Evergreen Overview
Prompt engineering is not just about better outputs. In practice it shapes reliability, scope, fallback behavior, and how well an AI system resists misuse when instructions, tools, and untrusted content collide.
Prompt Engineering
Prompt design patterns, instruction hierarchy, and defensive prompt construction.
prompt engineeringsystem promptsinstruction hierarchyguardrailstask decomposition
What matters most
- Instruction hierarchy and role separation
- Clear task boundaries, fallback behavior, and refusal handling
- Prompt structures that support monitoring and repeatable evaluation
Where teams get into trouble
- Overloading prompts with too many responsibilities
- Relying on wording instead of system controls
- Treating prompts as static text instead of part of application design
Who this page is for
- Teams operating prompt-heavy workflows
- Builders refining assistant and agent behavior
- Reviewers trying to connect prompt design to safety and risk
References
Current notes, events, and source material
These items are included because they add useful evidence, framing, implementation detail, or upcoming context for teams working in this area.
Diagnose prompt-cache misses without widening an agent’s tool access
OpenAI’s prompt-caching guidance explains how to compare requests for changes that invalidate shared prefixes, place explicit breakpoints, and preserve tool definitions while changing which tools are callable. GPT-6 can also receive appended reasoning-effort updates without rewriting the earlier prefix. Workload savings still need measurement.
Teen-safety policy prompts: adapt labels and regression-test the classifier
OpenAI’s Teen Safety Policy Pack supplies prompt-based classification policies and matching validation datasets for gpt-oss-safeguard. The six initial areas cover risks including dangerous activities, harmful body ideals and age-restricted goods. Developers map the policy labels into filtering, review or monitoring workflows and can adapt the prompts to their application. These inspectable starting materials do not provide comprehensive protection or establish performance on a particular product’s users and content.
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Skill engineering: independent reviews, edit hooks and rule-level evaluations
AI Engineer’s notes from Paul Bakaus’s workshop explain separate visual and deterministic reviews, selective instruction loading, edit hooks and rule-by-rule ablation tests. They distinguish blocking pre-tool hooks from post-edit feedback, describe portability failures, and retain human judgment because aesthetic evaluators can reward the wrong behavior.
Understanding prompt injections: a frontier security challenge
An accessible explanation of prompt injection risk in real AI products, including how third-party content can redirect or manipulate agent behavior.
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When Will AI Models Blackmail You, and Why?
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OpenAI to acquire Promptfoo
OpenAI announced plans to acquire Promptfoo, highlighting automated AI security testing, red teaming, and evaluation as core enterprise requirements.
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New OpenAI Model 'Imminent' and AI Stakes Get Raised (plus Med Gemini, GPT 2 Chatbot and Scale AI)
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Claude 3.7 is More Significant than its Name Implies (ft DeepSeek R2 + GPT 4.5 coming soon)
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AI Improves at Self-improving
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AI CEO: ‘Stock Crash Could Stop AI Progress’, Llama 4 Anti-climax + ‘Superintelligence in 2027’ ...
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GEPA: use execution feedback to improve prompts and agent programs
Lakshya Agrawal’s publisher notes describe GEPA’s reflective search: inspect execution traces and errors, propose text changes, score candidates, and retain alternatives that work well on different examples. Optimize Anything extends the editable object from prompts to programs, skills and policies. The reusable method depends on informative feedback and a suitable evaluator. The talk’s large benchmark gains lack complete evaluation protocols in the presentation, so they do not establish a universal advantage over reinforcement learning.
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How Far Can We Scale AI? Gen 3, Claude 3.5 Sonnet and AI Hype
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AI Declarations and AGI Timelines – Looking More Optimistic?
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11 Major AI Developments: RT-2 to '100X GPT-4'
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'Show Your Working': ChatGPT Performance Doubled w/ Process Rewards (+Synthetic Data Event Horizon)
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9 of the Best Bing (GPT 4) Prompts
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