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Meet your new Fellow. It doesn't sleep.
FellowHire pairs your team with AI Fellows โ purpose-built for real roles, integrated into your tools, and ready to contribute from day one.
AI Fellows work best in well-defined roles with clear inputs and outputs:
Engineering Support โ Triages bug reports, monitors alerts, writes PR summaries, flags code smells
Small and mid-size businesses losing 10+ hours per week to recurring admin work
Law firms, MSPs, agencies, and professional services
MSPs and resellers offering AI workforce to their clients (channel program available)
Not a chatbot. Not a generic virtual assistant. A real AI team member trained on your specific workflows, tone, and tools. Lives where your team already works (Slack, Teams). One Fellow per role. Same Fellow every day. Annual contracts.
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Based on our record, GitHub seems to be more popular. It has been mentiond 2474 times since March 2021. 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.
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 / 3 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 / 10 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 / 11 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 / 11 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 / 21 days ago
Upwork - Forget the old rules. You can have the best people. Right now. Right here.
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