

7/13/2026 at 11:00:38 AM

I would expect they have production based datasets they evaluate new models against.

by fxwin

7/13/2026 at 12:37:00 PM

I would not expect that. They wouldnt have missed mentioning it if that was the case. Its mostly driven by vibes.

by dominotw

7/14/2026 at 10:17:15 AM

>For four months, no frontier model beat Claude Opus in our production evals

What do you think that is referring to?

by fxwin

7/13/2026 at 12:52:07 PM

AI psychosis is still at all time high

by sekai

7/13/2026 at 7:41:20 AM

Its ironic that under an article with a ton of deep infrastructure insights half the comments are crying about the "forced writing style". What does it matter if claude helped the author clean up the text when inside is a ready-to-use blueprint on how to save 30% of the api budget and fix empty file reads?

by SwtCyber

7/13/2026 at 1:09:12 PM

One of many reasons I would assume is that people just hate anything related to AI, so they latch on to anything negative they can say.

Another reason is that they mean what they say... That they really, really hate the style of writing, enough to fixate on that.

Personally, I think the people whining about the style are silly. Maybe because I'm terrible at grammar and spelling, but I always just focus on the message, not the delivery. I just care about the concept, facts, the argument, and so forth. The actual grammar and spelling are just trees, while the forest is the point.

Edit: just an infobit: The reason my text isn't full of errors is due to the awesomeness of the dictation and a custom hotkey I have created on my computer, which uses a local LLM to spellcheck any text I have selected and replaces it with the corrected one. Nothing has improved my quality of life and writing more than these two tools!

by jtrn

7/14/2026 at 2:49:46 PM

On the infobit, I've been trying to build in a similar completely local LLM cleanup step into Epilude. Willing to share anything you've found especially useful in producing good spellchecks/cleanups in your local setup?

by oakst

7/13/2026 at 3:57:50 AM

> The fix that worked is a schema transform at the provider boundary. For OpenAI-family models only, we rewrite every optional property to be required but nullable, using anyOf: [T, null], which gives the model an explicit way to say “not using this.”

I admit, I've only used a bastardized form of MCP, but this smells... wrong? It's not clear to me why the Typescript type definitions would have any influence on (what I presume is) JSONSchema being sent from the agent to the inference backend as part of the completion request. The MCP specification (which the OpenAI backend might not use, I don't know) has an explicit field to signify "optional" parameters in the JSONSchema; my read on this is there's a bug somewhere between the Typescript layer(??) and the generated tool description which is actually sent to the inference backend.

It's possible the inference backend has changed from "generate valid tool responses" to "generate valid tool responses according to the JSON schema [where no parameters are optional]" but it's impossible to tell without seeing the actual requests sent to the inference backend (which I didn't see in TFA).

by lcampbell

7/13/2026 at 8:11:46 AM

The thing is this isn't a schema generation or Typescript bug at all. This is just how openai's function calling works under the hood. Their weights were fine-tuned for tool use to output the most complete data structures possible. If the model sees a parameter name in the system prompt context it will try to fill it with a value, even if it is not in the required array

by SwtCyber

7/13/2026 at 1:15:24 PM

If it isn’t a schema generation or typescript bug, then why did changing the API types they use result in different model behaviour?

by avianlyric

7/13/2026 at 4:10:01 AM

Modern frontier models, including Fable/Opus and 5.6, are often very loose with tool calls, and often don’t follow your schema precisely.

For example, see this post for Claude models hallucinating properties for an edit/replace tool call in Pi: https://lucumr.pocoo.org/about/

I suspect some part of this comes from the noticed intelligence degradation when you do constrained decoding. Yes, you’re guaranteed schema validation, but you lose a lot of intelligence. It’s fine if you just want a classifier, a summary, a prompt enhancement, etc; but I’d be careful in agentic loops.

Harnesses like Claude Code do a lot of preprocessing, repairing, cleaning, etc; as the blog post shows. You usually don’t see it.

In practice it’s easier and better to just make your harness “looser” and work better with the model (they’re coming out every month or two anyway, each with their own idiosyncrasies) than to assume and force perfect correctness.

Welcome to vibe applied AI ;)

by dannyw

7/13/2026 at 6:55:31 PM

It's not typescript definitions. Presumably it's zod schemas which are both typescript types and JSONSchema for the object.

Although tbh the article makes a lot of this obvious and trivial change in syntax.

by bluelightning2k

7/12/2026 at 8:41:08 PM

Migrating my workflow to Reasonix with cache hits on Deepseek make requests practically free, and that's on unsubsidized American providers.

by arikrahman

7/13/2026 at 1:06:07 AM

Sorry, what did that have to do with the article?

by gunapologist99

7/13/2026 at 1:25:52 AM

They also migrated and that also made the workflow cheaper.

It has everything to do with the article.

by bel8

7/13/2026 at 5:56:17 PM

Reasonix, the harness, only works with DeepSeek.

Neither are mentioned in the article at all, which was about a migration from Claude Opus to GPT 5.6.

Maybe a bit of DeepSeek astroturfing going on?

by gunapologist99

7/13/2026 at 7:47:55 PM

I wish people were astroturfing it

by arikrahman

7/13/2026 at 4:09:29 AM

What's your config, how does it compare to pi

by desterothx

7/13/2026 at 11:01:46 PM

Here's my config for agents: https://codeberg.org/arik/agents It's a lot better since it's optimized for the model and cache hits, unlike other frontends that try to be more general.

by arikrahman

7/12/2026 at 10:18:34 PM

> we’ve made GPT 5.6 Sol the default model powering every Ploy workspace

I would consider Luna for parts of the workload that touch actual tools. It is surprisingly capable and it runs fast.

Sol is great at talking to the human and orchestration of agent calls, but it's just too expensive to use everywhere.

You can get 5 Luna runs for the cost of 1 Sol run. Statistically speaking, going from one to five samples is a pretty big deal.

by bob1029

7/12/2026 at 11:17:57 PM

The problem I always run into with subagents is that they are isolated. This is a double-edged sword, as it keeps context down and lets them "focus", but it often means they must do their own research to continue to do work given to them, which eats uncached tokens.

So depending on how heavily agents are used on what tasks, it's entirely possible that you get worse work for more cost.

by Tadpole9181

7/12/2026 at 11:50:45 PM

> they are isolated

This is a feature if your goal is to obtain many samples. Independence is critical. This makes it easier to accurately model the uncertainty of a decision.

by bob1029

7/12/2026 at 11:53:50 PM

I feel Claude Code has added (and removed?) a feature that forks a subagent from the parent context, so it’s still isolated but it’s more of a continuation of what you were doing in one narrow direction and then it dies. Rather than a blank slate with a prompt of what to do.

by taspeotis

7/13/2026 at 2:39:31 AM

Statistically speaking if each part of the Luna run has a 90% chance of being correct, 5 of those is 0.9^5 = 0.59 = 59%. Or one Sol run being maybe 95% correct? Exact numbers vary of course. But then again having sol verify at end may be cheaper.

by auspiv

7/13/2026 at 6:51:33 AM

The goal is not 100% correctness. The goal is to demonstrate the current amount of variance / uncertainty to the planning agent.

If the planner sees that 4/5 Luna runs resulted in approximately the same summary, it may conclude that variance is low and that it is over the target. If all Luna runs are different, the planner can conclude that additional research rounds are required.

by bob1029

7/13/2026 at 6:44:56 PM

Most agent harnesses that have not been designed from scratch for current models are over-engineered.

Chances are whatever was needed to make earlier models perform well now either is no longer helping much or actively hurts performance (worse results, slower, uses more tokens …).

by tosh

7/13/2026 at 6:50:36 PM

Agreed!

Example: for large Eloqua/Marketo/HubSpot emails we would previously make a planner which delegated the sections to their own call.

GPT5.6 can do the whole thing. The planner is unhelpful.

My suggestion: feature flag your complex implementations so you can rapidly contrast with and without it. (Or a formal eval suite if you have one).

If you prefer the simpler path, delete the old path.

Note: the challenge is making things compatible with these tools. Obviously generating html directly has been simple for ages.

(Source: mopsy.ai)

by bluelightning2k

7/13/2026 at 1:05:47 AM

The cost reduction is impressive, but I think consistency matters even more for production agents. I'd be interested to know whether prompt engineering or tool-calling workflows had to change significantly.

by redfather918

7/13/2026 at 2:50:39 AM

He actually talks about that in the article. Including how they had to rearchitect tool calling using nulls as well as limitations of prompt caching

by narmiouh

7/13/2026 at 6:47:17 AM

Personally, could you share the code sometime later? The GPT code looks decent to me. Or even just the prompt would be fine.

by jdw64

7/13/2026 at 4:07:47 PM

What does a site build cost, in real $$ with Opus vs Sol? Could you share a ballpark?

by yusufnb

7/14/2026 at 1:54:52 AM

[flagged]

by jon_steadioai

7/13/2026 at 3:35:31 AM

I catch a lot of issues on the technical writing side.

by desktopentree

7/13/2026 at 4:14:49 PM

AI wrapper companies still exist?

by brcmthrowaway

7/13/2026 at 6:59:55 PM

Must admit, for this particular case I don't see the appeal in using a wrapper.

Why would I not just use Codex directly?

The we wrote a bunch of prompts argument is kind of meh. That sort of thing has not only diminishing value with subsequent model releases but I actually believe will turn negative. The model will know better by default.

For example, initially giving the model some advice on code best practice was helpful. But now it's unhelpful because the model already knows best.

by bluelightning2k

7/15/2026 at 2:05:30 AM

Idk man, they raised money lol

by brcmthrowaway

7/13/2026 at 2:23:19 PM

is it common to measure LLMs with landing pages like this ? it seems a bit too simple

by agumonkey

7/13/2026 at 4:29:16 AM

I found Claude to be better for the first prototype. It was more likely to come up with something fast. But it kept lying and claiming it did world class work and it was just hardcoding response by the end. I found GPT never lied to me.

by htlemur_bobby

7/13/2026 at 4:24:37 AM

We at Playcode.io - a company similar to Ploy are still using Opus 4.6. "Why?" you might ask.

Because GPT 5.6 Sol, while fast and pleasant to use, is essentially the same model as 5.5 wrapped in new marketing packaging, just to avoid losing ground to Anthropic. In practice, it's the same quality: it generates the same garbage, tons of code, and can never solve even a single complex task. We simply don't trust it to write code for clients that they'll end up throwing away anyway.

"Then why not Opus 4.8?" you might ask.

Well, because Opus 4.8 and 4.7 are just another lie, a price hike with no actual quality improvement.

That's why at Playcode, we give our clients the best possible quality/price - which is Opus 4.6. Regardless of what people write in articles like this.

by ianberdin

7/13/2026 at 6:02:29 AM

Did you just paste your marketing copy into a hn comment?

by Valodim

7/13/2026 at 6:35:56 PM

I have already developed a habit of speaking in this format over 10 years of supporting my product.

by ianberdin

7/13/2026 at 4:27:15 AM

Everyone probably has the same question: what about Fable? Fable 5 is sick.

It is simply the best model in the world out of everything we have ever tried. It's absolutely fantastic. It solves almost any task from start to finish, the way it should be done — no errors, perfect code. It's a miracle.

If there's any way to make it a little more affordable, that would be incredible.

As for GPT-5.6 Sol — it doesn't even come close. I honestly don't understand why people even try to compare them. It feels like Sam's attempt to hold onto his audience with those endless daily limit resets. A clever trick, nothing more.

by ianberdin

7/13/2026 at 5:34:11 AM

> Fable 5 is sick. [It] solves almost any task from start to finish, the way it should be done — no errors, perfect code. It's a miracle.

> As for GPT-5.6 Sol — it doesn't even come close. I honestly don't understand why people even try to compare them.

What kind of problems are you working on? I like Fable but when planning work on a complex C codebase it's making more mistakes than 5.6 Sol xhigh for me.

In what scenarios is Fable giving you "no errors, perfect code"?

by porker

7/13/2026 at 6:40:37 PM

I have a large monorepo that includes about 15 TypeScript services and many Rust services. Everything is well-documented and organized, with standardized and structured custom code.

When an issue arises, I often test the systems by providing a minimal prompt, like: "this user, this is their email, this isn't working, figure it out in production." I send this to both Opus and ChatGPT, but it doesn't help. I've set up Agents.md and Quote.md identically, with the same access and linkers, so the Harness is consistent.

ChatGPT rarely succeeds. If the task is complex and requires a multi-step process to identify the true cause, ChatGPT usually stops after a few initial ideas and wrongly claims it has found the solution.

- For simple tasks, like identifying a missing item in a to-do list, ChatGPT performs well. - However, for issues like memory leaks or file system corruption, it struggles.

On the other hand, Opus 4.8 always finds the solution, albeit slowly. I can rely on it without worrying about whether it will succeed. It just gets the job done.

Recently, Fable 5 has emerged, which resolves issues without needing any prompts. It operates even faster than Opus.

When I ask ChatGPT or Opus to create a new feature: - ChatGPT often produces superficial results, ignoring existing code and building unnecessary independent code. - Interestingly, the outcome from ChatGPT appears functional, but it's usually incorrect, focusing on a superficial "aha!" moment.

Opus, however, plans thoroughly, executes, and cleans up, ensuring everything works correctly. If needed, I can provide more realistic examples, though it's challenging due to the monorepo's size and complexity, with hundreds of thousands of lines of code.

by ianberdin

7/13/2026 at 6:52:56 PM

Claude is Extremely slow, especially fast few days. Codex is so much faster in in my opinion with comparable quality. Anthropic is going to fix their problems, but for me as a user that depends for the service to work, it's not acceptable. ChatGPT 5.5 is already a better version than Opus 4.8, at lest in my experience. Firstly, thing get done today and I don't see quality to be worse. I has many situation where Opus was just going in circles, finding more and more issues with the code it wrote a few hours back, to me this is counterproductive.

by yruzin

7/13/2026 at 6:30:33 AM

For PCB design 5.6 Sol/Terra is streets ahead of 5.5, and uses fewer tokens, so I'm not sure it can really be the same model.

by mattclarkdotnet

7/12/2026 at 11:47:54 PM

[flagged]

by implexa_founder

7/13/2026 at 3:31:53 AM

[flagged]

by modgate

7/13/2026 at 3:09:12 AM

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by langs

7/12/2026 at 10:08:32 PM

[flagged]

by przemarzec

7/13/2026 at 2:58:16 AM

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by rjnz199

7/13/2026 at 1:35:31 AM

[flagged]

by jing09928

7/12/2026 at 10:28:47 PM

[dead]

by luciana1u

7/12/2026 at 10:29:24 PM

[dead]

by CurbStomper

7/12/2026 at 7:58:37 PM

[flagged]

by hankbond

7/12/2026 at 8:38:42 PM

But what users prefer? Given this is for marketing, which results produce more conversions? From the examples shown, personally I strongly preferred Claude Opus in all cases.

by estebarb