use cases

Claude Code can feel brilliant for the first hour of a feature. It finds the right files, follows your conventions, and remembers why you picked one implementation path over another.

In March 2026, a team at Meta published a paper showing AI agents that improved their own code from 20% to 50% on the SWE-bench benchmark — not by getting

Claude Code feels much better when it remembers the project. It stops asking which test command to run, stops rewriting code against the wrong style, and starts acting more like

You upload a PDF. You ask a question. NotebookLM answers. Sounds simple. But if you have ever asked NotebookLM something and gotten a confident, completely wrong answer, you already know

Open any AI personal finance app's marketing page and you'll see the same pitch: your money, understood. Proactive insights. A coach that never sleeps. Ask it anything about your spending

Your agent looked solid in the demo. It remembered the user's preferences, carried context across tool calls, and even recovered from a follow-up question without breaking stride. Then the process

IntroductionMost teams try to add memory to an AI agent the same way they add caching: flip on a feature, point it at a store, and hope the agent magically

You want to generate images in your app. The obvious answer six months ago was "call the OpenAI API and move on." But between $0.05 per image at scale, the

You've seen the definition. "Few-shot prompting means giving an LLM a few examples so it can infer the pattern." Technically correct. Practically useless until you see it work — and

The Local TTS Landscape Has Shifted DramaticallyYou need a text-to-speech model that runs locally — no API calls, no data leaving your machine, no per-character billing. Maybe you are building

You spent three weeks building a sophisticated AI agent. You chose the best orchestration framework, tuned your prompts carefully, and connected it to a capable LLM. Then you shipped it

The AI landscape has shifted dramatically in recent years. What started as a niche skill for researchers has become essential for anyone working with large language models. Whether you're building