Uploaded May 2026 | Updated September 2026, 3 weeks ago
Click here for full show notes including episode mentions and recommendations: jimrutt.substack.com/p/ep-344-lisa-buckingham-on-hiring
Jim talks with Lisa Buckingham—a veteran HR leader at Vialto Partners, US Soccer, Lincoln Financial, and Thomson—about how the LLM era is reshaping hiring and job architecture, and how companies and workers can roll with the changes.
They discuss:
- Jim and Lisa's shared history in natural language processing labs thirty years ago—and the contrast with today, where "everybody can be an AI expert"
- The kind of people to hire in the age of LLMs: intellectual curiosity, learning agility, and willingness to work differently
- "Trust the machine, but always validate"—the principle of embracing AI while maintaining human oversight
- COVID as an accelerant of technology adoption
- Workforce adoption realities at Vialto—evangelists, pessimists, and the change management challenge
- Shark Tank-style internal AI contests as a model for engaging employees with new tools
- Why the "future of work" is dead
- Programmers and product managers merging roles; job architectures flattening into skills-based, fluid inventories
- AI's historical weight—"as pivotal as electricity"—and the limits of anyone's ability to predict machine learning's trajectory
- Jim's "what, when" framework and the twin failure modes of AI projects
- "Test and learn" as the right posture toward AI transformation, and whose responsibility "what, when" actually is—CEO, CTO, and sales as a coalition
- The productivity multiplier for programmers—7–10x gains—and Jim's argument that demand for software could actually increase total programmer headcount
- Why sales jobs are probably not highly "AI-able" anytime soon, and what salespeople need to communicate to retain relevance
- Lisa's personal use of Claude and Copilot 365
- The leveling effect of AI for non-STEM people
- Jim's argument (since November 2022) that top liberal arts graduates are the most natural prompt engineers
- Lisa's 1999 Georgetown thesis—"Are liberal arts majors the answer to the .com era worker shortage?"—and its uncanny parallel to the 2026 humanities debate
- The education paradox: how Lisa's son was banned from using AI in class but required to be an AI expert for his summer internship
- The calculator analogy, and whether AI in education follows the same arc
- Resistance to the AI voice in writing
- Jim's technique for capturing stylistic tendencies with AI
- The rising costs of frictional bureaucracy and the unreasonable effectiveness of small teams
- What Lisa saw on a recent safari about what AI can't replace, and the choice between evolving and being overtaken
- Learning agility as the core HR question—how to handle employees who cannot or will not embrace AI
- The shifting meaning of "owning your work"
… and much more.
Click here for full show notes including episode mentions and recommendations: jimrutt.substack.com/p/ep-344-lisa-buckingham-on-hiring
Jim talks with Lisa Buckingham—a veteran HR leader at Vialto Partners, US Soccer, Lincoln Financial, and Thomson—about how the LLM era is reshaping hiring and job architecture, and how companies and workers can roll with the changes.
They discuss:
- Jim and Lisa's shared history in natural language processing labs thirty years ago—and the contrast with today, where "everybody can be an AI expert"
- The kind of people to hire in the age of LLMs: intellectual curiosity, learning agility, and willingness to work differently
- "Trust the machine, but always validate"—the principle of embracing AI while maintaining human oversight
- COVID as an accelerant of technology adoption
- Workforce adoption realities at Vialto—evangelists, pessimists, and the change management challenge
- Shark Tank-style internal AI contests as a model for engaging employees with new tools
- Why the "future of work" is dead
- Programmers and product managers merging roles; job architectures flattening into skills-based, fluid inventories
- AI's historical weight—"as pivotal as electricity"—and the limits of anyone's ability to predict machine learning's trajectory
- Jim's "what, when" framework and the twin failure modes of AI projects
- "Test and learn" as the right posture toward AI transformation, and whose responsibility "what, when" actually is—CEO, CTO, and sales as a coalition
- The productivity multiplier for programmers—7–10x gains—and Jim's argument that demand for software could actually increase total programmer headcount
- Why sales jobs are probably not highly "AI-able" anytime soon, and what salespeople need to communicate to retain relevance
- Lisa's personal use of Claude and Copilot 365
- The leveling effect of AI for non-STEM people
- Jim's argument (since November 2022) that top liberal arts graduates are the most natural prompt engineers
- Lisa's 1999 Georgetown thesis—"Are liberal arts majors the answer to the .com era worker shortage?"—and its uncanny parallel to the 2026 humanities debate
- The education paradox: how Lisa's son was banned from using AI in class but required to be an AI expert for his summer internship
- The calculator analogy, and whether AI in education follows the same arc
- Resistance to the AI voice in writing
- Jim's technique for capturing stylistic tendencies with AI
- The rising costs of frictional bureaucracy and the unreasonable effectiveness of small teams
- What Lisa saw on a recent safari about what AI can't replace, and the choice between evolving and being overtaken
- Learning agility as the core HR question—how to handle employees who cannot or will not embrace AI
- The shifting meaning of "owning your work"
… and much more.
