Since June, Faur Insights has been quiet. That silence wasn’t absence: it was focus.
While client work continued (Grayling, Birmingham Sports Quarter, Visa Europe), our content energy shifted to Applied Comms AI, the practical AI testing lab we launched to document what actually works in communications.
Twelve articles. Real experiments. Transparent failures and proven frameworks.
Here’s what we have built so far.
Building AI Tools
Speed-Building an AI ‘Will My Boss Hate This?’ Detector, Using Lovable
Three hours. No coding experience. A functional stakeholder feedback tool that tests your content through different personas before you hit send. Documented minute-by-minute, including the bugs. The transition from “I wish this existed” to “I built this” is now viable for communications professionals.
Building a LinkedIn Content Creator with Claude Artifacts
Testing Claude’s no-code app builder by creating a LinkedIn content tool offering multiple posting approaches in one structured workflow. The barriers between idea and implementation continue to crumble.
App Building: Our Ground Rules
When building AI tools for communications, we’re solving real problems — not creating unicorn startups. The framework for why, when, and how we build.
Tool Testing
We Tested Grammarly for 18 Months
Real client work. Actual emails, proposals, newsletters. Not a sponsored trial — a genuine evaluation of whether Grammarly’s AI features earn their place in a professional workflow.
ChatGPT’s Deep Research: A Real Comms Challenge
We put ChatGPT’s Deep Research through its paces with an actual communications task. The results? Imperfect, but strong enough to prove worth in specific situations.
Our Tool Testing & Review Methodology
The communications world is inundated with AI tool recommendations from individuals who’ve never used them. Our approach: test on real communications work, or don’t recommend it.
Frameworks & Standards
How Project Folders Transformed Our Workflow
The unsexy productivity multiplier. When OpenAI introduced project folders to ChatGPT (following Claude’s lead), it transformed workflow organisation from chaos to structure. How organised AI workspaces multiply capability.
A Perfect AI Prompt for Media Pitch Subject Lines
Stop agonising over subject lines. This prompt thinks like a journalist — asking the right questions and generating newsworthy subject lines without PR clichés. Iteratively developed, tested on actual pitches.
Prompt Engineering: Our Production Standards
Prompt engineering sounds sophisticated. It’s really just learning to ask AI systems better questions. Our approach focuses on what actually works for communications professionals, tested on genuine tasks: press releases, crisis statements, pitches.
Practitioner Insights
AI in Crisis Communications: Amanda Coleman Interview
“The key is preparation. Use AI now to understand its capabilities and limitations. Build your prompts library when you’re calm. Test on low-stakes issues. Because when a real crisis hits, you don’t want to be experimenting — you want proven tools and workflows ready to deploy.”
Amanda Coleman — who literally wrote the book on crisis communications — breaks down AI’s role across all seven stages of crisis response. Where it helps (monitoring, drafting options, triage). Where it hinders (empathy, judgement, accountability).
From Watson to Lovable: Flipside’s Barney Evison
Flipside’s Managing Director has been experimenting with AI since 2017, long before ChatGPT made everyone an overnight expert. What’s working: SOW generators, user story tools, research assistants. What’s not: automated video generators, content creation tools. Hard truths from years of actual implementation.
FleishmanHillard’s Joyce Higgins on AI in PR
Insights from FleishmanHillard’s approach to integrating AI across their communications practice. Another voice from the frontlines of implementation, not theory.
What We’ve Learned (And Where Next)
These twelve articles represent genuine learning. Not just documenting tools, but understanding where AI genuinely helps communications professionals versus where it creates more problems than it solves.
In October, I completed Imperial College London’s Professional Certificate in Machine Learning and Artificial Intelligence — formalising years of practical experimentation with structured technical knowledge. That combination — two decades of strategic communications leadership backed by proper ML/AI training — remains rare. It’s what lets Faur build systems, not just recommend them.
The archive continues working. Articles published months ago still drive discovery, still solve problems, still provide frameworks. Quality compounds.
But here’s the critical question: where should we explore next?
Applied Comms AI exists to test what actually works for communications professionals. To share failures as openly as successes. To bridge the gap between AI promise and communications reality.
We’ve covered tool building, prompt engineering, crisis applications, and workflow optimisation. We’ve interviewed practitioners who are implementing, not just theorising.
What’s missing? What challenges are you facing? What experiments would be valuable?
Reply to this newsletter, message on LinkedIn, or email directly. The next chapter of Applied Comms AI should address the questions that keep communications professionals awake at night — not just the topics that sound impressive.
Explore the full Applied Comms AI archive: appliedcomms.ai