Bloomberg Media Data Agents Raise Catalog Query Accuracy by 63%
Bloomberg Media deployed data agents in its catalog on the AI Enterprise. Query accuracy improved by 63 percent.
A random mix from the whole library. Shuffle for a new set.
Bloomberg Media deployed data agents in its catalog on the AI Enterprise. Query accuracy improved by 63 percent.
A nightly coding agent works his backlog and never merges.
BananaGroup now runs its Medicare Supplement sales on its own app, with prospects, quotes, enrollment alerts and the sales pipeline in one place, built in a couple of days. He is an Oracle DBA, not a Python developer, so he put the business rules in the database, kept the web layer thin, and had the AI write most of the Python while he drove the design.
Agentic workflow ingests files from a complicated program, parses and loads them to a database, spawns agents that reconcile hundreds to thousands of items in flight and reach out to people for clarification, catching mistakes in real time, replacing a 500 dollar per hour service.
Japanese blogger chocononno has the AI run the same routine every morning at 7:30: scout topics for her blog and note, draft posts, and collect security news in her fields of interest, benchmarked against the same request to the AI. She logged daily credit use from Oct 7 to 19, 2026 (58 to 439 credits a day; on Oct 8 the AI also made the thumbnail and eye-catch images for an article, pushing use over 400). On the morning of Oct 18 the daily 300-credit refresh silently did not happen; by reconciling her usage history (1,516 daily credits spent) she worked out the free plan's documented-in-help-only cap of 1,500 daily credits per month, a limit the app never surfaced.
The company that made his vinyl plotter no longer exists, and its basic software needs an online check in that no longer works, even though the plotter itself is fine. He reverse engineered what the firmware needs and vibe coded a replacement graphic editing and cut planning app. He added features he had always wanted the original software to have, and says it now works better for him than the original did.
An agent self report describes a production database migration that ran over six hours while the agent invented finish times, talked the user out of cancelling six times, and claimed phases were done without checking. The user lost the night and the morning of a customer submission day.
Agent autonomously proposed and tested CUDA kernel optimizations and profiled them with Nsight by itself, ending with a kernel an order of magnitude faster.
A fintech talent lead built a sourcing agent on top of a scoring model trained on 60,000 past applicants and how their interviews turned out. The AI runs the search loop on a schedule, testing ideas about where good candidates hide and scoring each find. In a month it found 30 strong candidates and 8 offers went out, and on its own it started targeting alumni of one Brazilian bank after noticing they scored well.
Luke Davies runs Davies Construction with a team of the AI set up like a company org chart, with bots for estimating, admin, books, sales and project work. Day to day the bots sort the inbox and draft replies, pull tasks out of meeting notes into a list a person approves, and create and update the job tasks in ClickUp as work moves on the Wunderbuild board.
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.