Lesson 142 — Advanced

Deep Research & Long-Horizon Scenarios

Kuch sawaal ek prompt aur ek response ke andar hal ho jaate hain; kuch ghanton chalte hain, daurlag sources padhte hain aur ek report par khatam hote hain. Is lesson mein hum dekhenge long-horizon run alag kyun hota hai, question ko kaise decompose karte hain, breadth-first padhai, sources ko critically padhna, disagreement reconcile karna, notes carry-forward, stopping conditions aur audit-wali report.

⏱ 20 min• Advanced• Choosing a Multimodal Model

Long-horizon run kya hai

Kya hai?

Long-horizon run matlab ek aisa agentic task jo minutes ya ghante chalta hai: sawaal chhote hisson mein tootta hai, sources explore hote hain, structured notes bante hain, aur ek cited report se khatam hota hai. Single prompt-response nahi — plan-execution loop hai.

Kab kaam aata hai?

Market research, competitive analysis, literature review, due diligence, ya "ye technology hamare liye fit hai" jaise sawaal — jahan ek answer nahi, judged synthesis chahiye.

Kahan milta hai?

Deep-research style agent products mein, khud banae multi-step tool-use loops mein, aur batch jobs mein jo sources traverse karke report file karti hai.

Funda ye hai ki context window poore run tak nahi chalta — sources itne hote hain ki raw text carry karna mumkin hi nahi. Isliye is game mein jeet uski hai ki tum raw source ko tod kar chhote notes banao, notes ko aage carry karo, aur original sawaal ko kabhi bhoolo na.

Mental model: Sawaal → sub-questions → broad search → source shortlist → critical read → cited notes → synthesis → stopping decision → auditable report. Har step ka apna artifact hona chahiye — sirf "chat chal rahi hai" wala run kabhi auditable nahi banta.

Decompose karo, breadth-first jao

# Pehle sawaal ko chhote, independently checkable hisson mein todo
question = "Kya hum is vendor ko production ke liye lein?"
sub_qs = [
    "vendor kya support karta hai (SLA, uptime)?",
    "pricing model kya hai, hidden limits?",
    "hamari data residency requirement match hoti hai?",
    "alternatives kaun hain aur unka trade kya hai?",
]
# har sub-question ka apna sources + finding hoga — report isi pe baithegi

# Breadth first: pehle bahut candidates, phir chhun ke gehrai
candidates = search_all(sub_qs)              # kaafi saare links (titles/summaries)
worth = rank_and_pick(candidates, k=5)       # sirf chhune hue 5 ko close-read karo
Scope creep roko: Sub-questions original question se nikalne lagein toh back-link rakho. Run ke end mein report original question ka jawab de, apni research journey ki diary nahi — drift isi rule se rukti hai.

Critical reading aur disagreement

Critical reading ka matlab har sentence pe doubt nahi — evidence ke tier ko pehchanna hai. Ek official changelog ka weight tweet se zyada hai, aur dono ka weight ek controlled observation se kam. Ye hierarchy tumhare notes mein visible honi chahiye, taaki synthesis mein hierarchy bik jaaye nahi.

Reconciliation rule: Do sources disagree toh teen mein se ek: (1) behtar evidence wala prefer karo, (2) dono stances reasons ke saath likho, (3) uncertainty report karo. Average sabse galat option hai — wo number kisi source ne bola hi nahi hota.

Notes aur carry-forward state

# Context badh raha hai — raw sources mat carry karo, findings carry karo
note = {
    "sub_q": "pricing model?",
    "finding": "per-seat + usage tiers; free tier limits documented",
    "sources": ["doc:pricing", "doc:limits"],   # har finding ke sources
    "confidence": "verified-2-sources",
    "checked_at": "2026-10-19",
}
run_state = [note, ...]        # chhota structured state = tumhari memory

# Agla step: notes padho -> gap dhoondo -> next search chalao
# Raw page text sirf tabhi dobara khulta hai jab note kam pade
Context management hi asli skill hai: Bade transcripts prompt mein dhone ki jagah, structured notes ka ek chhota state rakho. Iska fayda teen cheezein hain: resume aasaan, report banane mein sources pe turant pahunch, aur prompt cost controlled.

Stopping, report aur classic failures

Definition of done: Report ka har paragraph source se linked ho, original question ka jawab top pe ho, aur tum khud ek reader ki tarah audit kar sako bina dobara search kiye. Yahi long-horizon run ka acceptance test hai.

Exercise

Question: Gehrai se padhne se pehle titles/summaries dekh kar sources chunna — ye strategy kya kehlata hai? (do shabd)

Question: Do sources disagree — unka average nikaalne ke bajaye kis cheez ko prefer karte hain?

Question: Context badhne par raw sources ki jagah notes mein kya carry karte hain? (ek shabd)

Question: Sources repeating hone lagein toh research run ko kya karna chahiye? (ek shabd)

Common mistakes

Desi example: CA ki due diligence file

Accha CA faisla seedha nahi deta — pehle kaagazat ki list banata hai (decompose), sab folders ek nazar dekhta hai (breadth), zaroori wale kholta hai (depth), aur har finding ke saath page number likhta hai (citation). Sirf "meri rai hai" wali file audit mein nahi chalti:

text
sawaal -> kaagazat list -> folders scan -> zaroori kholo -> har finding pe page number
      -> summary: kya mila, kya nahi, kya doubt hai      (cited notes)
warna: bina reference wali rai = kisi kaam ki nahi
Interview angle — yahan se sawaal aate hain
  • Q: Long-run aur single prompt-response ka farq kya hai? — State, notes aur stopping decisions chahiye; context window itna nahi ki raw sources sab carry kar sakein.
  • Q: Breadth-first kyun? — Gehrai mehngi hai; pehle candidate pool, phir top-k ko close-read — coverage aur cost dono behtar.
  • Q: Sources disagree toh kya karoge? — Evidence hierarchy lagao, behtar wala prefer karo, warna disagreement explicitly state karo — average kabhi nahi.
  • Q: Long-run ki teen classic failures? — Question se drift, thin evidence pe confident synthesis, aur supporting nahi wali citations.
  • Q: Kab stop karoge? — Answer mil gaya, sources repeat ho rahe hain, ya baaki uncertainty search se resolve nahi hogi.
Lesson complete?

Long-horizon runs clear — decompose, breadth-first, critical reading, carry-forward notes, stopping conditions aur auditable report sab aa gaya. Agla lesson — On-device & Edge Modalities — mein dekhenge kaunse parts user ke device pe chalane chahiye aur kyun.

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