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Mike Taylor is an AI Engineer
14
Mentions
13
Articles
6
Outlets
Dec 2025 — Nov 2026
Coverage
Positive
Sentiment
Associated Topics
Companies Covered
Coverage Patterns
How media typically covers Mike Taylor
Article Types
- opinion2
- analysis1
Media Angles
- business1
- product1
- technical1
Narrative Framing
- trend1
- humaninterest1
- breakthrough1
Appears In
Sentiment Distribution
Based on 13 scored articles
Positive 62%Neutral 23%Mixed 15%
Associated AI Models
Claude2Claude Code1ChatGPT1Claude Opus1DSPy1GEPA1
Writes About
Appears Alongside
Articles
Most recent firstArticles Written
Mike Taylor as author
Why I Turned Off ChatGPT's Memory
Every - Also True for HumanscautiousMar 1, 2026
“Author of "Why I Turned Off ChatGPT's Memory" in Every - Also True for Humans”
Also Mentioned In
Referenced in coverage
Latest Models Can Rewrite Prompts
icu.every.topositiveNov 2, 2026
“Author writing about prompt optimization frameworks like DSPy and GEPA for improving LLM performance.”
The skills that make AI agents reliable are identical to the skills that make human teams effective
icu.every.topositiveNov 2, 2026
“Wrote about how managing AI agents requires same skills as managing human teams, and how AI teaches management principles.”
Five Principles of Prompting
icu.every.topositiveNov 2, 2026
“Author who wrote about five principles of prompting and their application as management techniques for humans.”
Every Model Has a Six-month Shelf Life Now
Every - Context WindowneutralNov 1, 2026
“Discusses how to maintain generalist skills while appearing specialized and demonstrates Claude's ability to automate website migration.”
The seven rules for getting Claude and ChatGPT to cite you based on 2,484 tests
icu.every.toneutralOct 27, 2026
“Head of evals at Every who conducted 2,484 tests on how Claude and ChatGPT cite sources based on article characteristics.”
How to Get AI Agents to Recommend Your Articles
icu.every.toneutralOct 27, 2026
“Conducted experiments testing how Claude and ChatGPT agents recommend articles based on 2,484 tests.”
Why Plus One gave way to a shared agent, frontier team experiments, and Mike Taylor's new book on DSPy
icu.every.topositiveOct 25, 2026
“Head of evals at Every who wrote a book on Context Engineering with DSPy and conducted a livestream on measuring agent outputs.”
Opus 5.5
icu.every.topositiveOct 25, 2026
“Tested Opus 5.5 across consulting, knowledge work, and engineering tasks, running recurring benchmark tasks.”
How Microsoft Is Building for a World of Metered Intelligence
EverycautiousJun 15, 2026
“Wrote about Microsoft's approach to metered intelligence pricing and RTX Spark laptop at Build conference.”
What Board Games Taught Me About Working with AI
Every - Working OvertimeopinionpositiveFeb 22, 2026
Thinking about AI product development through board game mechanics—specifically worker placement, area control, and victory conditions—helps overcome creative blocks when building with large language models.
“Teaching a live, beginner-friendly workshop on Claude Code.”
AI ProductsGenerative AIAI AgentsLLMs
What AI Is Teaching Us About Management
Also True for HumansopinionpositiveJan 25, 2026
Management techniques for AI agents and humans are converging, with prompting and clear direction being key skills that belong in business schools rather than solely in computer science labs.
“Writes about how management techniques for AI agents and humans are converging, arguing that prompting belongs in business school rather than computer science.”
AI ManagementPromptingAI AgentsManagement Practices
This Prompt Optimizer Learns From Its Mistakes Like DNA
Every - Also True for HumansanalysispositiveDec 7, 2025
GEPA, a genetic algorithm-based prompt optimizer within DSPy, delivers 25% better performance than other optimization methods using 35 times fewer trials, enabling cost-effective automatic prompt improvement for enterprise applications.
“Wrote about GEPA prompt optimization framework and DSPy for enhancing how you prompt language models.”
LLMsPrompt EngineeringAI InfrastructureGenerative AI