Yesterday, the client changed the brief again—and my AI assistant was carrying a heavy pack
At 10 p.m. on Tuesday, I was revising a quote for a freelance client in Hangzhou. The longer we chatted, the “smarter” my AI assistant became—but also the slower and more expensive it got. Old quotes, abandoned drafts, and two rounds of repeated requests all stayed in its context. The cost warning made me flinch—I’ve been stuck there too, assuming that remembering more meant being more professional. Later, I realized memory isn’t a warehouse: packing it full only slows down every task.
NVIDIA’s approach is subtraction, not more AI memory
These AI agents read files, reason, and call tools. Over time, temporary details pile up too. NVIDIA’s strategy isn’t simply to expand memory. It starts by asking what’s worth keeping, where it belongs, and whether it can be reused next time.
I know a friend, Lin Yue, who builds a personal brand in Guangzhou and posts two short videos each week. She has her assistant retain only her “brand voice, approved bio, and long-term topics,” then archives temporary scripts and comments after each episode goes live. Her rule is: “Remember the conclusion; don’t keep carrying the process forever.” That doesn’t mean making the AI forget everything. It means not treating every detail as long-term memory.
Replicating this setup costs very little
The cost is 0 yuan and about 30 minutes. The only technical barrier is being able to distinguish “long-term materials” from “temporary conversations.” First step: open the AI chat or project page you already use, create a list called “Frequently Used Materials,” and add only your brand introduction, client preferences, and reusable conclusions. Don’t import every chat history yet, and don’t buy a larger memory plan. After completing a task, spend five minutes deleting outdated requests. Once the list reaches a dozen or so entries, consider whether a dedicated memory tool makes sense. There’s no rush to tidy up now; with only a few small clients, repeated usage usually isn’t noticeable yet.
Choose based on the load you’re carrying now
Just starting out: I wouldn’t add another tool yet. I’d keep one manual list and clean it once a week, building the habit of not dumping everything into storage.
If you have one or two clients: I’d store each client’s approved requirements separately so information doesn’t bleed across accounts. For quotes and delivery dates, I’d personally confirm the details once more before sending.
If you’re scaling: I’d test automatic filtering, archive temporary records on a schedule, and let only high-frequency, long-term information enter the frequently used memory. Not everyone needs a tool, but the larger the team and the more frequent the calls, the more worthwhile configuration and monitoring become. I’d start with the project burning the most money, run it for two weeks, then decide whether to continue.