
Vux
9 posts

Vux
@Iri_146
Ngta không phải thất bại vì thiếu cơ hội mà bởi vì kì vọng quá nhiều!


Posted about token waste yesterday. a reader came back with his own numbers. 139M input. 935K output. 148 to 1. his agent was injecting 52KB of context every single turn before it even saw the message. MEMORY.md alone was 22KB. every conversation started with rereading a small book. this is not an edge case. most agents are not thinking. they are reviewing. the fix is boring. move everything except core rules out of the prompt. put it in semantic search. let the agent fetch what it needs, when it needs it. he said token usage dropped 40-60% after the change. quality stayed the same. the most expensive thing is not paying your agent to think. it is paying it to reread the same files over and over.


There are multiple $1B+ opportunities to build managed AI agent "swarms" for specific industry verticals. Here's how I think about it: After just a few days toying around with agents, it's clear to me that the biggest challenge for adoption from non-tech companies/people isn't around initial deployment. It's going to be actually getting value out of the agents after they're deployed. You might be able to build and deploy an agent, but what the hell do you do with it after it's deployed? How do you train it to get better? What are the use cases that are most valuable for your industry? What are the latest skills that it needs to function at a 10/10 level? Without that, you're just going to have a bunch of fancy looking AI agents gathering dust on the shelves because you have no clue how to get any value out of them. That's the opportunity... Here's how you grab it: Pick a valuable industry vertical. Let's say finance. Build an agent "swarm" that is hyper-specific to that industry use case. So, for finance, it might be around modeling, industry case studies, company analysis, document review, etc. Hire a handful of ex-finance folks (or get them at a high hourly rate in their off-time). Use their industry expertise to train the agents on the initial expertise plus to refine them on an ongoing basis. You could niche down even further and choose one specific use case for an initial land grab (i.e. a modeling agent swarm or a loan analysis agent swarm). Deploy the agents the same way a staffing firm would deploy into a company. You could charge a one-time implementation plus ongoing annual license fee. Continue to manage and improve the agents using the data and insights coming back from customers. Manage them, keep them up to date, fix any issues. Customer is happy because they get the benefits of the transformative tech and cost savings without having to understand the tech or improve it. You're happy because you are making money (and doing something pretty cool). You could probably replicate this exact playbook across a long list of verticals (hence why I think there are multiple $1B+ opportunities). Just a thought...







