Coefficient.io VS GitHub
Compare Coefficient.io VS GitHub and see what are their differences
A simple way to keep all your data under control. Build your own business applications in just 4 minutes.
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Coefficient is a sidebar app for Google Sheets. Coefficient connects to any data source, imports live data into Google Sheets, automates spreadsheet workflows, and exports data into your business systems.
Coefficient.io GitHubCoefficient.io is recommended for professionals and teams in finance, operations, sales, and any business function that relies heavily on data analysis, reporting, and workflow automation. It's particularly beneficial for small to medium-sized enterprises that need to leverage data effectively without investing heavily in complex IT infrastructure.
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Based on our record, GitHub seems to be a lot more popular than Coefficient.io. While we know about 2474 links to GitHub, we've tracked only 4 mentions of Coefficient.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.
I do this all the time. The problem at first was I didnโt have access to real-time data from my sources. https://coefficient.io/ has a bunch of Google Sheets connectors you can use for free. Since then I never have to update my dashboards, I just send them out. Itโs great. Source: almost 4 years ago
Coefficient (https://coefficient.io) | Multiple Roles | Fully Remote | Full time | VC-Backed startup Coefficient is a fully remote, seed-stage SaaS startup based in the SF Bay Area. Started by repeat founders with successful past exits, Coefficient has raised $6.7M from Foundation Capital, S28 Capital, and prominent angel investors such as Eric Yuan, Zoom founder/CEO. Coefficient enables users to create custom... - Source: Hacker News / about 4 years ago
Coefficient | Multiple Roles | Fully Remote | Full time | VC-Backed startup | https://coefficient.io. - Source: Hacker News / over 4 years ago
Coefficient does that. You can schedule data refreshes, and every time the data updates, it automatically pulls down the formulas for each new row. Source: over 4 years ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 4 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 11 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 12 days ago
# git: the API token, plus the credential used for the push Kubectl create secret generic foreman-github \ --from-literal=GITHUB_TOKEN="$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 / 12 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 / 22 days ago
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