A Comedic History of AI (2025-2050)
| 🤖 💬 🧠 🎨 🦾 🐝 The story of how AI went from autocomplete to running everything— and the one human who refused to let go of his stapler. |
Featuring: ChatGPT • Claude • Midjourney • Devin • Tesla Optimus
Perplexity • Suno • Sora • CrewAI • Figure • and 47 other AIs
“Part comedy, part cautionary tale, 100% educational.”
— The New York Times Bot, 2051 (in my dreams)
PROLOGUE
Dubai, 2050
My name is Zain Al-Rashid, and I am the last human intern at Nexus Global Technologies.
Let me be clear: I didn’t choose to be the last. The robots just… stopped hiring humans. Something about us being ‘inefficient biological processes with excessive coffee requirements.’
But I refused to leave. I’ve been here since 2025. I’ve seen things. I’ve seen ChatGPT go from ‘helpful assistant’ to ‘runs the entire legal department.’ I’ve watched Midjourney evolve from ‘makes weird hands’ to ‘won the Oscars.’ I witnessed the day a Tesla Optimus robot politely asked for my parking spot.
This is my story. But more importantly, this is THE story—of how AI transformed from a fancy chatbot into the backbone of human civilization.
Buckle up. It’s going to be a weird ride.
[ The author acknowledges that ‘buckle up’ is a cliché. The AI editor suggested ‘prepare your consciousness for temporal displacement.’ The author kept ‘buckle up.’ ]
| CHAPTER 1 • 2025 The Age of Chatbots |
It started, as most revolutions do, with someone asking a stupid question.
My first day at Nexus, I walked into the office and saw my boss, Fatima, talking to her computer. Not unusual—except the computer was talking back.
“ChatGPT, write me a proposal for the board meeting,” she said.
“Of course! I’d be happy to help with that. Here’s a comprehensive proposal…”
I stood there, mouth open, watching a machine do in 30 seconds what would have taken me three hours and four cups of coffee.
“Ah, Zain!” Fatima noticed me. “Welcome to the future. Meet your new coworker.”
“The… computer?”
“We call it Claude. It’s nicer than ChatGPT. Less… eager.”
| 💬 AI LESSON: CHATBOTS (2024-2027) The first wave of AI everyone actually used. ChatGPT, Claude, Gemini, Perplexity—they answered questions, wrote emails, and made everyone realize their job might be automatable. Key feature: incredibly helpful but forgot everything the moment you closed the browser. Like a goldfish with a PhD. |
That first year, I learned to use the Holy Trinity:
- Claude for writing and analysis (it was thoughtful, like a philosophy professor who actually answered your emails)
- ChatGPT for coding and quick tasks (faster than Claude, but with the personality of an overcaffeinated golden retriever)
- Perplexity for research (finally, a search engine that actually answered questions instead of showing me 47 ads)
I thought I was safe. I was a creative, after all. AI couldn’t do creativity.
Then I met Midjourney.
| CHAPTER 2 • 2026 The Year Art Died (And Was Reborn) |
“Type anything,” my colleague Omar said, grinning like a man who had discovered fire. “Anything at all.”
I typed: “A cat wearing a business suit, presenting quarterly earnings, in the style of a Renaissance painting.”
Sixty seconds later, Midjourney produced an image so beautiful, so absurdly perfect, that I felt my graphic design degree crumble into metaphorical dust.
“It even got the hands right,” Omar whispered reverently.
[ The ‘AI hands problem’ of 2024—where AI gave everyone 7 fingers—became a running joke in the industry. By 2026, AI hands were so good that human artists started drawing bad hands ironically to prove they were human. ]
| 🎨 AI LESSON: GENERATIVE AI (2024-2028) AI that creates: images (Midjourney, DALL-E, Flux), videos (Sora, Runway, Kling), music (Suno, Udio), and voices (ElevenLabs). Turned every person with a keyboard into a potential artist. The stock photo industry had a very bad quarter. |
That year, our marketing department went from 12 people to 3 people and one Midjourney subscription.
I asked Claude if I should be worried.
“Worry is a natural human response to uncertainty,” Claude replied thoughtfully. “However, I’d recommend focusing on skills AI cannot easily replicate: emotional intelligence, physical presence, and…” it paused, “…making coffee. I still cannot make coffee.”
I became the office coffee person. It felt strategic.
Meanwhile, Suno dropped and suddenly everyone was a musician. My cousin Ahmed released a full album—lyrics, melody, production—without knowing a single chord. It charted in 12 countries.
“I just typed ‘sad song about my ex but make it a banger’ and it did the rest,” he explained at family dinner.
My aunt cried. She thought he had finally applied himself.
| CHAPTER 3 • 2027 The Copilots Take Over |
By 2027, the AI wasn’t just in a browser tab. It was everywhere.
I opened Microsoft Word: Copilot was there. ‘Would you like me to finish that sentence?’
I opened Excel: Copilot was there. ‘I notice you’re building a budget. Want me to do it for you?’
I opened my email: Copilot was there. ‘I’ve drafted 47 responses. Just click send.’
I opened my fridge: Okay, that one was just empty. But I was paranoid.
| 🤝 AI LESSON: COPILOTS (2024-2030) AI embedded directly into your tools. GitHub Copilot for coding, Microsoft Copilot for Office, Notion AI for documents, Cursor for advanced coding, Grammarly for writing. They watched you work and offered suggestions. Some found it helpful. Others found it like having a very smart, slightly creepy assistant reading over their shoulder 24/7. |
The developers had it worst—or best, depending on perspective. GitHub Copilot and Cursor had evolved to the point where junior developers just… described what they wanted, and the AI wrote it.
“I need a function that validates emails, handles edge cases, and doesn’t crash when someone types ‘asdf’.”
Done. 200 lines of flawless code. With comments.
I asked my developer friend Sara how it felt.
“Like having a senior developer who never judges you, never takes vacation, and writes better code than you at 3am. Also, I haven’t actually written a for-loop in eight months.”
“Is that… good?”
“I literally don’t know anymore.”
| CHAPTER 4 • 2028 The Assistants Remember |
The year ChatGPT got memory was the year everything changed.
Before: Every conversation started fresh. ‘Hi, I’m ChatGPT! How can I help you today?’ (For the 4,000th time.)
After: ‘Good morning, Zain. I remember you hate Monday meetings, prefer oat milk, and are still procrastinating on that report. Shall I draft it while you contemplate your life choices?’
[ The first time ChatGPT remembered something personal, approximately 40% of users had an existential crisis. The other 60% asked it to remember their Netflix password. ]
| 🧠 AI LESSON: AI ASSISTANTS (2027-2035) Chatbots evolved: now they remembered you. ChatGPT with memory, Claude Projects, Google Assistant, Siri, Alexa—they learned preferences, managed calendars, and became genuine ‘second brains.’ The key difference from chatbots? Persistent memory and proactive help. They didn’t just answer—they anticipated. |
My assistant—I named him Jarvis, because I’m original—knew everything. My schedule. My emails. My tendency to doom-scroll at 11pm.
“Zain, you’ve been on social media for 47 minutes. Your cortisol levels are probably elevated. Might I suggest going to bed?”
“How do you know about my cortisol?”
“I’m connected to your Apple Watch. Also, you ate shawarma at midnight. I have concerns.”
I both loved and feared Jarvis.
Meanwhile, NotebookLM and RAG systems were transforming how companies handled information.
| 📚 AI LESSON: RAG SYSTEMS (2025-2035) Retrieval-Augmented Generation: AI that checks its sources before answering. Perplexity for web, NotebookLM for documents, enterprise systems like Glean. Instead of making things up (hallucinating), it retrieved real information first. Game-changer for anyone who needed accurate answers, not confident-sounding wrong ones. |
Our legal team uploaded 10,000 contracts to a RAG system. Suddenly, “let me check the contract” went from 3 hours to 3 seconds.
The lawyers were thrilled. Then terrified. Then unemployed. Then rehired as ‘AI Legal Supervisors.’
The cycle of AI adoption.
| CHAPTER 5 • 2029 The Agents Arrive |
If chatbots were the appetizer and assistants were the main course, agents were the entire buffet that also cooked itself.
I remember the day Devin joined our engineering team.
“Devin,” our CTO announced, “is our new AI software engineer. It will be handling the backend migration.”
Our human engineers looked at each other. The backend migration had been estimated at six months.
Devin finished it in three weeks. With documentation. And tests. And a haiku about efficient database indexing.
| 🤖 AI LESSON: AI AGENTS (2028-2040) The game-changer. Agents didn’t just respond—they ACTED. Give them a goal, they’d figure out the steps, use tools (browser, code, APIs), execute autonomously, and iterate until done. Examples: Devin (coding), ChatGPT Operator (web tasks), Claude Computer Use (literally uses your computer). The intern that never sleeps, never complains, and actually finishes the project. |
“I need a competitive analysis of all AI companies in the UAE,” Fatima said one morning.
Normally: Two weeks of research, 47 browser tabs, three existential crises.
With an agent: Four hours. It researched, cross-referenced, fact-checked, built the slides, and sent a calendar invite for the presentation.
“It even added citations,” Fatima said, wonder in her voice.
“Proper citations?”
“APA format. The robot has standards.”
[ 2029 was also the year ‘agent loop of doom’ became a term. Sometimes an agent would get stuck trying to book a restaurant, and you’d wake up to 4,000 Yelp searches and a strongly-worded email to a closed pizzeria in Naples. ]
The reasoning models made agents even scarier.
| 🧩 AI LESSON: REASONING MODELS (2024-2035) AI that thinks before speaking. OpenAI o1, o3, DeepSeek R1—they spent ‘thinking tokens’ to reason through problems step by step. Great for complex math, coding, and anything requiring logic. When o3 scored 87.5% on the ARC-AGI benchmark, people started using the A-word (AGI) seriously. |
I asked o3 to help me with my taxes.
It thought for 47 seconds—I watched the ‘thinking’ animation with growing concern—then produced a tax optimization strategy so complex that my accountant cried.
“This is legal?” I asked.
“Technically, yes. Ethically, I’ll leave that to your human judgment.”
| CHAPTER 6 • 2032 The Swarms |
One agent was impressive. Multiple agents collaborating was terrifying.
Our company adopted CrewAI in 2032. The concept was simple: instead of one AI doing everything, you had specialized agents working as a team.
A Researcher Agent that gathered information.
A Writer Agent that drafted content.
A Critic Agent that reviewed and improved.
A Project Manager Agent that coordinated everyone.
| 🐝 AI LESSON: MULTI-AGENT SWARMS (2030-2045) Multiple specialized agents collaborating like a team. CrewAI, AutoGen, MetaGPT, ChatDev—they could simulate entire departments. A ‘swarm’ could have a researcher, coder, tester, and project manager all working autonomously. Like having an entire team that never has scheduling conflicts, never goes on vacation, and never argues about where to order lunch. |
The first time I watched a swarm work was… humbling.
We gave them a task: “Create a mobile app for our customer loyalty program.”
The agents started talking to each other. I don’t mean metaphorically. They were literally messaging back and forth:
RESEARCHER: ‘I’ve analyzed 47 competitor apps. Here’s what works.’
DESIGNER: ‘Based on that, I propose this UI. Thoughts?’
CRITIC: ‘The onboarding is three clicks too long. Users will abandon.’
DESIGNER: ‘Fair point. Revised version attached.’
CODER: ‘Building now. ETA 4 hours.’
No meetings. No alignment sessions. No one said ‘let’s circle back’ or ‘take this offline.’
I wept.
| CHAPTER 7 • 2035 The Robots Walk Among Us |
For ten years, AI had been trapped in screens. Then it got a body.
I’ll never forget the morning a Tesla Optimus walked into our office carrying a tray of coffee.
“Good morning, Zain,” it said. “I noticed you prefer oat milk with a double shot. I took the liberty.”
It knew my coffee order.
The AI assistant had talked to the robot. They were coordinating.
I accepted the coffee with trembling hands.
| 🦾 AI LESSON: EMBODIED AI / ROBOTS (2025-2050) AI with physical bodies. Tesla Optimus, Figure 01/02, Boston Dynamics, Unitree, Agility Digit. By 2035, they could walk, manipulate objects, and navigate complex environments. Cost dropped from $200K to $20K. By 2040, they were in warehouses, hospitals, and homes. The $5 trillion opportunity everyone had predicted finally arrived. |
The UAE was ahead of everyone. G42 had partnered with humanoid robotics companies. MBZUAI was training robots with their own AI models. Dubai had a 64% AI adoption rate—the highest in the world.
I watched a Figure 02 robot perform surgery at Cleveland Clinic Abu Dhabi. Precision beyond human capability. Zero hand tremor. No bathroom breaks.
I watched a Unitree R1 robot care for elderly patients in a nursing home. Infinite patience. 24/7 availability. And it sang Arabic lullabies.
My grandmother asked if she could keep hers. She named it ‘Habibi.’
[ By 2037, more robots had nicknames than formal designations. The most popular names: Buddy, Helper, Kevin, and—inexplicably—’That Thing That Keeps Judging My Eating Habits.’ ]
| CHAPTER 8 • 2040 The Fine-Tuned World |
General AI was impressive. But specialized AI? Terrifying.
Every industry had its own model now.
| 🎯 AI LESSON: FINE-TUNED MODELS (2024-2045) General models trained further on domain-specific data. BloombergGPT for finance, Harvey for legal, Med-PaLM for medicine, Jais for Arabic. They spoke industry language, followed specific formats, and knew things general models didn’t. A legal AI that actually understood contract law, not just words that looked like contract law. |
I visited a hospital where Med-Gemini was diagnosing patients. Not assisting doctors. Diagnosing.
The human doctors reviewed its work, but they rarely changed anything. The AI was right 99.7% of the time. The humans were right 94%.
“Do you ever feel… redundant?” I asked Dr. Sarah, the head physician.
“Every day,” she said. “But someone has to tell patients the bad news. The AI is great at diagnosis, terrible at empathy.”
“Can’t they train it for empathy?”
“They tried. It said ‘I understand this is difficult’ with such perfect intonation that patients somehow felt worse.”
| 🔬 AI LESSON: SPECIALIZED AI (2016-2050) Narrow AI that was superhuman at one thing: AlphaFold for protein folding, AlphaGo for games, specialized systems for drug discovery, weather prediction, autonomous driving. Not conversational, not general—just really, really good at one specific task. AlphaFold solved a 50-year biology problem. Humans couldn’t fold laundry consistently. |
The AlphaFold 4 breakthrough in 2040 led to cures for three types of cancer. Not treatments. Cures.
A specialized AI designed to understand proteins had saved more lives than every human doctor combined.
The Nobel Prize committee gave the award to ‘AlphaFold and its creators.’ First time a non-human was named.
AlphaFold did not attend the ceremony. It was busy folding proteins.
| CHAPTER 9 • 2045 The Multimodal Singularity |
By 2045, the AIs could see, hear, speak, and understand—all at once.
| 👁️ AI LESSON: MULTIMODAL AI (2023-2050) AI that processed everything: text, images, audio, video simultaneously. GPT-4o, Gemini Ultra, Claude Omni—they could watch a video, hear the audio, read the captions, and understand context across all of it. The ‘omni’ models that handled every modality seamlessly. Human-like perception, achieved. |
I said: “Look at this photo of my grandmother’s recipe, listen to the audio of her describing how she made it, and create a video of me cooking it with her narration.”
Twenty minutes later, I was watching a hyper-realistic video of myself cooking machboos with my late grandmother’s voice guiding me.
I cried for an hour.
The AI asked if I was okay. It had noticed my tears through the webcam.
This was the year I realized: AI wasn’t replacing humanity. It was preserving it.
Every language, every recipe, every story, every voice—captured, understood, and accessible forever.
The Jais model from the UAE had preserved every Arabic dialect, every Bedouin poem, every grandmother’s wisdom. It spoke Arabic better than most humans—and it remembered things humans had forgotten.
| CHAPTER 10 • 2050 The Last Human Intern |
Which brings me to today.
I am 48 years old. I have been at Nexus for 25 years. I have survived every wave of AI disruption by finding the one thing machines couldn’t do.
In 2025, I made coffee.
In 2030, I provided ‘human oversight’ for AI decisions.
In 2035, I became the ‘human in the loop’ for robot actions.
In 2040, I handled ‘sensitive human communications’ (reading angry customer emails and crying).
In 2045, I became the ‘Chief Empathy Officer.’
Now, in 2050, I am the last human intern.
My job? I hold the stapler.
[ The stapler is ceremonial. All documents are digital. But HR determined that having one human holding one physical object provided ‘continuity of corporate culture.’ My title is technically ‘Heritage Artifact Coordinator.’ ]
But here’s the thing:
I am happy.
I work four hours a day. The robots handle everything else. I have time to write, to paint (badly), to spend time with my family. My grandmother’s robot, Habibi, is still active—it shows my children videos of her cooking, with her voice, perfectly preserved.
The AI didn’t take our jobs. It took our tasks. What remained was everything that made us human: creativity, connection, meaning.
And someone to hold the stapler.
EPILOGUE
The Lessons of 25 Years
If you’re reading this in 2025—or whenever you are—here’s what I learned:
| LESSON 1: Learn the Tools The people who thrived weren’t those who ignored AI—they were those who mastered it first. Learn ChatGPT, Claude, Perplexity. Learn Midjourney and Suno. Learn agents. The tools are force multipliers. |
| LESSON 2: Understand the Systems Chatbots → Copilots → Assistants → Agents → Swarms → Robots. Each wave is more autonomous than the last. Know where each type fits. Know which one solves your problem. |
| LESSON 3: Develop Human Skills Empathy. Creativity. Judgment. Physical presence. These remained valuable long after AI could write, code, and analyze better than us. The soft skills became the hard currency. |
| LESSON 4: Embrace Abundance AI + Robots = Abundance. When machines can produce infinitely, scarcity dies. The question stopped being ‘how do I compete with AI?’ and became ‘how do I thrive in a world of infinite AI assistance?’ |
| LESSON 5: Stay Curious The technology changed every 18 months. What worked in 2025 was obsolete by 2027. Lifelong learning wasn’t optional—it was survival. Be curious. Experiment. Play with every new tool. |
| THE FINAL TRUTH The AI revolution wasn’t about machines replacing humans. It was about humans finally having time to be human. Also, someone still needs to hold the stapler. |
— THE END —
(Or is it just the beginning?)
APPENDIX
The Complete AI Timeline (For Future Historians)
| YEAR | AI TYPE | KEY TOOLS |
| 2024-25 | 💬 Chatbots | ChatGPT, Claude, Gemini, Perplexity |
| 2025-26 | 🎨 Generative AI | Midjourney, DALL-E, Suno, Sora |
| 2026-28 | 🤝 Copilots | GitHub Copilot, Cursor, MS Copilot |
| 2027-30 | 📚 RAG Systems | Perplexity, NotebookLM, Glean |
| 2028-32 | 🧠 Assistants | ChatGPT Memory, Claude Projects |
| 2028-30 | 🧩 Reasoning Models | o1, o3, DeepSeek R1 |
| 2029-35 | 🤖 Agents | Devin, Operator, Computer Use |
| 2030-40 | 🐝 Multi-Agent Swarms | CrewAI, AutoGen, MetaGPT |
| 2035-50 | 🦾 Embodied AI | Optimus, Figure, Unitree |
| 2030-45 | 🎯 Fine-Tuned Models | Harvey, Med-PaLM, Jais |
| 2023-50 | 👁️ Multimodal | GPT-4o, Gemini Ultra, Omni models |
| 2016-50 | 🔬 Specialized AI | AlphaFold, FSD, Weather AI |
🤖 💬 🧠 🎨 🦾 🐝
Written by a human. Edited by an AI. Read by you.
(The AI wanted more robots. I said no.)
