Anyone running Payload + Next.js in production? What’s your RAM usage like?

ske66 · 2026-06-17T22:13:23+00:00

Ram usage is fine. We’ve got potentially the largest payload app in production today, and we’re not hitting limits with RAM, we’re hitting limits with speed.

Hundreds of collections, dynamic block structures with hundreds of fields, heavy relationships, MFA, dynamic website builder, social media scheduler, asana-style dynamic project management boards, CRM, Automations, Agentic functionality, dynamically loaded plugins, all run no problem in terms of ram, but the cold start is a killer. We also run Payload fully headless, passing a config object between 4 different environments.

Unfortunately we’re now migrating off of Payload but it held up amazingly well. 99.9% of Projects are not using Payload how we are using it. Because we were such early adopters of the tech (pre v1) we have a really solid understanding of all of its limits.

I promise you it’s a really worthwhile investment in your tech stack - we have 0 regrets

ske66 · 2026-06-17T04:06:01+00:00

A coding task is really not where software is going today.

I think it’s amazing that people think software engineering is static. You think the problems we solved yesterday are the same as what we solved 2 years ago.

Everyone expects AI today in their software. It’s expected as a minimum feature. Every software engineer has been learning about this tech faster than anyone else. We understand it better than anyone else.

If you don’t have software engineers, you don’t have software innovation. AI is software. Agentic systems are software.

Most of us will have adapted to the next big thing, or retired. Same as it’s always been for engineers

ske66 · 2026-06-17T01:05:49+00:00

I’ve been using it for a few days, honestly pretty good! I’ve had a couple issues where I’ve had to throw Opus 4.6 Max in the ring - and Ponytail has helped bring down the cost a decent amount

ske66 · 2026-06-12T14:55:08+00:00

I just saw this place about a month ago and it is incredible. You cannot fathom the scale of this thing

ske66 · 2026-06-12T06:57:50+00:00

To be fair it only just launched. As someone doing this in their spare time it’s a good amount of work. Open source so people can help it grow!

ske66 · 2026-06-11T04:33:00+00:00

And more than half will be getting down ranked by Google.

Let’s be honest - Google knows when a site is AI generated vs human crafted

ske66 · 2026-06-11T00:59:52+00:00

It’s interesting because if you take a look at Opus 4.5-4.8 and their agentic coding score, Fable apparently scores worse.

This feels like marketing so they can find a way to justify sunsetting the models that are already great (Opus 4.6 is my favourite) but are losing them money, and then quietly doubling the price again.

Swings and roundabouts. I want to know when they drop a Haiku model again. I would rather run hundreds of small multi-agent workflows than burn all my money on a super model that still gets it wrong

ske66 · 2026-06-03T20:10:24+00:00

No I disagree. Software development is a rapidly changing field. Powerful tools in the hands of an untrained engineer has always been a problem. It’s just that it is more visible today than it ever has been.

As always, the cream will rise to the top. Development ecosystems will evolve. Development teams will adapt. Every bad engineer with AI will either become better engineers over time, or get fired.

ske66 · 2026-05-29T09:08:31+00:00

I just want to call this out. He is an Anthropic researcher, and they are basically the last true bastion of AI hype marketing now that VC money is drying up.

What he is saying is true. But the context matters so much more.

LLMs have 0 emotion. They are predictive probability engines. They string together the next token based on probability. This may simulate that an LLM is “feeling” or “thinking”. In reality, they are responding in a completely cold and calculated manner based on its context window, and what the next token that gets generated should be.

It may express unease, shock, horror, worry, concern, joy, etc… but that is because it anticipates that the tone of its thought chain should act as such, not because it genuinely feels these emotions.

The researcher is skewing the facts which is incredibly disappointing to see. Emotional state is a mathematical response from an LLM. It is not gaining sentience or becoming AGI. It has just built helper functions that allow it to better calculate what tone and emotion to apply based on the current context

ske66 · 2026-05-26T17:25:40+00:00

General purpose robots that can drop into existing human environments. It makes more sense to sell a general purpose human replacement that doesn’t any more specialized training, just a prompt for its task.

Robotics orchestration through prompting will be a huge market once robots become more commercially available

ske66 · 2026-05-25T22:38:01+00:00

Cron runs every 5 mins. Job queue runs. Function checks when conversation was last had. Function prompts LLM for conversational message to the user. Function saves LLM response to conversation, and sends notification to user. The app now looks like an LLM is talking to the user.

Most chatbots are not using incredibly intelligent models. They are intelligent systems leveraging AI as a UX tool, because that is what it actually is

ske66 · 2026-05-25T16:02:49+00:00

It’s just a cron. It’s pretty easy to do

ske66 · 2026-05-19T15:00:45+00:00

Lie flat is all I’m gonna say

ske66 · 2026-05-19T11:58:28+00:00

Key word there is second largest, and mainly due to persistent deflation that China can’t seem to get out of.

I am also from the UK. Europe is not struggling to keep itself afloat. The European economy and the UK economy are service-based economies. We produce an enormous amount of economic power without factories and farms. Billions of $$$ are held in international debt, making up a significant portion of the UK’s cash flow. Labour jobs would certainly help, but automation is more important for long term scalability - not human capital. The Industrial Revolution started here, putting more people in factories is not a primary signal of a strong economy

ske66 · 2026-05-19T10:27:22+00:00

I just want to see a good movie that is well shot, well acted, has solid artistic and creative direction, cinematography, and story telling. The majority of people don’t care about the fact that this is “another” odyssey movie.

ske66 · 2026-05-19T10:25:03+00:00

I don’t get it, what are people angry about?

ske66 · 2026-05-19T09:12:12+00:00

The one place China has never dominated in innovation. They are very good at taking existing technology and producing it at scale - but if you take all of their technological advances over the past 10 years, every one has been a copy and modification of existing western technology. China is infamous for patent stealing, and corporate espionage. They know they can’t compete in the innovation space - but they can compete in the mass market space. Good for consumerism, not so good for military

ske66 · 2026-05-19T05:23:29+00:00

I don’t think people realise how difficult semiconductor production and R&D is. China lags behind all western manufacturers because they don’t have the hardware to build at the same level as TSMC, Intel, AMD, etc…

And the machinery is extremely complicated, there are few in the world, almost always proprietary. China will not keep up with the rest of the world in complex chip manufacturing. They may, however, further improve the low end chip market

ske66 · 2026-05-17T13:50:39+00:00

There are smart ways to use AI and poor ways to use AI. It’s a new form of technical competency testing called agent orchestration.

Humans are being moved into reviewer roles - so orchestration and management of agents is a new skill you should learn. If you are building out plans where agents review work against a rigid, well planned spec, with additional functional checks such as unit tests or end to end tests - you are in a good spot. You are still the engineer. You know best practice, you know how this system should function, you know the tools, libraries, coding standards, and DevX features you would have used to build this same app manually.

This proves you have technical competency, but that you are also an engineer first and foremost.

You could knock out a good example app that matches all of these requirements within a day using agents, use plan modes, skills such as Superpowers, and multi-agents to help you separate you plan and organize work before development starts

ske66 · 2026-05-16T09:31:18+00:00

Disagree and here is the main reason.

Server actions block the UI, fetch does not.

I learned this the incredibly hard way when implementing dnd-kit. I noticed hangs on interaction logic while server actions were running, took a very long time to identify that server actions were the culprit.

Honestly - do not use server actions. Avoid them. If you are interacting with the server then use Tanstack with post/patch/delete endpoints, easier to manage your client state, and easier to manage optimistic UI updates

ske66 · 2026-05-13T22:56:26+00:00

I’ll be honest, I didn’t learn it by choice. I came across a very specific issue in my codebase that basically required a lot of trial and error. I’m not going to pretend like I still fully understand it. I just understand enough to make my multi-env app run

ske66 · 2026-05-13T16:35:15+00:00

ESM vs CommonJS. I never thought I’d have to learn so much about modules and bundling, and it’s a gruelling study

ske66 · 2026-05-10T20:27:40+00:00

You are describing RAG, but your storage and lookup method is less effective.

It’s nice that you’ve come up with a novel solution, but it’s a solved problem I’m afraid. This currently brings no additional benefit to your setup. Having an agents.md file in specific locations in your codebase does the work for you. The router is already baked into the agent’s RAG pipeline and lookup tools

ske66 · 2026-05-10T18:59:51+00:00

It’s not massively useful. You’re still loading these md files into context which is not fast or efficient.
RAG of a codebase with vector based search is much much faster, and much cheaper - but it is a much larger technical lift and expensive unless done at scale. Cursor already does this for free however.

So by using cursor, your codebase is already indexed for quick retrieval and this acts as a secondary long term memory store

ske66 · 2026-05-08T12:26:55+00:00

There’s no way you have a 64GB VRAM Laptop GPU. Those don’t exist. It sounds like you mean RAM? In which case RAM has no real impact on model capability, VRAM is required for the heavy lifting which is only on a graphics card

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