App Engineer का अंत: क्यों अगले 10 साल Agent Builders के नाम होंगे

Itihaas ka khud ko dohrane ka apna hi ek alag aur mazedaar tareeka hai, aksar tab jab hum bilkul comfortable ho jate hain.

90 ke dashak ke aakhri saalon ki kalpana karein. Agar aap HTML aur thodi bahut Perl ya PHP ke saath kushti karke ek chalti-firti website bana lete the, toh aap kisi 'jaadugar' se kam nahi the. Aap ek Web Engineer the, aur duniya aapki mutthi mein thi. Aap internet ke storefronts (dukaanein) bana rahe the.

Ab 2009 mein aage badhein. iPhone ne duniya ko badal kar rakh diya tha. Achanak, kisi ko aapki static website ki utni parwah nahi thi. Saari energy Objective-C aur Java ki taraf shift ho gayi. Agar aap ek Mobile App Engineer the, toh aap bhavishya likh rahe the. Aap woh tools bana rahe the jo log apni jeb mein lekar ghumte the.

Ab, 2024 ko dekhein. Mahual fir se thoda ruka hua aur shaant lag raha hai. App stores bhare pade hain; web par bhid-bhaad hai. Lekin satah ke neeche, ek bada badlav (tectonic shift) ho raha hai. Hum Interface ke daur se nikal kar Agent ke daur mein pravesh kar rahe hain.

Aagle dashak mein, sabse kimti title "Full Stack Developer" ya "iOS Engineer" nahi hoga. Woh hoga AI Agent Engineer.

Naya Tectonic Shift (Bada Badlav)

Yeh sirf koi naya framework war nahi hai ya koi nayi programming language seekhne jaisa nahi hai. Yeh ek buniyadi badlav hai ki kaam kaun karta hai.

Pichle bees saalon se, software engineering ka matlab tha insaanon ke click karne ke liye saaf, deterministic (nischit) raaste banana. Aapne ek button banaya; insaan ne us par click kiya; code ne ek function execute kiya. Insaan dimag tha; software sirf maanspeshiyan (muscle) thi.

Yeh dynamic ab palat raha hai.

Agentic Era mein, software dimag provide karta hai. Aapka kaam ab insaan ke click karne ke liye button banana nahi hai. Aapka kaam us digital employee ko banana hai jo yeh tay kare ki button kab click karna hai, ya behtar yeh ki, yeh pata lagaye ki button ki zaroorat hi nahi hai.

Main pichle das saalon se products bana raha hoon, aur main is zameen ko hilte hue mehsoos kar sakta hoon. Agar aap aaj ek agent likh sakte hain—ek aisa agent jo aapki seva kare, aapke workflow ko automate kare, ya aapke customers ko serve kare—toh aapke paas wahi leverage (taqat) hai jo 1999 mein us bachche ke paas thi jisne abhi-abhi business ko online lana seekha tha.

Lekin kadwa sach yeh hai: Agar aap isse seekhne se inkaar karte hain, agar aap sirf purani deterministic coding se chipke rehte hain, toh aap desktop publishing ke daur mein ek typesetter ban kar reh jane ke jokhim mein hain.

Jadoo se Parda Uthana: Tools aur Context

Jab log "AI Agent" sunte hain, toh woh Skynet ya kisi behad complex neural network architecture ki kalpana karte hain. Chaliye is shor ko hatate hain aur seedhi baat karte hain.

Agent banana koi jadoo nahi hai. Yeh engineering hai. Aur yeh do cheezon par aakar rukta hai: Tools aur Context.

Maine dekha hai ki zyadatar developers isse unnecessarily complex bana dete hain. Unhe lagta hai ki unhe models train karne ki zaroorat hai. Aapko nahi hai. Models—Claude, GPT-4, Llama—kaafi smart hain. Aapka kaam unhe haath (hands) aur yaadasht (memory) dena hai.

1. Tools (Model ko Haath Dena)

Ek Large Language Model (LLM) bas ek jar mein rakha hua dimag hai. Woh soch sakta hai, lekin duniya ko chhoo nahi sakta. Ek "Agent" bas ek LLM hai jise API endpoints ya CLI commands ka access diya gaya hai.

Aap model ko batate hain: "Yahan list_files naam ka ek tool hai. Yahan read_file naam ka ek tool hai. Yahan send_email naam ka ek tool hai."

2. Context (Model ko Disha Dena)

Fir aap role define karte hain. "Tum ek senior QA engineer ho. Tumhara lakshya is repository mein type errors ko fix karna hai."

Bas yahi hai. Yahi core loop hai.

Agar aapne Cursor ya Claude Code use kiya hai, toh aapne isse action mein dekha hoga. Aap edits ko micro-manage nahi karte. Aap kehte hain, "utils.ts mein type errors fix karo."

Agent sochta hai: Theek hai, mujhe pehle file dekhni hogi. Woh ls tool use karne ka faisla karta hai. Fir woh grep ya read use karne ka faisla karta hai. Woh error dhoondhta hai. Woh fix likhne ka faisla karta hai. Woh apne kaam ko check karne ke liye compiler run karta hai.

Yahi breakthrough hai. Yeh ab sirf "chatting" nahi rahi. Yeh ek decision loop hai. Model khud chun raha hai ki aapki di gayi samasya ko hal karne ke liye kaun sa tool uthana hai.

Chatbots se Decision Engines Tak

Pichle do saalon se, hum "Chat" phase mein phase hue hain. Hum AI ko ek smart librarian ki tarah treat karte hain—hum sawal poochte hain, woh jawab deta hai.

Woh daur ab khatam ho raha hai.

Agentic phase execution (kaam karne) ke baare mein hai. Yeh CLI ko sirf aapke type karne ki jagah ke roop mein nahi, balki model ke liye ek khel ke maidan (playground) ke roop mein dekhne ke baare mein hai.

Startups ke liye iske maayne (implications) sochiye. Pehle, agar mujhe customer refunds handle karne ke liye koi service banani hoti, toh mujhe ek UI, ek backend, ek database banana padta, aur buttons click karne ke liye ek support team hire karni padti.

Aaj, main ek agent likh sakta hoon. Main use Stripe API (Tool) aur hamari email history (Context) ka access deta hoon. Main use ek policy deta hoon: "Agar user 7 dinon ke andar nakhush hai toh refund kar do." Agent aane wale email ko padhta hai, faisla karta hai ki kya yeh criteria par khara utarta hai, Stripe refund tool trigger karta hai, aur ek jawab draft karta hai.

Kisi UI ki zaroorat nahi. Koi support ticket queue nahi. Bas ek lakshya aur kuch tools.

Agents Banane ka "Messy Middle" (Asli Sangharsh)

Main yahan koi khayali duniya (utopia) nahi dikhana chahta. Maine pichle chhe mahine agent building ki gehrayiyon mein bitaye hain, aur main aapko bata doon: yeh kaafi uljha hua (messy) hai.

Traditional coding logical hoti hai. If X then Y. Ya toh yeh chalta hai ya toot jata hai.

Agent engineering sambhavnaon (probabilistic) par chalti hai. Aap agent banate hain, use tools dete hain, aur kabhi-kabhi woh khidki kholne ke liye hathoude (hammer) ka use karne ka faisla kar leta hai. Kabhi-kabhi woh aisa parameter hallucinate kar leta hai jo exist hi nahi karta.

Yahi woh jagah hai jahan naya skill set kaam aata hai.

Agent Engineer hona sirf Python scripts likhna nahi hai. Iska matlab hai:

• Prompt Engineering as Architecture: Model ke behavior ko seemit (constrain) karne ke liye system prompts design karna.
• Eval Driven Development: Aap creativity ke liye unit tests nahi likh sakte, isliye aap evaluation pipelines banate hain yeh mapne ke liye ki agent kisi task mein kitni baar safal hota hai.
• Tool Design: Aise API interfaces banana jo itne "saaf" hon ki model bina confuse hue unhe samajh sake.

Maine agents ko unhi ke banaye bug ko fix karne ki koshish mein infinite loops mein phaste dekha hai. Maine unhe pure confidence ke saath galat file delete karte dekha hai. Yeh haqeeqat hai. Lekin in rukawaton (friction points) ko solve karna hi woh jagah hai jahan asli value create hoti hai.

Practical Takeaways: Aaj Kaise Shuru Karein

Agar main aaj shuruat se start kar raha hota, ya apna career pivot karna chahta, toh main bilkul yahi karta:

1. GUIs Banana Band Karein: Kam se kam apne side projects ke liye. Bina frontend ke kisi problem ko solve karne ki koshish karein. Kya aap isse CLI aur LLM ke saath solve kar sakte hain?
2. Interface Protocol ko Samjhein: Samjhein ki OpenAI ki function calling ya Anthropic ka tool use kaise kaam karta hai. Yeh agent age ka TCP/IP hai.
3. "Karne Wala" (Doer) Banayein, "Bolne Wala" (Talker) Nahi: Aisa bot mat banayein jo aapke calendar ke baare mein sawalon ke jawab de. Aisa bot banayein jo aapke calendar ko manage kare. Use events delete karne ki shamta dein. AI ko write access dene ka darr mehsoos karein. Tabhi aap sach mein seekhna shuru karte hain.
4. Context Management mein Maharat Hasil Karein: Seekhein ki context window ko overflow kiye bina usme sahi jaankari kaise bharni hai. RAG (Retrieval-Augmented Generation) toh bas shuruat hai.

Aage Ka Avsar

Hum ek aise bhavishya ki taraf dekh rahe hain jahan ek akela developer, specialized agents ki fauj ke saath, 20 logon ke startup jitna kaam kar sakega.

Creation (kuch banane) ke liye rukawatein zero hoti ja rahi hain. Lekin orchestration ke liye rukawatein—in dimagon ko ek saath kaise jodna hai yeh samajhna—naya moat (suraksha ghera) banti ja rahi hain.

Das saal pehle, aapko code likhne ke liye hire kiya jata tha. Aaj, aapko us system ko architect karne ke liye hire kiya jata hai jo code likhta hai.

Train station se nikal rahi hai. Aap ya toh platform par khade hokar apne purane frameworks ko pakde reh sakte hain, ya fir aap is par chadh kar patriyan (tracks) banane mein madad kar sakte hain.

Chaliye, kuch banate hain (Let's build).