Podcast · Tech & Cybersécurité
CEO of Fellow, the AI meeting assistant platform, bringing direct expertise in implementing AI systems at scale across enterprise workflows.
⏱ 8 min read · Readable by ChatGPT, Gemini, Claude
This New Way documents how real companies are building AI into their operations—not through vendor pitches or hypothetical frameworks, but through direct implementation stories from leaders actively testing and adapting. The podcast reveals concrete patterns: content teams updating 100+ pieces in a week using AI, managers replacing guesswork with employee-wide insights, GTM engineers accelerating code updates, and entrepreneurs launching businesses in 40 minutes by leveraging AI tools.
Explore the full This New Way catalog to understand how your industry is adopting AI in practice.
This New Way moves beyond AI theory to examine operational reality. Each episode pairs Aydin Mirzaee with a leader implementing AI in a specific domain—content marketing, GTM strategy, people operations, software engineering, business creation. The pattern that emerges is not "AI replaces humans" but "AI accelerates the parts of the job that humans find repetitive, freeing them to focus on judgment and strategy."
Content marketing guests reveal how AI tools can update 100+ blog posts, product pages, and internal docs in a single week, flagging what needs human review and what can ship unchanged. Engineering leaders show how AI writes 99% of their code while they focus on architecture and debugging. People ops teams use AI to surface employee sentiment and performance patterns that managers missed or didn't have time to collect manually.
The podcast also documents the failures and skepticism. Guests are frank about tools that didn't work, integrations that fell flat, and internal resistance to change. This honesty—acknowledging what failed alongside what succeeded—is what separates This New Way from marketing content. The implicit contract is: you're hearing from people learning in real time, not from vendors or theorists.
Content leaders and marketing teams benefit immediately from episodes on scaling content production, updating legacy archives, and automating routine marketing workflows. The concrete examples—100+ posts updated in a week—directly address the bottleneck most marketing organizations face.
Engineering and GTM leaders will find immediate utility in episodes covering AI-assisted code generation, documentation automation, and rapid prototyping. If your team is evaluating GitHub Copilot, Claude Code, or similar tools, the guests provide real-world rollout patterns and ROI signals.
Managers and people operations professionals gain strategic value from episodes exploring AI-powered employee insights and decision support. Replacing guesswork with company-wide sentiment analysis, performance visibility, and retention signals is a tangible outcome these guests have shipped.
A consistent thread across This New Way episodes is the compression of time-to-value. A business launched in 40 minutes. 100+ marketing pieces updated in a week. Code written, tested, and documented in days instead of weeks. These are not theoretical—they reflect actual outputs from guests who are shipping products and campaigns today.
Another pattern is the iterative nature of success. No guest claims their first AI implementation was perfect. Instead, they describe a feedback cycle: deploy a tool, measure the output quality, refine the process, iterate. This mirrors the way successful software teams work, not the way marketing teams often describe transformations.
A third insight is that AI success rarely comes from replacing a single person or job. Instead, it emerges when a tool reduces the friction of a routine task—freeing a content team to focus on strategy instead of formatting, letting engineers spend time on architecture instead of boilerplate. The leaders who see traction are those thinking in terms of workflow redesign, not just tool substitution.
For content organizations, the implication is that backlogs of stale or outdated content—often deferred for years—can now be tackled at scale. This reshapes content strategy from "create fewer, higher-quality pieces" to "maintain a living library with AI-assisted updates." The time freed from tactical updates can flow toward original research and competitive analysis.
For engineering teams, the shift is from hiring for velocity to hiring for judgment. If AI writes most of the code, the constraint moves upstream—how do you specify what to build, validate output quality, and maintain systems over time? Teams that navigate this transition gain a significant throughput advantage over those still hand-writing boilerplate.
For managers, AI-powered people insights disrupt the annual review cycle. Instead of relying on quarterly check-ins and gut feel, managers can see granular performance signals, team sentiment, and retention risk continuously. This shifts the manager's role from occasional decision-maker to continuous course-corrector.
Discover how your peers are adopting This New Way in your industry.
Listen to This New Way to learn how leading companies are building AI into operations.
Organizations are applying AI across multiple functions: automating repetitive tasks like email and meeting management, accelerating content creation and updates, improving hiring and employee insights, and building rapid prototypes and business models. Leaders are moving beyond theory to test real implementations, learning what works through direct experimentation rather than industry hype.
The gap lies in specificity and iteration. Real AI implementation requires measuring what works versus what fails, adapting processes to fit AI capabilities rather than forcing AI to fit legacy systems, and building feedback loops with teams. Companies seeing results focus on concrete use cases—updating 100+ content pieces in weeks, replacing guesswork with employee data insights—rather than vague transformation narratives.
Content marketers, GTM engineers, managers making people decisions, and software developers are seeing the fastest wins. Anyone managing high-volume repetitive tasks—writing, analysis, code updates, scheduling—can offload or accelerate that work. Managers also gain visibility into company-wide performance and employee sentiment through AI-powered analytics, replacing intuition with data.
Start with a single high-impact problem, not a platform-wide rollout. Test the tool with a small team, measure the time or quality improvement, and decide based on results rather than vendor promises. Most guests reveal they were skeptical until they saw concrete output—a marketing campaign launched in 40 minutes, 99% of code written by AI—then the ROI became obvious.
3 questions answered · 1 episode indexed
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