Autonomous Research Agent
Part of the AI Engineer Roadmap
In short
Build an agent that takes a question, searches the web, reads sources and writes a cited report. It's the project that proves you can make an agent finish a real task.
An agent that searches, gathers, and synthesizes information on a topic with minimal human guidance — a strong demonstration of tool-use, planning and multi-step reasoning.
Think of it like this
The hostel friend who researches laptops
You ask your nerdy hostel friend for the best laptop under your budget. She searches, reads reviews, ignores spammy sites, notes what each source says and comes back with a short answer and links. Your agent does exactly that, without the late-night Maggi.
Watch it happen
Build plan for the research agent
1/5Milestone 1: take a question and a budget, like max 6 searches and 10 pages read.
The big ideas
What you need to know
Every claim cited
Keep notes tied to their URL. The report must cite a source for every fact it states.
Hard budgets
Cap searches, pages and tokens. Show the user what was used when the agent stops.
Dedupe and filter
Drop repeated URLs and obvious spam. Ten copies of one press release are not ten sources.
Test with known answers
Keep 10 questions where you know the answer. Rerun them after every change to catch regressions.
See it in code
Walk through the code
1MAX_SEARCHES = 62 3def research(question, search, read, llm):4 notes, sources = [], []5 queries = llm(f"List 3 search queries for: {question}").splitlines()6 for q in queries[:MAX_SEARCHES]:7 for url in search(q)[:2]:8 if url in sources:9 continue10 sources.append(url)11 notes.append(llm(f"Note facts relevant to '{question}':\n{read(url)}"))12 report = llm("Write a report. Cite [n] after each claim.\n" + "\n".join(13 f"[{i+1}] {n}" for i, n in enumerate(notes)))14 return report, sources1/4The model plans its own search queries from the question.
The core loop. You pass in search, read and llm functions, so you can test it with fakes before wiring up real APIs.
Save yourself the pain
Common mistakes
Oops
Stuffing whole web pages into the final prompt.
Do this instead
Summarise each page into notes first. The final call then sees only the useful parts.
Oops
Showing the report without the source list.
Do this instead
Always show links next to citations, so readers can check the agent's work.
Your mission
First milestone: fake it end to end
Quick check
Why turn each page into a short note before writing the report?
Go deeper
- 1Give the agent search and browsing tools, then have it produce a cited research summary.
- 2Add explicit stopping conditions so the agent doesn't loop indefinitely.
- 3Log the agent's full reasoning trace so you can debug and explain its decisions.
More projects at this stop
Multi-Agent Task Automation
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