Shadowing Practice: 5 open source tools that replaced my $320/mo AI stack... - Learn English Speaking with Video

Recently, I did some math, and it made me realize how broken the world is.

A cursor, $20.

Claude Max, $100.

GPT Pro, another $100.

Gemini Ultra, another $100.

Not to mention 11 Labs, DeepSeq, and all the API keys I signed up for two years ago and forgot about.

My AI addiction got so expensive that I had to quit alcohol and Zin.

And I'm not the only one, because alcohol sales in the United States are currently sitting at historic lows.

And Big AI is the one to blame for this.

But that was my wake-up call, and since then, I've cancelled all these subscriptions, and now self-host the ultimate AI stack for developers that's not only cheaper, but far more productive.

In today's video, we'll look at a bunch of free and open-source projects you can run on your own server.

We'll make them work together, while still having the option to tap into the intelligence of big models like Claude and GPT Sol.

It is September 7th, 2026, and you're watching The Code Report.

The first tool we need to talk about is OLAMA, because every AI stack first needs a model.

For most people, this means sending your proprietary code to a trillion dollar corporation and trusting them to keep it totally safe, or you can use OLAMA and do everything locally.

I've talked about this tool many other times on the channel, and essentially it's like Docker for large language models.

It gives you a simple command line interface and API for downloading and running models on your own machine.

This is great if you want to try out the latest Chinese models or any other open weight models, and what's even better is that all your prompts stay private and the inference cost is zero,

which means the model continues to work even after your credit card is declined.

The big problem, though, is that you probably don't own the hardware to run anything close to state-of-the-art.

The small models will run almost anywhere, but running a frontier-sized model would require a small data center, and that's a big problem if you're a Vibe engineer who needs to write top-tier slot.

Luckily, there's a self-hostable solution to this called 9Router, which is an AI tool that sits between your AI tools and dozens of different model providers through one local endpoint.

Instead of juggling nine different API keys, 9Router provides one door with an OpenAI compatible proxy that allows you to point everything through localhost.

But the thing that's really cool about 9Router is fallback tiers.

On tier one, you might have an existing subscription like Claude Max that you already pay for.

Then on tier two, you might have a cheap pay-per-token OpenAI model as a backup.

Then tier three has all of free providers like Chinese models, vertex trial credits, and so on.

That means if you max out Claude Max, it'll automatically roll over to the next tier without you having to do anything.

But in addition to that, 9Router also tracks usage and will compress your tool output to reduce token consumption, which will ultimately save you a bunch of money.

But if you're still eating billions of tokens per day, then you need to know about Headroom, which is a context compression layer for AI agents.

You ask AI to center a div, and to do that, it reads 50,000 lines of your package lock JSON file, then it evaporates an Olympic-sized swimming pool worth of water,

just to realize it needs to install Tailwind CSS.

Headroom sits between your application and the model provider,

and compresses everything from tool outputs to log files and any other useless chunks before it actually goes to the model, which would be billable input tokens.

And one clever design feature of this tool is that it's reversible.

The compressed content that ships to the model is cached on your local machine, which means if the model ever needs it, it can always retrieve it.

This sounds awesome, but at this point, you might be wondering, where do I deploy all this stuff?

Well, the answer, of course, is Hostinger, the sponsor of today's video.

Not only is it one of the most affordable places to host your own virtual private server, but they also have an entire Docker catalog built into the panel,

which means every single open source project I talk about in this video can be hosted there with a single click.

In fact, you could have all these tools running and working together on the same VPS.

Head over to hostinger.com slash fireship and use my coupon code to save a bunch of money spinning up your own VPS.

Once you have that done, the next tool you'll want to install there is Diffy.

Everything we've talked about so far is infrastructure, but now it's time to build an actual app that'll make us rich.

Instead of trying to engineer everything through prompts, Diffy is a visual builder that allows us to drag nodes on a canvas.

This has been a game changer for Horse Tinder and its AI matchmaking feature.

The app will send Diffy each horse's profile information, then a visual workflow retrieves compatible horses from the database, and uses a large language model to explain each match.

Like Thunder and Butternuts are a 94% match because they both enjoy trail rides and biting children.

Then the entire workflow is exposed as an API, so the front-end application can just call it whenever a horse swipes right.

Amazing, but building apps as a human became outdated in Q2 2026 after the release of open hands

which is an open source tool

that allows you to fire yourself this tool is a top performing autonomous coding agent on swebench verified

which is the benchmark where models fix real github issues instead of trying to build

and fix things just open up github issues

and let open hands do all the work essentially it gives

you a command center where you can self-host an army of ai agents

that are always on and working in the background and because Because it's running on your own virtual private server, you have the option to run it with OpenAI or Anthropic models,

or use the local LLMs that you installed earlier with OLAMA.

And now at this point, we have our own private AI stack that could build any type of software you can imagine.

But this is just the tip of the iceberg, and there's tons of other open source applications in Hostinger's Docker catalog that you can install with zero hassle.

Check out the link below

and use coupon code Fireship to get your own virtual private server on Hostinger up and running right now.

This has been the Code Report, thanks for watching, and I will see you in the next one.

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Vocabulary and speaking notes for this lesson

This B2 speaking lesson is built on the video “5 open source tools that replaced my $320/mo AI stack..”. The speaker keeps coming back to these words: model, tool, tier, code, private. This video has 63 sentences and 1161 words to shadow. The speech runs for 5:22. The speaker talks fast, about 217 words per minute, so expect linked and reduced sounds. Only 80% of the words are among the 3,000 most common in English, so the vocabulary is demanding.

Key vocabulary in this video

The 15 most advanced words in the video, with pronunciation and meaning:

Word	Pronunciation	Meaning
tier noun	/ˈtɪɚ/	A row or range, especially one at a higher or lower level than another.
token noun	/ˈtoʊkən/	Something serving as an expression of something else.
compress verb	/ˈkɑmpɹɛs/	To make smaller; to press or squeeze together, or to make something occupy a smaller space or volume.
stack noun	/stæk/	A large pile of hay, grain, straw, or the like, larger at the bottom than the top, sometimes covered with thatch.
provider noun	/pɹəˈvaɪ.də(ɹ)/	One who, or that which, provides a service, commodity, or the means for subsistence.
install verb	/ɪnˈstɔl/	To connect, set up or prepare something for use
hosting noun	/ˈhoʊstɪŋ/	Running and maintaining a computer system on someone's behalf.
workflow noun	/ˈwɝkfloʊ/	The flowrate at which a flow of work takes place.
retrieve verb	/ɹɪˈtɹiːv/	To regain or get back something.
prompt verb	/pɹɑmpt/	To lead (someone) toward what they should say or do.
coupon noun	/ˈkuːˌpɑn/	A section of a ticket, showing the holder to be entitled to some specified accommodation or service, as to a passage over a designated line of travel, a…
catalogue noun	/ˈkæt.əˌlɔɡ/	A systematic list of books, names, pictures, etc.
compatible adjective	/kəmˈpæt.ə.bəl/	Capable of working together without conflict.
subscription noun	/səbˈskɹɪpʃən/	Access to a resource for a period of time, generally for payment.
billable adjective	/ˈbɪləbəl/	Capable of being billed for.

Phrasal verbs you will hear

Word	Pronunciation	Meaning
check out verb		To record the departure or withdrawal of someone or something (such as guests, employees, books, etc.).
open up verb		To open.
try out verb		To test (something) to see how it works or whether it is suitable.
wake up verb	/ˌweɪk ˈʌp/	To stop sleeping; to awake.
work together verb		To be coworkers with someone; to share a workspace with someone.

Grammar in this video

The structures the speaker uses most, with the exact words from the video:

Structure	In the video
Present perfect have/has + past participle — a past action that still matters now	I've cancelled · I've talked · we've talked
Passive voice be + past participle — the focus is on what happens, not who does it	is declined · is cached · can be hosted
Relative clauses who / which + clause — extra information about a person or thing	consumption, which will · Headroom, which is · machine, which means

Pronunciation to watch

The speaker uses 13 contractions and reduced forms, such as you're, I've, we'll. Say them the short way, as you hear them.

The “sh” and “zh” sounds: subscription /səbˈskɹɪpʃən/, benchmark /ˈbɛn(t)ʃmɑːk/, cache /kæʃ/, compression /kəmˈpɹɛʃ.ən/, addiction /əˈdɪkˌʃən/
Long words — get the stress right: compatible /kəmˈpæt.ə.bəl/, evaporate /ɪˈvæp.ə.ɹeɪt/, reversible /ɹəˈvɜː(ɹ)sɪbəl/, proprietary /pɹəˈpɹaɪ.ə.tə.ɹi/, autonomous /ɔˈtɑnəməs/

How to practise with this video

Listen to the whole video once without speaking and note the words you do not know.
Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
Record yourself and compare with the original, paying attention to words like tier, token, compress.

What is the Shadowing Technique?

Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.

Shadowing technique: read the full step-by-step guide →

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Vocabulary and speaking notes for this lesson

Key vocabulary in this video

Phrasal verbs you will hear

Grammar in this video

Pronunciation to watch

How to practise with this video

What is the Shadowing Technique?