AI Briefing#prompt-engineering
The latest AI and developer news about #prompt-engineering, with the original source and a short summary.
The latest AI and developer news about #prompt-engineering, with the original source and a short summary.
A VSCode/OpenCode tool that visualizes and controls the context AI sees
A reference implementation of the five-stage structure of context engineering, built with a Bedrock example.
AI automation boosted travel product registration speed from 20 per day to over 5,000.
6 tips for Claude Code: auto-allow, recaps, focus mode, and verification.
Released a pre-critique skill to prevent agents from over-complying.
Role, process, standards, and honesty—not 'unlocking'—determine output quality.
Assume LLMs hallucinate, loop, and ignore tools — wrap them with subagents and scripts.
It compresses the context of each LLM call into a Manifest to auto-bootstrap the evaluation stack.
Rewriting a 13KB KB alone raised the Llama 3.1 8B extraction success rate from 60% to 100%.
The solution to agent problems is not the prompt but the operating structure.
Built a paper-based web app with Qwen3.5 35B and confirmed it maintains context well up to 70-80K tokens.
In investment research, a chain that enforces a fixed task order works better than an LLM's default reasoning.
Introducing PEACE, a local chat app that bypasses its way into implementing Claude-style thinking in small models.
Google has released Gemini 3.1 Flash TTS, enabling voice style control through prompts.
Emotional prompting effects across the Claude model lineup were compared through 1,000 experiments.
By splitting documents and rules into smaller injections, Gemini-based TC automation became a practical part of daily work.
Claude Code is not a conversational AI but an execution structure that runs on Agent, Skill, and Context.
It turns MCP schemas into Python modules and maintains research memory across sessions.
The LLM judge favored patches that 'looked like gold,' distorting benchmark scores.
Caveman for Claude Code and Codex compresses answers to cut output tokens by about 75%.
Introduces the basic usage of ChatGPT, your first conversation, use cases, and voice features.
ElevenLabs unveiled the Eleven v3 model, which allows fine-grained control over a voice's emotion and delivery through audio tags.
LLM-based conversational AI requires specialized prompt design that accounts for tone, assumptions, latency, and other characteristics of voice interaction.
The overnight memory feature worked well, but it exposed weaknesses in memory protection, verification, and write methods.