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Tuesday, August 19, 2025

An AI ‘Nerd Knob’ Each Community Engineer Ought to Know


Alright, my mates, I’m again with one other publish primarily based on my learnings and exploration of AI and the way it’ll match into our work as community engineers. In in the present day’s publish, I need to share the primary (of what’s going to probably be many) “nerd knobs” that I believe all of us ought to pay attention to and the way they’ll influence our use of AI and AI instruments. I can already sense the joy within the room. In spite of everything, there’s not a lot a community engineer likes greater than tweaking a nerd knob within the community to fine-tune efficiency. And that’s precisely what we’ll be doing right here. Advantageous-tuning our AI instruments to assist us be more practical.

First up, the requisite disclaimer or two.

  1. There are SO MANY nerd knobs in AI. (Shocker, I do know.) So, should you all like this sort of weblog publish, I’d be blissful to return in different posts the place we have a look at different “knobs” and settings in AI and the way they work. Properly, I’d be blissful to return as soon as I perceive them, at the least. 🙂
  2. Altering any of the settings in your AI instruments can have dramatic results on outcomes. This consists of growing the useful resource consumption of the AI mannequin, in addition to growing hallucinations and reducing the accuracy of the data that comes again out of your prompts. Contemplate yourselves warned. As with all issues AI, go forth and discover and experiment. However accomplish that in a protected, lab atmosphere.

For in the present day’s experiment, I’m as soon as once more utilizing LMStudio working domestically on my laptop computer somewhat than a public or cloud-hosted AI mannequin. For extra particulars on why I like LMStudio, try my final weblog, Making a NetAI Playground for Agentic AI Experimentation.

Sufficient of the setup, let’s get into it!

The influence of working reminiscence measurement, a.ok.a. “context”

Let me set a scene for you.

You’re in the midst of troubleshooting a community challenge. Somebody reported, or observed, instability at some extent in your community, and also you’ve been assigned the joyful process of attending to the underside of it. You captured some logs and related debug info, and the time has come to undergo all of it to determine what it means. However you’ve additionally been utilizing AI instruments to be extra productive, 10x your work, impress your boss, you recognize all of the issues which can be happening proper now.

So, you determine to see if AI can assist you’re employed by way of the info quicker and get to the basis of the problem.

You hearth up your native AI assistant. (Sure, native—as a result of who is aware of what’s within the debug messages? Finest to maintain all of it protected in your laptop computer.)

You inform it what you’re as much as, and paste within the log messages.

Asking an AI assistant to help debug a network issue.Asking an AI assistant to help debug a network issue.
Asking AI to help with troubleshooting

After getting 120 or so strains of logs into the chat, you hit enter, kick up your toes, attain to your Arnold Palmer for a refreshing drink, and await the AI magic to occur. However earlier than you possibly can take a sip of that iced tea and lemonade goodness, you see this has instantly popped up on the display:

AI Failure! Context length issueAI Failure! Context length issue
AI Failure! “The AI has nothing to say”

Oh my.

“The AI has nothing to say.”!?! How may that be?

Did you discover a query so tough that AI can’t deal with it?

No, that’s not the issue. Take a look at the useful error message that LMStudio has kicked again:

“Attempting to maintain the primary 4994 tokens when context the overflows. Nevertheless, the mannequin is loaded with context size of solely 4096 tokens, which isn’t sufficient. Attempt to load the mannequin with a bigger context size, or present shorter enter.”

And we’ve gotten to the basis of this completely scripted storyline and demonstration. Each AI instrument on the market has a restrict to how a lot “working reminiscence” it has. The technical time period for this working reminiscence is “context size.” In the event you attempt to ship extra information to an AI instrument than can match into the context size, you’ll hit this error, or one thing prefer it.

The error message signifies that the mannequin was “loaded with context size of solely 4096 tokens.” What’s a “token,” you surprise? Answering that may very well be a subject of a completely completely different weblog publish, however for now, simply know that “tokens” are the unit of measurement for the context size. And the very first thing that’s performed whenever you ship a immediate to an AI instrument is that the immediate is transformed into “tokens”.

So what can we do? Properly, the message offers us two attainable choices: we will enhance the context size of the mannequin, or we will present shorter enter. Typically it isn’t a giant deal to offer shorter enter. However different instances, like after we are coping with giant log recordsdata, that choice isn’t sensible—all the information is vital.

Time to show the knob!

It’s that first choice, to load the mannequin with a bigger context size, that’s our nerd knob. Let’s flip it.

From inside LMStudio, head over to “My Fashions” and click on to open up the configuration settings interface for the mannequin.

Accessing Model SettingsAccessing Model Settings
Accessing Mannequin Settings

You’ll get an opportunity to view all of the knobs that AI fashions have. And as I discussed, there are quite a lot of them.

Default configuration settingsDefault configuration settings
Default configuration settings

However the one we care about proper now’s the Context Size. We are able to see that the default size for this mannequin is 4096 tokens. But it surely helps as much as 8192 tokens. Let’s max it out!

Maxing out the Context LengthMaxing out the Context Length
Maxing out the Context Size

LMStudio gives a useful warning and possible cause for why the mannequin doesn’t default to the max. The context size takes reminiscence and assets. And elevating it to “a excessive worth” can influence efficiency and utilization. So if this mannequin had a max size of 40,960 tokens (the Qwen3 mannequin I take advantage of generally has that prime of a max), you won’t need to simply max it out immediately. As an alternative, enhance it by a bit of at a time to search out the candy spot: a context size large enough for the job, however not outsized.

As community engineers, we’re used to fine-tuning knobs for timers, body sizes, and so many different issues. That is proper up our alley!

When you’ve up to date your context size, you’ll have to “Eject” and “Reload” the mannequin for the setting to take impact. However as soon as that’s performed, it’s time to reap the benefits of the change we’ve made!

The extra context length allows the AI to analyze the dataThe extra context length allows the AI to analyze the data
AI totally analyzes the logs

And have a look at that, with the bigger context window, the AI assistant was in a position to undergo the logs and provides us a pleasant write-up about what they present.

I significantly just like the shade it threw my manner: “…contemplate searching for help from … a professional community engineer.” Properly performed, AI. Properly performed.

However bruised ego apart, we will proceed the AI assisted troubleshooting with one thing like this.

AI helps put a timeline of the problem togetherAI helps put a timeline of the problem together
The AI Assistant places a timeline collectively

And we’re off to the races. We’ve been in a position to leverage our AI assistant to:

  1. Course of a major quantity of log and debug information to establish attainable points
  2. Develop a timeline of the issue (that will probably be tremendous helpful within the assist desk ticket and root trigger evaluation paperwork)
  3. Establish some subsequent steps we will do in our troubleshooting efforts.

All tales should finish…

And so you’ve it, our first AI Nerd Knob—Context Size. Let’s evaluate what we discovered:

  1. AI fashions have a “working reminiscence” that’s known as “context size.”
  2. Context Size is measured in “tokens.”
  3. Oftentimes instances an AI mannequin will assist a better context size than the default setting.
  4. Rising the context size would require extra assets, so make modifications slowly, don’t simply max it out utterly.

Now, relying on what AI instrument you’re utilizing, you might NOT have the ability to alter the context size. In the event you’re utilizing a public AI like ChatGPT, Gemini, or Claude, the context size will depend upon the subscription and fashions you’ve entry to. Nevertheless, there most positively IS a context size that may issue into how a lot “working reminiscence” the AI instrument has. And being conscious of that truth, and its influence on how you should use AI, is vital. Even when the knob in query is behind a lock and key. 🙂

In the event you loved this look beneath the hood of AI and wish to study extra choices, please let me know within the feedback: Do you’ve a favourite “knob” you want to show? Share it with all of us. Till subsequent time!

PS… In the event you’d wish to be taught extra about utilizing LMStudio, my buddy Jason Belk put a free tutorial collectively known as Run Your Personal LLM Regionally For Free and with Ease that may get you began in a short time. Test it out!

 

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Learn subsequent:

Making a NetAI Playground for Agentic AI Experimentation

Take an AI Break and Let the Agent Heal the Community

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