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Canny.io
GitHubProduct managers, software development teams, startups, and companies that want to engage their user base in the feedback process and prioritize feature development based on real customer input.
Based on our record, GitHub seems to be a lot more popular than Canny.io. While we know about 2473 links to GitHub, we've tracked only 42 mentions of Canny.io. 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.
What's the difference between this and like https://canny.io/ ? - Source: Hacker News / over 1 year ago
This is a slightly different feature set, but being more customer feedback centric rather than OKR centric might be worth considering: https://canny.io/. Source: over 2 years ago
Solutions like canny.io makes >$2M in ARR. My aim is to create product combining some features from canny and wiredash. Source: over 2 years ago
Researched the market and found https://wiredash.io/ - which is great tool, but it costs so much. 99 usd monhtly is.... 5 hours of work in Poland, where I live. Also I want to share project roadmap with my users inside it. Something like https://canny.io/ integrated into app. Source: over 2 years ago
Canny | Software Engineer | REMOTE | Full-time | https://canny.io Canny helps software companies keep track of feature requests to build better products. * Early-stage startup, 17 person team, $3m+ annual recurring revenue * 100% remote, distributed across US, Canada, Spain, Turkey * Bootstrapped and profitable https://careers.canny.io/?utm_source=hn Why work at Canny: https://canny.io/blog/work-at-canny/. - Source: Hacker News / almost 3 years ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 5 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 6 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$GITHUB_TOKEN" -n foreman-system Kubectl create secret generic foreman-git-credentials \ --from-literal=token="$GITHUB_TOKEN" -n foreman-system Helm upgrade foreman llmkube/foreman -n foreman-system --reuse-values \ --set agent.githubToken.secretName=foreman-github \ ... - Source: dev.to / 6 days ago
This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 16 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 17 days ago
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