शैडोइंग अभ्यास: 5 open source tools that replaced my $320/mo AI stack... - वीडियो के साथ अंग्रेजी बोलना सीखें

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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इस पाठ की शब्दावली और बोलने के सुझाव

यह B2 स्तर का स्पीकिंग पाठ वीडियो “5 open source tools that replaced my $320/mo AI stack..” पर आधारित है। सबसे ज़्यादा दोहराए गए शब्द ये हैं: model, tool, tier, code, private। इस वीडियो में शैडोइंग के लिए 63 वाक्य और 1161 शब्द हैं। बोला गया हिस्सा 5:22 लंबा है। वक्ता तेज़ बोलता है, लगभग 217 शब्द प्रति मिनट, इसलिए जुड़ी हुई और कमज़ोर ध्वनियाँ ज़्यादा मिलेंगी। केवल 80% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली कठिन है।

इस वीडियो की मुख्य शब्दावली

वीडियो के 15 सबसे कठिन शब्द, उच्चारण और अर्थ के साथ:

शब्द	उच्चारण	अर्थ
stack संज्ञा	/stæk/	धुआँरा
provider संज्ञा	/pɹəˈvaɪ.də(ɹ)/	प्रदाता, दाता
workflow संज्ञा	/ˈwɝkfloʊ/	कार्यप्रणाली, कार्यपद्धति
catalogue संज्ञा	/ˈkæt.əˌlɔɡ/	सूची, तालिका
subscription संज्ञा	/səbˈskɹɪpʃən/	सदस्यता
iceberg संज्ञा	/ˈaɪsbɝɡ/	हिमशैल, हिमखंड
inference संज्ञा	/ˈɪn.fə.ɹəns/	अनुमान, आकलन
vertex संज्ञा	/ˈvɝˌtɛks/	शीर्ष
benchmark संज्ञा	/ˈbɛn(t)ʃmɑːk/	मानक, मापदंड
builder संज्ञा	/ˈbɪl.dəɹ/	निर्माता, राजगीर
autonomous विशेषण	/ɔˈtɑnəməs/	स्वायत्त
verify क्रिया	/ˈvɛɹɪfaɪ/	परखना, जाँचना
frontier संज्ञा	/ˈfɹʌntɪə/	सीमा, सरहद
expose क्रिया	/ɪkˈspoʊz/	खोलना, उघाड़ना
interface संज्ञा	/ˈɪn(t)ɚˌfeɪs/	राब्ता, वास्ता

वीडियो में आने वाली फ़्रेज़ल वर्ब

शब्द	उच्चारण	अर्थ
wake up क्रिया	/ˌweɪk ˈʌp/	जागना

इस वीडियो का व्याकरण

वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:

संरचना	वीडियो में
Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है	I've cancelled · I've talked · we've talked
Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है	is declined · is cached · can be hosted
Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारी	consumption, which will · Headroom, which is · machine, which means

ध्यान देने योग्य उच्चारण

वक्ता 13 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे you're, I've, we'll। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।

“sh” और “zh” की ध्वनियाँ: subscription /səbˈskɹɪpʃən/, benchmark /ˈbɛn(t)ʃmɑːk/, cache /kæʃ/, compression /kəmˈpɹɛʃ.ən/, addiction /əˈdɪkˌʃən/
लंबे शब्द — बलाघात सही रखें: compatible /kəmˈpæt.ə.bəl/, evaporate /ɪˈvæp.ə.ɹeɪt/, reversible /ɹəˈvɜː(ɹ)sɪbəl/, proprietary /pɹəˈpɹaɪ.ə.tə.ɹi/, autonomous /ɔˈtɑnəməs/

हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:

/v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: provider /pɹəˈvaɪ.də(ɹ)/, workflow /ˈwɝkfloʊ/, retrieve /ɹɪˈtɹiːv/, evaporate /ɪˈvæp.ə.ɹeɪt/, reversible /ɹəˈvɜː(ɹ)sɪbəl/
शब्द की शुरुआत में s + व्यंजन — पहले “इ” न जोड़ें: stack /stæk/, swipe /swaɪp/, sponsor /ˈspɒn.səː/, slot /slɑt/
/æ/ — “ऐ” से ज़्यादा खुला: stack /stæk/, catalogue /ˈkæt.əˌlɔɡ/, compatible /kəmˈpæt.ə.bəl/, evaporate /ɪˈvæp.ə.ɹeɪt/, fallback /ˈfɔːl.bæk/

इस वीडियो से अभ्यास कैसे करें

पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर stack, provider, workflow जैसे शब्दों पर ध्यान दें।

शैडोइंग तकनीक क्या है?

शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।

शैडोइंग तकनीक: पूरी चरण-दर-चरण गाइड पढ़ें →

शैडोइंग अभ्यास: 5 open source tools that replaced my $320/mo AI stack... - वीडियो के साथ अंग्रेजी बोलना सीखें

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इस पाठ की शब्दावली और बोलने के सुझाव

इस वीडियो की मुख्य शब्दावली

वीडियो में आने वाली फ़्रेज़ल वर्ब

इस वीडियो का व्याकरण

ध्यान देने योग्य उच्चारण

इस वीडियो से अभ्यास कैसे करें

शैडोइंग तकनीक क्या है?