Every research programme is built on a stack of assumptions. Most hold. One won't. The question is whether you find it before you've committed three years and $4M of capital to a programme that fails on a premise you never stress-tested. Augle finds it — and tells you precisely what evidence would resolve it.
Research programme decisions happen fast. Literature summaries are compiled by team members with domain expertise but limited adversarial instinct. Errata go uncited. Foundational papers accumulate credibility without replication. By the time a programme fails, the assumption that killed it was visible in the evidence base from the start.
Questions research labs run on Augle
The Guardian's SVS tracks published errata across cited papers. A 2017 meta-analysis treated as confirmatory with a 31% reduction in pooled effect size after erratum — uncited in the team's literature summary — can rewrite the evidence weight assessment for every node that depended on it.
The Contrarian checks whether cited precedents actually apply to your specific context. Adaptive platform trials that demonstrated efficiency gains in characterised biomarker landscapes don't automatically support the same design in an uncharacterised one — and the Contrarian will say so, specifically.
The Methodologist traces which evidence nodes are load-bearing — which ones, if they fail, take the programme with them. The output names that assumption explicitly, specifies what data would resolve it, and estimates whether resolving it is feasible within your timeline and budget.
Team members reviewing their own programme's foundational literature have a structural conflict of interest. The Contrarian has none. It is architecturally required to steelman every claim before challenging it — which means it produces the strongest possible case for your programme before finding the objection that case doesn't fully answer.
Each scenario is drawn from the Augle Use Case Compendium — hypothetical sessions illustrating realistic deliberation behaviour across the research lab lifecycle.
“Is the published evidence for this oncology target sufficient to justify committing to a three-year, $4M research programme, or are there foundational assumptions that require resolution first?”
The lab director didn't get a yes or no. She got the specific assumption the programme depends on and a decision structure that resolves it cheaply before full sunk cost accumulates.
“For a combination immunotherapy Phase II trial in this indication, which trial design — randomised controlled or adaptive platform — is better supported by the available methodological and clinical evidence?”
The PI was leaning toward the adaptive design based on general literature. The ensemble surfaced the specific data dependency that makes the adaptive design's efficiency advantage unavailable in this trial — a finding that changes the protocol decision without requiring new experiments.
“Does the 2016 default mode network prospective memory finding have sufficient replication and methodological integrity to serve as a foundational assumption for a new multi-year research programme?”
The team's literature summary cited the 2017 meta-analysis as confirmatory without the erratum. Augle's SVS caught it. The corrected effect size changes what the programme can assume — catching this before programme launch avoids building three years of work on a specificity claim the corrected evidence doesn't support.
Submit the question alongside your team's literature summary, trial design brief, or programme memo. The Guardian immediately begins SVS authentication across every cited source — checking for retractions, errata, and preprint status before deliberation begins.
Across all three deliberation phases, the Methodologist evaluates which evidence nodes are critical dependencies — the assumptions whose failure takes the programme with them. Each gets a confidence grade and an explicit statement of what would change it.
It's not enough that a precedent exists — it has to apply to your specific context. The Contrarian actively tests whether cited studies' populations, designs, and biomarker landscapes match your trial's requirements. Inapplicable precedents are called out specifically.
The Pragmatist translates the finding into a concrete decision structure — including the specific experiment, checkpoint, or data collection that would resolve the critical assumption at minimum cost and time before full programme commitment.
Errata, retractions, and effect size corrections don't always propagate through the literature. The Guardian's Source Verification Service cross-references every cited paper against retraction databases and published errata — before the deliberation begins, not after you've built a programme on the finding.
The Methodologist doesn't produce a risk register of things that could go wrong. It identifies the single load-bearing assumption — the one whose failure takes the programme with it — and provides the specific evidence that would resolve it. General uncertainty acknowledgments are not permitted outputs.
Internal review is conducted by people who want the programme to succeed. The Contrarian is architecturally required to steelman every claim before challenging it — producing the strongest possible case for your hypothesis and then finding the objection that case doesn't fully answer. That's a structurally different process.
A cited precedent only supports your decision if it actually applies to your context. The Contrarian evaluates whether each precedent's population, design, biomarker landscape, and conditions match your specific research question. Citing an adaptive trial that succeeded in a characterised landscape doesn't support the same design in an uncharacterised one.
The Pragmatist produces a concrete resolution pathway — the specific checkpoint, assay, or substudy that resolves the critical assumption at minimum cost before full programme commitment. You don't just learn what's uncertain. You learn what to do about it, in what order, and at what cost.
A Standard deliberation costs $0.60. A three-year research programme costs millions. The economics of running an adversarial review before committing to a programme — or before locking a trial design — are straightforward. The question isn't whether you can afford to run Augle. It's whether you can afford not to.
Join the waitlist and get one Standard session free.
Run it on a programme decision that's live right now.