Summary
According to a post on X by @codatta_io, Codatta has introduced Humanbased, a platform where developers define tasks and rewards. Experts then contribute their knowledge to build the data that AI agents need. The post frames this as a bet that expert human input, not just scraped data, will improve agents. The source snippet does not give pricing, user numbers, or launch dates, so those details are not available here.
AI-assisted summary based on the listed source.
What happened
Codatta introduced Humanbased, a platform where developers define tasks and rewards and experts contribute their knowledge to build the data AI agents need. Why it matters: It is another bet that expert human input, not just scraped data, is what improves agents. Original post on X Section: Launches & New Products
Why it matters
Developers building AI agents may gain a new way to source specialized training data by setting tasks and rewards for human experts. The approach shifts some attention from scraped data toward curated expert input, which could matter for teams whose agents need domain knowledge. Watch for details on how quality is checked, how experts are paid, and whether early users report measurable gains.
Signal Intelligence
Signal Strength 90%
Technical label WATCH
Public Interest 38
Category AI AT WORK
Reader Depth PRACTICAL
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
Recognizable Entity Score 0
Practical Impact Score 56
Novelty Interest Score 94
Consequence Score 18
Curiosity Score 16
Shareability Score 35
Why this is here
VQV surfaced this signal because it is recent, relevant to AI Agents, connected to Scobleizer News Pulse (X).