Research · Intelligence

Autonomous research agent

RecommendedHand Manus a goal; come back to a deliverable

When the task is 'research this market and write a 3-page summary' or 'find me 50 leads in this niche with verified contact info', a chat LLM is the wrong tool — too much hand-holding. Manus runs the multi-step plan autonomously and returns a deliverable. Claude is the QA gate before you trust it.

RESEARCHINTERMEDIATEIntermediateFrom $20/mo
The stack
Manus
Autonomous executor

Plans, executes, and returns a deliverable for high-context multi-step work. Good for research, list building, lightweight analysis. The right pick when the task would otherwise be a dozen chat turns and a human aggregator.

Free trial · $39/mo Starter · $199/mo Pro
Claude
QA + sanity check

Read the Manus output critically. Cross-check 3 to 5 claims with citations. Don't act on autonomous output without a human-in-the-loop pass.

$20/mo Pro · API $3/M tokensAlts: ChatGPT, Perplexity
Real monthly cost
small
$20/mo
Trial / occasional use
  • manusFree trial
  • claude$20 (QA)
medium
$59/mo
Weekly research runs
  • manus$39 Starter
  • claude$20
heavy
$219/mo
Daily delegated work
  • manus$199 Pro
  • claude$20
Workflow
  1. 1
    Write the goal, not the stepsManus

    Manus plans best when given the destination, not the route. 'Find me 30 EU-based SaaS companies in the HR space with public funding rounds in 2025' beats 'first search Crunchbase, then…'.

    Prompt · Goal-shaped Manus prompt
    I want a deliverable, not a chat. Here's the goal.
    
    Goal:
    """
    {{describe the deliverable: what it is, who it's for, what 'done' looks like}}
    """
    
    Constraints:
    - Time budget: {{e.g. "no more than 30 min of agent time"}}
    - Quality bar: {{e.g. "every claim has a primary-source link"}}
    - Format: {{Markdown / Google Doc / CSV with these columns / etc.}}
    - Out of scope: {{things you should NOT spend cycles on}}
    
    Run the plan. Hand me the deliverable when it's done.
  2. 2
    Watch the first 2 to 3 stepsManus

    Manus is autonomous, not magical. The first few steps tell you whether the plan is on the right track. Cancel + re-prompt if it's drifting.

  3. 3
    QA with ClaudeClaude

    Don't act on autonomous output blind. Run a structured QA pass against the deliverable.

    Prompt · QA pass on autonomous output
    Audit the deliverable below for trustworthiness before I act on it.
    
    Deliverable:
    """
    {{paste Manus output}}
    """
    
    Goal it was supposed to satisfy:
    """
    {{paste original goal}}
    """
    
    Output:
    1. **Coverage** — did it actually answer the goal? Anything missing?
    2. **Trust spot-checks** — pick 3 specific claims and tell me which I should verify by hand.
    3. **Format issues** — does it match the requested format? Are headings, columns, links right?
    4. **Red flags** — fabricated facts, broken links, hallucinated names. List specifically.
    5. **Verdict** — ship as-is / fix list / re-run with a tighter prompt.
    
    Be a skeptical reviewer, not a polite one.
What it produced
GTM analyst, weekly market scan

Replaced 3 hours of manual Crunchbase / LinkedIn search per week with a Manus run. Quality was within 90% on the first pass after the QA step caught 4 fabricated funding rounds. The QA gate is non-optional.

Common pitfalls
Trusting autonomous output blind

Manus hallucinates with the same physics as any LLM — just over more steps, with more confidence. The Claude QA step is the only thing keeping bad data out of your decisions.

Over-broad goals

'Research the EU SaaS market' is unbounded. Tight constraints make Manus useful; loose ones make it expensive.

Curated by @rae-f
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