
Dovetail
Canny.io
Sprig
Betafi
Theysaid
UserTesting.com
Survicate
Condens.io
GitHub
GitLab
BitBucket
VS Code
Git
Treehouse
Pantheon
CodePen
Dovetail
GitHubDovetail is recommended for research teams, UX/UI professionals, product managers, and any organization needing powerful tools for qualitative data analysis and research collaboration. It is ideal for teams who want to centralize their research insights and improve decision-making through data-driven approaches.
Based on our record, GitHub seems to be a lot more popular than Dovetail. While we know about 2476 links to GitHub, we've tracked only 14 mentions of Dovetail. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Most of my friends at Canva and Atlassian swear by Dovetail (dovetail.com) which was pretty much built for this workflow. Source: over 2 years ago
2 - DoveTail: Qual study tool; really love this one and it has a lot of features. Auto-transcription, sentiment analysis, and customizable data organization to streamline research analysis. Source: over 2 years ago
Dovetail. We have played with this for our studies and really like it, it creates video clips out of your time stamps. https://dovetail.com/. Source: about 3 years ago
Nice way to visualize your research. There is also an app called Dovetail where you can also tag and organize findings. Source: over 3 years ago
Https://dovetailapp.com/ and https://condens.io/ (both excellent and specifically focused on user research). Source: about 4 years ago
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 5 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 6 days ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 11 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 18 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 19 days ago
Canny.io - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.
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Betafi - Your User Research Sidekick
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