Shadowing Practice: The last real programmers are dying out... - Learn English Speaking with Video
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The programmer.
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Four years ago, science classified 10 known variants of this animal,
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and the taxonomy held up pretty well until an asteroid hit in 2023 and nearly wiped them off the Earth.
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Since then, the habitat has changed.
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9 out of 10 developers are now using AI to write their code, which means the one who doesn't is now endangered.
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Meanwhile, several new species have emerged recently, and in order to understand them,
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we need stereotypes, which experts still estimate are about 99 % accurate about 12 % of the time.
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In today's video, we'll look at the seven programmer stereotypes of 2026 to help you find out which one you've mutated into.
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First up, we have the non -technical vibe coder.
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This specimen doesn't know what a for loop is, and he doesn't really care.
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He describes himself as a founder
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and his entire tech stack is a chat window with a prompt that says it's still not working.
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He launches a SaaS on Tuesday, it gets hacked on Wednesday because the API keys are hard -coded on the front end,
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and on Thursday, he posts a thread about resilience.
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His natural predator is Edsger Dykstra, and his natural habitat is a screenshot of monthly recurring revenue
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that was also generated by AI because he doesn't know how to use dev tools.
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Evolutionary biologists have traced his lineage directly back to the boot camp programmer who normalized not understanding computer science fundamentals.
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Next, the closest living relative to the non -technical vibe coder is the prompt casino degenerate.
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This guy is technical, but only if it's easier than LeetCode Medium.
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He pulls the lever the agent spins, and about 60 % of the time,
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he gets a tasty piece of cheese he can make a PR out of.
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He spends $400 per month of his own money on coding agents
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because his company just set a $29 per month employee limit after agentic abuse.
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When the code is good, it's because he's a prompt engineer, and when it's bad, it's because Opus is nerfed.
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His family left him after
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he cashed out the kid's 529 college plans to give his agent full API access to his CalShe account,
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but that's okay because the latency with local voice models is low enough that it feels real.
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Next, the apex predator of the prompt casino degenerate, the swarm lord, who biologists classify as eusocial.
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This guy knows how to code and enjoy it, but he's gaslit himself into thinking he's never been more productive.
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He runs 12 agents in parallel from his phone, and his favorite thing to do while his agents work is tell you
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that he runs 12 agents in parallel from his phone.
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He hasn't looked at a line of code in years, but he has strong opinions about which model has the best taste.
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His natural predator is uptime, and his mating call is saying that writing software is a solved problem.
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The Swarmlord feasts on our next variant, the Slop Maintainer.
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This guy wrote a date formatting library in 2019 that now has 40 million weekly downloads and is critical web infrastructure.
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He gets hundreds of PRs per month that are each co -authored by Claude,
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and in October, he gets 10 ,000 more from junior devs in Bangalore, hoping to get a free t -shirt.
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He survives on the $95 he gets from his GitHub sponsors every month, while he watches the famous library maintainers make millions getting acquired by Shopify.
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His natural predator is a North Korean maintainer offering to help, and his mating call is threatening to archive the repo every other month.
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The maintainer never found out who sent those 10 ,000 PRs, but the biologists have, and they're calling him the unemployed junior.
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His whole life, he did everything right.
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Good grades, studied leak code, didn't kiss any girls, and he's been rejected by every AI screener that's come across his resume.
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He graduated in 2024, which was about six months after the last entry -level job on earth was filled.
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His GitHub contribution graph is a solid wall of green made entirely of readme typo fixes and Python projects from school.
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His natural habitat is a Discord server, and his natural predator is the non -technical vibe coder who can build everything he can,
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just with a marketing degree.
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His mating call is asking if anybody is hiring, and the guy who keeps saying no is our next specimen, the old jaded developer.
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This guy is in his mid -30s.
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He learned Grunt, then Gulp, then Webpack.
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He got excited for jQuery, then
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Angular, then React.
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He even stuck around for Hooks and Next .js, but now he's old, tired, and couldn't care less about benchmarks.
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He's not going to learn your harness, he's not going to read your system prompt, and he's not going to run 12 of anything.
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The full extent of his AI usage is hitting
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Tab and GitHub Copilot, which he's gotten for free since 2023 because he contributed to Gatsby back in the day.
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He doesn't know there's a chat window in his IDE, he misses 100 seconds videos, and when co -pilots suggest something wrong,
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he just deletes it by hand like a monk raking gravel.
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He's not anti -AI, he just has a parent -teacher conference at 4pm, and is coaching his third graders basketball at 7.
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But you know who is anti -AI?
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Our final specimen, the purist.
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This man is the best in us, he's noble, brave, handsome, and has 20 years of experience in a world that no longer exists.
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He hasn't had a job since MCP was released, which by the way he thinks is just Korba with worse security.
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When he did have a job, he wrote every line by hand and would gladly tell you the big O of any slop you whipped up.
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His favorite books are Introduction to Algorithms and The Pragmatic Programmer,
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and nowadays he can be found in his natural habitat on Hacker News talking about the craft of writing software.
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Biologists estimate that there are fewer than 10 ,000 of these left in the wild, and their numbers are dwindling by the day.
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But no matter which stereotype you identify as, you need to check out Serp API, the sponsor of today's video.
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If you're building an AI app that needs live data, like prices or store hours,
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your LLM will start spitting out confidently wrong answers because of its stale -ass training data.
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The Serp API lets your agent pull real -time results from Google, Amazon, Maps, and over 100 other engines.
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It's all sourced from public pages and their own search index, so your agents are always working with data that's already public.
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And they just launched
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Extract API, so when your agent finds a page it needs,
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it can grab the whole thing as structured JSON or as clean markdown that won't nuke your context window.
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You can add it to Cloud Code, Cursor, and Codex through their MCP server, and SERP API is already used by companies like NVIDIA and Perplexity,
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because even AI search engines need a real search engine to try it out for free with this QR code
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or at the link below.
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Thanks for watching and I will see you in the next one.
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Vocabulary and speaking notes for this lesson
This speaking lesson is built on the video “The last real programmers are dying out..”. The speaker keeps coming back to these words: agent, code, natural, Api, month. This video has 78 sentences and 1199 words to shadow. The speech runs for 5:55. The speaker talks fast, about 203 words per minute, so expect linked and reduced sounds. Only 77% of the words are among the 3,000 most common in English, so the vocabulary is demanding.
Key vocabulary in this video
15 words from the video worth learning, with pronunciation and meaning:
| Word | Pronunciation | Meaning |
|---|---|---|
| prompt verb | /pɹɑmpt/ | To lead (someone) toward what they should say or do. |
| predator noun | /ˈpɹɛd.ə.tɚ/ | Any animal or other organism that hunts and kills other nonplant organisms (their prey), primarily for food. |
| habitat noun | /ˈhæb.ɪ.tæt/ | Conditions suitable for an organism or population of organisms to live. |
| programmer noun | /ˈpɹoʊɡɹæmɚ/ | One who writes computer programs. |
| vibe noun | /vaɪb/ | An atmosphere or aura felt to belong to a person, place or thing. |
| specimen noun | /ˈspɛsɪmɪn/ | An individual instance that represents a class; an example. |
| server noun | /ˈsɝvɚ/ | A program that provides services to other programs or devices, either in the same computer or over a computer network. |
| estimate noun | /ˈɛs.tɪ.mət/ | A rough calculation or assessment of the value, size, or cost of something. |
| parallel adjective | /ˈpæ.ɹəˌlɛl/ | Equally distant from one another at all points. |
| developer noun | /dɪˈvɛləpɚ/ | A person or entity engaged in the creation or improvement of certain classes of products. |
| casino noun | /kəˈsiːnəʊ/ | A public building or room for gambling. |
| sponsor noun | /ˈspɒn.səː/ | A person or organization with some sort of responsibility for another person or organization, especially where the responsibility has a religious, legal, or… |
| variant noun | /ˈvæɹi.ənt/ | Something that is slightly different from a type or norm. |
| meanwhile adverb | /ˈmiːnwaɪl/ | During the time that something is happening, often specifically in a different place. |
| relative noun | /ˈɹɛl.ə.tɪv/ | Someone connected by blood, marriage, or adoption; someone in the same family. |
Phrasal verbs you will hear
| Word | Meaning |
|---|---|
| find out verb | To discover, as by asking or investigating. |
| cash out verb | To reconcile at the end of a shift; to compare receipts of items sold to records of credit card, check and cash placed into the drawer, verifying that correct… |
| check out verb | To record the departure or withdrawal of someone or something (such as guests, employees, books, etc.). |
| come across verb | To change sides; to cross over to work for the opposition. |
| hold up verb | To wait or delay. |
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 | has changed · have emerged · you've mutated |
| Passive voice be + past participle — the focus is on what happens, not who does it | is now endangered · was also generated · is nerfed |
| Relative clauses who / which + clause — extra information about a person or thing | code, which means · guy who keeps |
Pronunciation to watch
The speaker uses 14 contractions and reduced forms, such as doesn't, hasn't, couldn't. Say them the short way, as you hear them.
- The “th” sounds: thread /ˈθɹɛd/, threaten /ˈθɹɛt.n̩/
- The “sh” and “zh” sounds: contribution /ˌkɑntɹɪˈbjuʃən/, evolutionary /ˌiː.vəˈluː.ʃən.ɛɹ.i/, screenshot /ˈskriːn.ʃɑt/, benchmark /ˈbɛn(t)ʃmɑːk/
- Long words — get the stress right: developer /dɪˈvɛləpɚ/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, contribution /ˌkɑntɹɪˈbjuʃən/, fundamental /ˌfʌn.dəˈmɛn.təl/, evolutionary /ˌiː.vəˈluː.ʃən.ɛɹ.i/
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 prompt, predator, habitat.
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.