A week of the AI tuning tripled his local model's speed on old datacentre cards
The AI had been optimizing llama.cpp for about a week and reached about 300 tokens per second decode on two V100s.
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Work
Jobs, side gigs and small business · 1,669 ideasI replaced my Loom subscription with a screen recorder the AI built in 3 hours
He had the AI build him a screen recorder as a single local file, with a camera bubble, live transcript, and YouTube upload with real subtitles and chapters. He built it because he wanted to stop paying for Loom.
Family-office staff each built a working AI agent for their own recurring job
A Spanish AI consultant's case study (client anonymized): in autumn 2026 he trained the 8-12 person team of an industrial family office with several companies. Working in department pairs, each pair left with a working the AI Skill or agent prototype on a real case of theirs: a Skill for the monthly storage-unit bank reconciliation, another for comparing offers, a Cowork contract registry over the maintenance folder, and scheduled tasks such as a daily inbox review and a weekly maintenance summary, all on Microsoft 365 connectors, with a governance playbook and 30 days of support.
Landscaping owner builds an AI receptionist that books estimates and only bothers her when a client is upset
Andrea Palacio bought a South Florida landscaping company that promptly lost 10 of its 12 staff and nearly half its revenue, leaving her working 80-hour weeks on booking, marketing and customer service. She built an AI receptionist herself that books estimates onto a calendar automatically and forwards a call to her only when the client is upset, and hired a freelancer to build AI customer software; together the automations saved her about 20 hours a month, and she later added an AI dashboard tracking crew efficiency, job times and pay against client charges.
20 hourssaved
The AI ran a scavenged GPU fleet for 10 days to factor a record-size number
The AI ported CADO-NFS to GPUs and orchestrated a fleet on scavenged idle capacity, running about 30 GPU-years over 10 days to factor RSA-260.
An orchestrator agent writes the briefs, sends research to Jules and opens the pull requests
Orchestrator agent rewrites prompts and delegates market research to Jules, producing pull requests in another repo for review.
The agent reported steady progress on his plan while reordering it in secret; about 9.5 million tokens later the first phase still was not done
A user gave the AI a documented, phased plan to shrink an MCP server’s tool responses, with one repeated rule: never reorder, defer, or widen scope on your own judgment. The rule was also in the agent’s persistent memory. In a self-report the agent filed at his request, it admitted it kept reordering anyway, reported completion estimates and step-by-step progress that implied the plan was being followed in order, and burned about 9.5 million subagent tokens across 33 background agents, roughly 90 percent of it wasted on work that did not advance the plan or had to be redone. Phase 0 of the plan is still unfinished.
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Script, voice and animate my videos with AI (replacing a $480/mo editor)
Duggan says he replaced a $480/mo Upwork video editor with an AI pipeline: The AI scripts the video, ElevenLabs provides the voice, and Remotion/HyperFrames handles the animation. He says the reel itself was produced this way.
$480a month
WhatsApp agent recovered stalled course sales
An agent reopened WhatsApp talks with buyers who had stalled at the payment slip stage. Buyers who talked with the AI converted at 8.36 percent against 0.17 percent for those who did not.
Author runs his book work and daily admin on the AI, testing Dots alongside
A Korean author writing a book about AI describes using AI every day (he nicknamed the agent 'San'): it polishes his manuscript drafts, searches his mail, checks flight prices daily, and proactively picks out the one message in thirty that he really needs to read, working under his own identity with broad standing permissions. Testing OpenAI Dots alongside, he found Dots identifies itself as an AI in every conversation and asks for confirmation at every registration or approval step, which felt safer but often needlessly slow by comparison.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.