Briefly
Complex ideas. Clearly explained.
AI agents and agentic systems — concepts, comparisons, and explainers. The plain-language answers, without the 2,000-word essay.
How does an AI agent remember?
What a model can see during a task is bounded by its context window. Everything beyond that boundary must be written somewhere and retrieved on demand.
How to think about choosing an AI model
Every model is a set of trade-offs: capability, speed, cost, context length, modality, and where it runs. The right choice depends on which ones matter for your task.
What are embeddings?
How a trained model turns a word, sentence, or image into a list of numbers where distance in the space carries meaning.
Agentic AI vs generative AI: what is the difference?
Generative AI produces content in response to a prompt. Agentic AI pursues a goal across multiple steps, almost always using a generative model as its engine.
AI agent vs AI assistant: what's the difference?
Assistants answer. Agents act.
AI agent vs automation: what's the difference?
One replays the same steps every run. The other decides its next move as it goes.
Can AI agents access my data?
What agents can and cannot see, how tool permissions gate access, and why the real risk is over-permission rather than circumvention.
Do AI agents hallucinate?
The loop does not just carry a hallucinated output forward. It compounds it.
How much do AI agents cost?
The per-call price is low; the loop is what makes the bill.
Nothing here yet under that search.
Stop reading about it. Start directing it.
Briefly explains the ideas. Brief is the team that runs on them — opening to a small group at a time.