December was the product starting point for ISEA. The main achievement was turning “AI helps you log life” from an idea into an interactive prototype: users could send messages, receive streamed replies, and let tools write structured records into local data.
This update is more foundational than later monthly notes because many user-facing experiences were just taking shape. But these foundations explain why ISEA became a record product rather than just another chat box.
The AI Agent MVP can talk
ISEA completed an early AI Agent MVP in December. Chat UI, streaming responses, loading states, and basic analysis flows came together so users could start expressing what they wanted to record in natural language.
We also started showing why the AI wanted to use tools, with compact tool cards for execution state. Users should see more than a block of generated text. They should understand what ISEA is trying to do.
Local-first record execution
The early architecture chose a local-first direction. AI does not only generate prose. It uses local tools to create, query, and update records. December added local queries, batch creation, account input normalization, past-time restrictions, and structured data validation.
That matters for the product experience: when you say “I spent 32 yuan on coffee yesterday,” ISEA should try to turn that into a reviewable record, not leave it trapped in chat history.
Messages and sessions start persisting
To make conversations more than one-off exchanges, December added AI message tables, tool call events, message sync, cursor sync, and server-side persistence foundations. Message ordering, flicker, duplicates, and tool output backfill also went through several rounds of fixes.
These details sound technical, but users feel the result: chat behaves more like a continuous timeline, and AI actions become easier to follow.
Prompts, safety, and assistant identity
December also included a lot of prompt work. ISEA began requiring tool calls for actionable requests, restricting future-dated records, reducing repeated tool use, and adding prompt-injection protection.
The assistant identity also became clearer. It is not just making conversation. It is trying to help turn life events into records, while explaining what it is doing in a more human way when needed.
Landing site and product shape
Near the end of the month, the early landing site joined the monorepo with localization, visual effects, ports, and testing foundations. The site was not the headline, but it gave ISEA a place to explain itself publicly.
December was early, but the core direction was already visible: natural language input, structured records, local-first storage, and AI-assisted organization. The mobile client and sync work that followed grew from this base.