Lesson 626 of 1596
Ollama Context Windows: Set Them Deliberately
Ollama local coding workflows often fail because the effective context is too small or too large for the hardware.
Creators · Tools Literacy · ~24 min read
Ollama Context Windows: Set Them Deliberately
Ollama local coding workflows often fail because the effective context is too small or too large for the hardware.
- 1Name the job before naming the tool.
- 2Write the smallest useful scope the agent can finish.
- 3Run the result as a user, not as a fan of the tool.
- 4Inspect the diff, data access, and failure path before sharing.
Use this as the working prompt or checklist for the lesson.
Check the model card. Set num_ctx deliberately. Test the same coding task at 4k, 16k, and 32k context and record accuracy plus latency.- What should the user be able to do when this is finished?
- What data should the app or agent never expose?
- What test proves the change works?
- What rollback path exists if the output is wrong?
Key terms in this lesson
End-of-lesson quiz
Check what stuck
8 questions · Score saves to your progress.
Tutor
Curious about “Ollama Context Windows: Set Them Deliberately”?
Ask anything about this lesson. I’ll answer using just what you’re reading — short, friendly, grounded.
Progress saved locally in this browser. Sign in to sync across devices.
Related lessons
Keep going
Creators · 45 min
OpenAI Use-Case Playbook: Match the Surface to the Job
OpenAI now spans chat, coding agents, APIs, images, realtime voice, search, files, and tools. Learn which surface belongs to which kind of product.
Creators · 9 min
Perplexity For Journalism And Fact-Checking
Reporters use Perplexity for the same reason librarians do: it shows the trail. The trick is using it for source surfacing — not for deciding what's true.
Creators · 8 min
Switching The Underlying Model In Pro
Pro lets you pick which LLM Perplexity uses for the final answer. The choice shifts tone, depth, and refusal behavior — sometimes more than the search itself.