Quiz: How to Use the Claude API with Python
This quiz checks Claude API Python skills: installing the SDK, client.messages.create(), system prompts, and Pydantic structured output.
Prompt Engineering
Better prompts get better answers. This topic gathers our prompt packs and techniques: how to give context, set a role, ask for structure, iterate on results and build system prompts you can reuse across tools.
Deprecating a Tool No One Invokes Directly
When models read tool descriptions once, API docs become runtime contracts; wording changes affect endpoint selection and lifecycle debt.
MCP’s Largest Update Helped AI Agents Scale—and Transformed a Prompt into a Password.
MCP's stateless update scales agents but exposes handles in prompts; servers must verify signature, audience, expiry, and caller to block hijacking.
Sora 2 has arrived
Sora 2 was a video generation model that turned text prompts into short video clips with synchronized dialogue and sound effects built in—unlike earlier generators that produced silent footage. This i…
Agent Performance Degrades as Context Windows Grow, and Doubling Them Quadruples Attention Cost
Context rot is a gradual LLM decline as prompts grow, driven by transformer attention. Long chats can lose reliability without context engineering.
Accelerating New Topic Mastery with AI: A Personal AI-Assisted Learning Framework
A practical AI-assisted framework helps learners map topics, explain concepts, quiz themselves, and verify ideas before creating notes.
Tokens, Context Windows, and Caching: What You’ve Been Getting Wrong
Claude agents fail on cost and latency from token fragmentation, tool schemas, context growth, and decode. Use count_tokens, caching, short answers.
GPT-5 is now available for developers
GPT-5 is now available on the API platform, bringing significantly stronger reasoning, improved performance on real-world coding tasks like debugging and code generation, and new developer controls fo…
Quiz on Developing LLM Applications with Python
A diagnostic quiz for Python LLM apps, checking APIs, prompts, LangChain, RAG, embeddings, vector databases, agents, and MCP tool connections.
Citing Matthew Green
Sandboxed AI agents can still propagate harmful instructions via shared channels like email, Slack, docs, or Muse, creating a worm-like risk.
Streamlining Financial Processes Using ChatGPT Work
Discover how finance professionals can use ChatGPT as a drafting partner and analytical assistant across four key workflows: monthly reporting commentary, variance analysis, forecasting support, and m…
The Double-Booked Operating Room: How Autonomous AI Schedulers Trigger Race Conditions
AI schedulers double-booked an OR by racing without distributed locks. Prompts can't serialize resources; a gateway must enforce atomic leases.
A Guide to the GPT-6 Model Family
GPT-6 guide for startups: pick models by task, tune reasoning effort, improve prompts and skills, coordinate tools, and prepare production workflows.
How Diffusion Controller Streamlines and Unifies AI Image Generation
Diffusion Controller adds a steering damper to frozen models, improving alignment, supporting gray-box access, and unifying image control methods.
From Prompting to Composition: A Spatial Canvas Interface for Poster Creation
Compo adapts an image editing model to generate posters from a Spatial Canvas, using four bindings for layout, copy, references, and preserved visuals
The Inversion Curse: Why Language Models That Understand “A Is B” Fail to Infer “B Is A”
LLMs may know A is B but fail B is A because next-token training is one-way. Test, prompt, and index both directions to improve retrieval and QA.