The Job Positions of the AI Future
The podcast explores how job roles are transforming in an AI-driven future, moving from domain-specific positions to archetypes based on work style and function. Building on Boris Cherny's framework of five product-facing roles (Prototyper, Builder, Sweeper, Grower, Maintainer), the host expands the analysis to include externally-facing roles (Editor, Scout, Evangelist, Orchestrator, Conductor, Risk Steward) and applies these archetypes across different organizational functions.
Summary
The episode begins by clarifying that rather than discussing job displacement or entirely new roles, it focuses on how work is changing as organizations shift from people doing jobs to people managing agents that do jobs. The host uses Boris Cherny's tweet about five work-facing archetypes as a foundation, which emerge based on product lifecycle stage rather than traditional job titles.
The five product-facing archetypes are examined in detail: Prototypers generate many ideas and use code-generating agents to create rapid prototypes, eliminating lengthy discussion phases. Builders transform prototypes into production-grade systems, requiring different mindsets and skills than prototypers. Sweepers optimize systems at a DNA level, cleaning up UI and simplifying code. Growers take built and optimized products to market and iterate based on real-world feedback. Maintainers manage mature systems at scale, ensuring security, reliability, and efficiency.
The host identifies a significant gap in Boris's analysis: the absence of externally-facing and people-focused roles. Six additional archetypes are introduced: Editors decide which prototypes deserve full development given scarce market attention. Scouts observe the real world and bring signals back to inform prototypers. Evangelists market products and help audiences see the world as builders do, working at the intersection of internal and external work. Orchestrators manage how disparate pieces work together across role archetypes and organizational parts. Conductors specifically manage agent teams for coherent outputs. Risk Stewards anticipate and prevent risks before they derail projects, viewed as dynamic forward-oriented roles rather than gatekeepers.
The host then maps these archetypes onto different organizational functions. In Sales, the roles translate to prototypers testing new pitches, builders creating repeatable playbooks, sweepers removing dead scripts, growers iterating on what works, and maintainers creating complete sales systems. Marketing follows a similar pattern with scouts reading audience signals, prototypers testing narratives, editors refining stories, builders creating campaigns, sweepers pruning channels, growers optimizing conversion, and maintainers maintaining brand systems.
Back office functions (Finance, HR, Ops) show different concentration patterns—fewer prototypers and builders, more maintainers—though sweepers and risk stewards remain valuable. The host notes that as making becomes cheaper through AI tools, even back office functions may develop prototyper roles, with people building custom software solutions.
The core argument is that roles are becoming less about narrow job descriptions and more about work archetypes aligned with personality and temperament. The fundamental shift is from doing work to managing agents that do work, with individuals able to push their organizations toward new thinking by becoming the makers in their functions.
About this episode
<p>As AI agents change the shape of work, today’s episode explores the emerging archetypes that may define future organizations — from prototypers, builders, sweepers, growers, and maintainers to editors, scouts, orchestrators, conductors, and risk stewards. NLW argues that the biggest opportunity may be for people in every function to become the “maker” who helps their organization discover what AI-enabled work can actually become.</p><p><strong>Brought to you by:</strong></p><p><strong>KPMG</strong> – Research from KPMG and the University of Texas at Austin shows the highest-impact AI users treat AI like a reasoning partner — and those skills can be taught at scale. Learn more at <a href="kpmg.com/us/Sophisticated">kpmg.com/us/Sophisticated</a></p><p><strong>Hyperagent </strong>-<strong> </strong>Hire a fleet of always-on agents. New users get $1,000 in inference. <a href="https://hyperagent.com/aidailybrief">hyperagent.com/aidailybrief</a></p><p><strong>Rackspace Technology-</strong> One accountable partner to build, operate and run your full enterprise AI stack <a href="https://www.rackspace.com/">https://www.rackspace.com/</a></p><p><strong>Section</strong> - Section turns AI investment into workforce transformation and ROI - <a href="https://www.sectionai.com/">https://www.sectionai.com/</a></p><p><strong>Scrunch -</strong> The AI customer experience platform - <a href="https://scrunch.com/">https://scrunch.com/</a></p><p><strong>Blitzy - </strong>Want to accelerate enterprise software development velocity by 5x? <a href="https://blitzy.com/">https://blitzy.com/</a></p><p><strong>AssemblyAI</strong> - The best way to build Voice AI apps - <a href="https://www.assemblyai.com/brief">https://www.assemblyai.com/brief</a></p><p><strong>Robots & Pencils</strong> - Cloud-native AI solutions that power results <a href="https://robotsandpencils.com/">https://robotsandpencils.com/</a></p><p>The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: <a href="https://pod.link/1680633614">https://pod.link/1680633614</a></p><p><strong>Our Newsletter is BACK: </strong><a href="https://aidailybrief.beehiiv.com/">https://aidailybrief.beehiiv.com/</a></p><p><strong>Interested in sponsoring the show? </strong>[email protected]</p>
Key Insights
- The host argues that the meta shift from doing jobs to managing agents doing jobs represents the common future transition for all organizational roles, requiring people to work backward from what agents can handle to determine what substantive work remains.
- Boris Cherny's five archetypes emerge from product lifecycle stage rather than traditional domain-specific job functions, meaning a designer, engineer, or PM might occupy any of these roles depending on product maturity and team needs.
- The host identifies that externally-facing roles (Editor, Scout, Evangelist, Orchestrator, Conductor, Risk Steward) are missing from Boris's product-focused framework, yet these roles become increasingly important as organizations scale and integrate agent-generated work.
- The host characterizes future risk stewards not as gatekeepers or bottlenecks but as forward-oriented roles that anticipate failures multiple steps ahead and prevent them before projects encounter derailment, inverting traditional risk management perspectives.
- As AI tools make building cheaper, even back office functions like Finance and HR will develop prototyper archetypes, as individuals leverage custom software to solve function-specific problems without waiting for traditional IT cycles, fundamentally shifting how those departments operate.
Topics
Transcript
Today on the AI Daily Brief, the job positions of this new agentic future. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. All right, friends, quick announcements before we dive in. First of all, thank you to today's sponsors, Robots and Pencils, Retool, Blitzy, and Airtable. To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. And if you want to learn more about sponsoring the show, send us a note at sponsors at ai-dailybrief.ai. Today, we are once again turning to the future of jobs. This episode is not about exploring what industries or types of…
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