· Research AI
How Research AI Handles Fake Data: Source URLs Before Synthesis
We found a bad pattern in Research AI: some UI blocks looked factual but were not backed by original sources.
글에 붙인 라벨로 아카이브를 거릅니다.
· Research AI
We found a bad pattern in Research AI: some UI blocks looked factual but were not backed by original sources.
· Research AI
After you type a topic, Research AI returns a verdict and a 0–100 Learning ROI score. Both come from the same worker run — not from the browser guessing.
· T Today / invest-t-advisor (`t.xingai.app`)
[T Today](https://t.xingai.app) reads brokerage screenshots and returns a 做T plan — buy zones, sell targets, cash notes. A confident wrong ticker is worse than “I can’t read thi…
· XingAI Travel AI — `xingai-travel-ai`
Most travel sites answer: “Here are 400 flights.”
· T Today / invest-t-advisor
T Today (t.xingai.app) answers a narrow question:
· T Today / invest-t-advisor (`t.xingai.app`)
[T Today](https://t.xingai.app) is the screenshot-first coach: upload brokerage holdings, get a 做T plan with buy zones and rule checks. It’s paper-only — no orders.
· T Today / invest-t-advisor
T Today’s holdings coach uses OpenAI with responseformat: { type: "jsonobject" }. The model returns a big JSON blob with zh and en blocks. Users switched language — still empty …
· XingAI Invest AI
Early V1 tried providers in Ollama → Gemini → OpenAI order. The idea: avoid cloud cost until you must.
· XingAI Invest AI
This post documents a decision we accepted, not something already running in production. It belongs in the same story as our CQRS market cache: derived data should have one writer.
· XingAI Invest AI
Three endpoints burn real tokens on every hit:
· XingAI Invest AI
Most AI investment tools today work like this: dump market data into one LLM, get an answer back. It's simple, and it's wrong.
· XingAI Invest AI
Our V1 system uses a fallback chain: try Ollama (local, free), then Gemini, then OpenAI. Whichever model responds first wins. It's resilient, but every model does the exact same…
글에 붙인 라벨로 아카이브를 거릅니다.
· Research AI
We found a bad pattern in Research AI: some UI blocks looked factual but were not backed by original sources.
· Research AI
After you type a topic, Research AI returns a verdict and a 0–100 Learning ROI score. Both come from the same worker run — not from the browser guessing.
· T Today / invest-t-advisor (`t.xingai.app`)
[T Today](https://t.xingai.app) reads brokerage screenshots and returns a 做T plan — buy zones, sell targets, cash notes. A confident wrong ticker is worse than “I can’t read thi…
· XingAI Travel AI — `xingai-travel-ai`
Most travel sites answer: “Here are 400 flights.”
· T Today / invest-t-advisor
T Today (t.xingai.app) answers a narrow question:
· T Today / invest-t-advisor (`t.xingai.app`)
[T Today](https://t.xingai.app) is the screenshot-first coach: upload brokerage holdings, get a 做T plan with buy zones and rule checks. It’s paper-only — no orders.
· T Today / invest-t-advisor
T Today’s holdings coach uses OpenAI with responseformat: { type: "jsonobject" }. The model returns a big JSON blob with zh and en blocks. Users switched language — still empty …
· XingAI Invest AI
Early V1 tried providers in Ollama → Gemini → OpenAI order. The idea: avoid cloud cost until you must.
· XingAI Invest AI
This post documents a decision we accepted, not something already running in production. It belongs in the same story as our CQRS market cache: derived data should have one writer.
· XingAI Invest AI
Three endpoints burn real tokens on every hit:
· XingAI Invest AI
Most AI investment tools today work like this: dump market data into one LLM, get an answer back. It's simple, and it's wrong.
· XingAI Invest AI
Our V1 system uses a fallback chain: try Ollama (local, free), then Gemini, then OpenAI. Whichever model responds first wins. It's resilient, but every model does the exact same…