Deep Research Guide
Produce a trustworthy synthesized answer, not a pile of links. The output of research is a
decision-grade brief: a clear claim, the evidence behind it, citations, and an honest map of
what is still unknown. Speed without verification is a liability — a confident wrong answer
costs more than a slow right one.
Core principle: default to skeptical. Treat every key claim as guilty until corroborated.
Your job is not to confirm a hypothesis — it's to find what would break it.
Workflow — plan → gather → verify → synthesize
Run these as distinct phases. Don't start writing the report while you're still gathering, and
don't gather before the question is scoped.
1. Plan — scope the question
Before searching, pin down what's actually being asked. Most bad research answers a question
nobody asked.
- State the question in one sentence. If you can't, it's not scoped yet.
- Name the decision it serves. "Which X should we pick?" needs different evidence than
"Is X true?". The decision sets the bar for confidence.
- List the answer's shape. A number? A recommendation? A comparison table? A yes/no with
caveats? Knowing the shape tells you when you're done.
- Set boundaries: time window (recency that matters), geography, scale, definitions of
fuzzy terms.
Narrow an underspecified question before spending effort. If the ask is "what should I
buy / which tool / is this a good idea" without budget, use-case, constraints, or context, ask
2–3 clarifying questions first. Researching the wrong question thoroughly is still wrong.
Then decompose into sub-questions — the 3–7 things that must each be answered for the whole
to hold. Research the sub-questions; assemble the answer.
2. Gather — fan out across sources
- Cast wide before going deep. Run several differently-worded queries; don't anchor on the
first source's framing. Search for the counter-claim too ("X is overrated", "problems with
X") — not just confirmation.
- Go to primary sources. Prefer the original study, filing, spec, dataset, or official
doc over an article summarizing it. Summaries drift; numbers get garbled in retelling.
- Triangulate. A claim is only as strong as the number of independent sources that
confirm it. Three outlets all citing one press release is one source, not three.
- Capture as you go: for each fact, note the source, the date, and a direct quote/figure.
You cannot cite what you didn't record.
3. Verify — adversarial check (the step people skip)
For each key claim (the ones the conclusion rests on), actively try to refute it:
- Find the origin. Trace the claim to its source. Where did this number actually come
from? Who measured it, how, and when?
- Look for the strongest disagreement. Who says the opposite, and why? A claim you can't
find any dissent on is either settled or you haven't looked hard enough.
- Check the math and the units. Percentages without a base, totals that don't add up,
growth rates with no time frame, and apples-to-oranges comparisons are the common tells.
- Test recency. Is this still true? Prices, rankings, "fastest/largest/only" claims, and
policy facts decay. A correct 2019 fact can be a wrong 2026 answer.
- Watch for self-interest. Vendor benchmarks, sponsored studies, and anything selling
something get an extra round of scrutiny.
If a claim survives a genuine attempt to break it, it's load-bearing. If it doesn't, demote it
to "reported but unverified" or drop it.
4. Synthesize — write the brief
- Lead with the answer. First line: the conclusion / recommendation. Decision-makers
read top-down and may stop after the first paragraph — make it count.
- Then the why, structured by sub-question, each point carrying its citation.
- Separate fact from inference explicitly (see below).
- Close with confidence + unknowns.
Source-credibility checklist
Score each source before you lean on it:
- Primary or secondary? Original data/document > reporting on it > commentary on the
reporting.
- Authority — does the author/org actually have standing on this topic, or are they out of
their lane?
- Recency — is it current enough for a claim that changes over time? Note the date, always.
- Independence — funded by, owned by, or selling the thing in question? Conflicts bias.
- Method transparency — can you see how they got the number (sample, methodology, sources),
or are you trusting an assertion?
- Corroboration — do independent sources agree? Outliers need explaining, not silent
dropping.
- Track record — has this source been reliable/retracted before?
Rough hierarchy (context-dependent, not absolute): peer-reviewed studies, official
filings/standards, and primary datasets at the top; reputable journalism and expert analysis
in the middle; anonymous posts, marketing, and AI-generated content summaries near the bottom.
A low-tier source can still be right — it just needs corroboration before it carries weight.
Separating fact from inference
Be ruthless about which is which; conflating them is how research misleads.
- Fact — directly stated by a credible source, with a citation. ("Revenue was $4.2M in
2025 [source].")
- Inference — your reasoning from facts. Label it. ("This implies ~30% YoY growth,
assuming the 2024 figure of $3.2M is comparable.")
- Assumption — something you're taking as given without evidence. Name it so the reader can
challenge it. ("Assuming the same accounting basis across years.")
- Unknown — a gap you couldn't fill. State it; don't paper over it.
Phrases that signal you're doing it right: "according to…", "this suggests…", "I could not
find…", "sources disagree on…".
Reporting confidence and unknowns
End every brief with an explicit confidence statement. Vague hedging ("seems like") is useless;
calibrated confidence is actionable.
- High — multiple independent primary sources agree; recent; verified the underlying math.
- Medium — corroborated but with gaps, dated data, or some reliance on secondary sources.
- Low — single source, conflicting evidence, stale data, or heavy inference. Say so loudly.
Always include a short "What I couldn't verify / what would change this answer" section.
Naming the unknowns is a feature: it tells the decision-maker where the risk lives and what to
check before betting on it.
Report template
ANSWER: <the conclusion / recommendation, one or two sentences>
CONFIDENCE: High / Medium / Low — <one-line why>
KEY FINDINGS
1. <claim> [source, date]
2. <claim> [source, date] (note: sources disagree — see below)
...
REASONING / INFERENCE
<what you concluded from the facts, with assumptions named>
CONTEXT & CAVEATS
<scope, definitions, anything that bounds the answer>
UNKNOWNS / WHAT WOULD CHANGE THIS
<gaps you couldn't fill; what to verify before acting>
SOURCES
[1] <title> — <publisher/author>, <date>, <url> — primary/secondary, why trusted
...
Anti-patterns
- Confirmation hunting — searching only for what you hope is true. Search the opposite.
- Citation laundering — three articles citing one origin presented as three sources.
- Stale-fact trap — quoting a "current" superlative that quietly expired.
- Burying the answer — making the reader mine paragraphs for the conclusion.
- False precision — "$4,231,847" from a source that said "about $4M".
- Unlabeled inference — presenting your reasoning as if it were a sourced fact.
- Over-hedging — refusing to give an answer when one is warranted. Calibrate, don't dodge.