Voice Fidelity & Corpus Training
Post-Training vs Prompting for Brand Voice Consistency
Fine-tuning rewrites a model's defaults; prompting merely wrestles with them.
Delancey Okafor
Contributing Editor, Voice & Corpus · · 10 min read
High Quality Writing
Adversarial Writing Systems
Prompt Injection Risks in Multi-Model Writing Pipelines
Multi-agent writing systems inherit vulnerabilities from passing unverified outputs between agents.
Delancey Okafor12 min read
Adversarial Writing Systems
Line-Level vs Document-Level AI Writing Review
Different architectures solve different revision problems, not better and worse approaches.
Miroslava Čech10 min read
Adversarial Writing Systems
Comparing Humanization Tools to Adversarial Writing Systems
Humanization tools fail where multi-model systems may succeed.
Delancey Okafor11 min read
Adversarial Writing Systems
Model Diversity and Output Variance in Writing Ensembles
Using multiple models together produces better writing than any single model alone.
Miroslava Čech12 min read
Adversarial Writing Systems
Why Single-Model LLM Output Falls Short for Content Marketing
Multi-model systems capture brand voice where single LLMs default to sounding like everyone else.
Soren Halvgaard11 min read
Adversarial Writing Systems
Convergence Criteria in Iterative Writing Systems
Iterative systems need control loops that catch errors mid-process, not just stronger models.
Soren Halvgaard12 min read
Adversarial Writing Systems
Adversarial Multi-Model Architectures for Text Generation
Multiple models reviewing each other's work beats single-model generation on complex tasks.
Miroslava Čech10 min read
