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Writesonic
GitHubBased on our record, GitHub seems to be a lot more popular than Writesonic. While we know about 2475 links to GitHub, we've tracked only 34 mentions of Writesonic. 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.
Short answer: there is no single best tool. There are five mainstream options that each solve one part of the workflow well (Jasper for brand voice, Copy.ai for sales workflows, Writesonic for GEO tracking, Writer.com for enterprise governance, Buffer AI for multi-platform scheduling), and one emerging tool (Ozigi) that solves the gap they all leave open: producing AI-generated content that does not read as... - Source: dev.to / 3 months ago
Writesonic delivers solid AI writing capabilities at competitive prices. The platform includes article generation, paraphrasing tools and a chatbot interface for interactive content creation. Its Photosonic feature even generates images to accompany written content. - Source: dev.to / 8 months ago
Generative AI can help you create text quickly and efficiently. Tools such as Jadve AI and Writesonic can assist. - Source: dev.to / over 1 year ago
If that's the criteria, then fair, but AIMD produces articles that are virtually indistinguishable from what an average copywriter would compose if you hired them. AIMD is very different from your typical article generators (like https://writesonic.com/, which good God I don't know why anyone would use, but they are doing good, so good for them) that is just spinning out... - Source: Hacker News / over 2 years ago
In principle, I agree with you. I spent a lot of time thinking about this subject and it boils down to: I can try to do this in such a way that creates the best possible outcome or I can wait for someone else to do it in such a way that makes it worse for everyone. Take something like https://writesonic.com/ as an example. It is backed by Y Combinator and claims to have 5M+... - Source: Hacker News / over 2 years 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 / about 1 hour 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 / 5 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 / 12 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 / 13 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 / 13 days ago
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