Tendril
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New · guided experience
A curated walkthrough of the library — ordered lessons, a 15-question quiz between each, and 3 next-steps so you stay in flow. Earn XP, badges, and a streak as you go.
Library · 6440 lessons · Research view
Deep dives, fact-checking, comparing sources. Pick a tool lane below to drill into concrete workflows, then use the browser to refine by age, situation, or skill level.
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Start with a real app or workflow. Each lane filters the library to practical lessons, not just broad theory.
603 lessons in research
Lessons handpicked for the Research shelf.
Primary sources are powerful but difficult. AI can generate structured analysis prompts, context scaffolds, and sourcing questions that make documents accessible to students across reading levels.
Students often see something powerful in a work of art but lack the language to discuss it. AI can generate structured critique frameworks — using describe, analyze, interpret, evaluate — that scaffold visual thinking without scripting responses.
The deepest learning happens when students apply knowledge from one subject in another. AI can generate cross-curricular connection prompts that make transfer explicit — giving students a reason to see their learning as connected rather than siloed.
Generic PD rarely changes classroom practice. AI can help teachers design personalized PD pathways — identifying specific skill gaps, locating relevant resources, and structuring a growth plan aligned to school and personal goals.
Fresh Research lessons added to the library.
Summarize medical research literature with AI for clinical decision-making — and never trust the citation without checking it.
AI plays hostile-discussant for your conference talk so creator-researchers don't get blindsided in Q&A.
AI digests sprawling archive finding aids so creator-researchers walk into reading rooms with the right box numbers.
AI translates effect sizes into plain-language analogies so creator-researchers communicate findings without misleading anyone.
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Primary sources are powerful but difficult. AI can generate structured analysis prompts, context scaffolds, and sourcing questions that make documents accessible to students across reading levels.
Students often see something powerful in a work of art but lack the language to discuss it. AI can generate structured critique frameworks — using describe, analyze, interpret, evaluate — that scaffold visual thinking without scripting responses.
The deepest learning happens when students apply knowledge from one subject in another. AI can generate cross-curricular connection prompts that make transfer explicit — giving students a reason to see their learning as connected rather than siloed.
Generic PD rarely changes classroom practice. AI can help teachers design personalized PD pathways — identifying specific skill gaps, locating relevant resources, and structuring a growth plan aligned to school and personal goals.
Detection arms races don't produce honest students. AI literacy education — helping students understand what counts as their own thinking and why — is the only approach that survives the next generation of AI tools.
School culture surveys generate data that often sits unanalyzed. AI can synthesize the responses for faculty discussion — including the uncomfortable findings that get buried otherwise.
AI can give students fast feedback on essays — comma usage, structure, argument strength. The art is using it to deepen teaching, not deskill teachers.
Teachers create resources constantly. AI accelerates while teacher authority on content remains.
Use AI to analyze a transcript of your own classroom and identify talk patterns you'd want to change.
Use AI to compare your written grading policy to your actual gradebook patterns and surface gaps.
Use AI to vet new curriculum materials against your actual standards and student profile.
Use AI to organize evidence for an external visit by aligning artifacts to your school improvement plan goals.
Decide which assignments warrant deep feedback and which need a check mark.
Write the incident report so it's clear, factual, and useful months later.
AI policies in syllabi rot fast — AI can compare last year's policy against this year's actual classroom AI use and propose revisions before semester starts.
AI can compare scope-and-sequence documents across grades and surface vertical alignment gaps — making the K-5 conversation legible before back-to-school.
Earnings call transcripts are rich sources of qualitative signal — management confidence, forward-looking language, hedges, and tone shifts. AI can analyze transcripts at scale, extract key statements, score sentiment, and flag changes from prior quarters that human listeners might miss.
An investment thesis distills complex research into a concise argument for or against a position. AI can help analysts structure the thesis, surface counterarguments, identify the key assumptions that must be true for the thesis to hold, and draft investor-ready prose — accelerating from research to recommendation.
ESG analysis involves synthesizing data across dozens of dimensions — carbon intensity, labor practices, board composition, supply chain risk, and more. AI can accelerate ESG screening by summarizing company disclosures, flagging controversies, comparing against peer benchmarks, and drafting ESG commentary for investment research.
SEC filings — particularly 10-K annual reports and 10-Q quarterly reports — are among the most information-dense documents in finance. AI can extract key disclosures, flag changes from prior filings, identify risk factors that have been added or modified, and summarize the financial condition sections that investors most need to read.
Algorithmic and quantitative trading strategies are often black boxes to non-quant finance professionals and clients. AI can explain the mechanics of common strategies, translate quant jargon into plain language, help practitioners understand the risk characteristics of algorithmic approaches, and draft client-facing explainers that build confidence without oversimplifying.
KYC packages can run hundreds of pages — beneficial ownership, source of wealth, sanctions screens, adverse media. AI can produce the synthesis that compliance officers need without the manual reading.
AI underwriting tools can analyze applications faster and surface considerations a human might miss. The loan officer still makes the call — AI just makes them better at it.
Wealth management AI lets advisors serve more clients with deeper personalization. The advisor relationship remains central.
Investment research synthesis across thousands of sources is bottleneck. AI accelerates without replacing analyst judgment.
Bank product development benefits from AI in customer research and prototyping. Compliance throughout.
Credit unions serve members with limited resources. AI augments small teams.
Structure a long-form initiation report from filings and call transcripts.
Outline state nexus considerations from revenue and presence facts.
Use AI to draft a trade-error memo documenting facts, customer impact, and remediation for compliance review.
AI can draft LBO debt schedule narratives that organize tranches, covenants, and amortization into a sources-and-uses summary the deal team can stress before IC.
AI can draft ESG controversy response narratives that organize incident facts, stewardship history, and engagement options into a summary the IC can use to decide engagement or exit.
AI can summarize a tax code section into a research memo, but a CPA or tax attorney verifies before reliance.
AI accelerates the structure of a tax memo; every citation must be verified against primary authority.
AI can suggest formula audits and structure improvements; you still walk every link before trusting it.
Prior authorization letters are time-consuming to write and have high stakes for patients. AI can draft compelling, evidence-based authorization requests that cite clinical guidelines and patient-specific factors — saving hours per case.