What Is a Prompt? How AI Prompts Work in 2026
A prompt is the instruction you give an AI model to tell it what to do. Here is what a prompt actually is in 2026, the parts that make one work, and the prompting techniques worth knowing.
Research Library
AI Research
New architectures, training methods, evaluation science and safety results — explained from the primary paper.
AI research is the work that pushes the field forward — new model architectures, training and post-training methods, evaluation science and safety results. This section explains the peer-reviewed papers and arXiv preprints that matter, distilling the result and why it is significant, and always linking the primary source so you can read the work yourself rather than take our word for it.
- Published
- 22
- Topics
- 10
- Updated
- Jul 10, 2026
Research areas we track
Evaluation
Evaluation, safety, and governance
Benchmarks, red-team methods, bias analysis, risk controls, and policy tests that decide whether AI systems are ready for real use.
Recent coverage SystemsProduction AI systems
MLOps, LLMOps, monitoring, reliability, knowledge infrastructure, and data-quality practices behind durable AI deployments.
PrivacyPrivacy and secure learning
Privacy-preserving machine learning, federated learning, confidential computing, secure aggregation, and synthetic-data limits.
Applied EvidenceApplied AI evidence
Clinical validation, medical imaging, fraud detection, speech recognition, and other domains where measured outcomes matter more than demos.
Latest research explainers
Is ChatGPT Generative AI? Yes — Here's Exactly Why (2026)
Short answer: yes. ChatGPT is generative AI built on the GPT — Generative Pre-trained Transformer — architecture. Here is what that means, how it works, and how it differs from older, non-generative AI.
Source Standard
How research makes the cut
Primary-source first
Claims anchor to papers, standards, regulator material, technical reports, or project documentation readers can verify directly.
Business relevance filter
Coverage favors work with practical consequences: measurement quality, operational risk, governance burden, cost, reliability, or data constraints.
No benchmark theater
Articles separate a paper result from deployment readiness and call out validation limits, assumptions, and failure modes.
Frequently asked about AI Research
What kind of AI research does this hub cover?
We cover peer-reviewed and preprint research with practical significance — architectures, training, evaluation and safety — and link the primary paper for every claim.
How do you decide which papers to cover?
We prioritize research with reproducible results, independent validation or clear downstream impact, citing the source so readers can verify.
Where can I read the original papers?
Each article links the primary paper (arXiv, a journal or a lab publication) directly.