Job Compass v1.1.0
AI-ranked LinkedIn jobs + auto-apply + real Gmail outreach
What it does
Job Compass is a Chrome extension that ranks every LinkedIn job by your resume, auto-applies to Easy Apply listings, and runs personalized outreach to hiring managers — sent from your real Gmail, not a relay. Free tier; Pro is $15/mo.
Does the same job
all alternatives →- JCJob Compass – AI agents that help you find jobs, not replace you2025 · jobcompass.ai · ▲30
My friend and I got tired of job hunting (347 applications, 4 responses) so we built AI agents to help job seekers instead of replacing them. The problem: 73% of applications never reach humans, 250+ people apply to each job, but 85% of positions are filled through networking. Our solution: AI agents that find hiring managers for any LinkedIn job, analyze your profile fit, and generate personalized outreach messages. Instead of competing with hundreds in the application pile, you reach decision-makers directly. Technical bits: LangChain + OpenAI for job parsing, Next.js + Supabase, custom…
Careerflow LinkedIn Optimization Tool2022 · ▲37640X more opportunities on LinkedIn with our Chrome Extension
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com