Choose Your Team, Not Just Your Tools

What if the next five years of your career isn't defined by which AI you use, but by who you're working with?

In this episode of KP Unpacked, KP Reddy and Nick unpack the quiet revolution happening in management consulting. OpenAI just launched a deployment company and acquired a consulting firm. Anthropic is backing enterprise AI consultancies. PE firms are partnering with AI-enabled consultants and offering equity instead of hourly fees. The result? Three tiers of value capture emerging: billable hours (worst talent), risk-based fees (middle tier), and equity models (where the best people go). If you're still getting paid by the hour to do AI transformation work, you're in the bottom tier.

But the deeper insight is about career trajectory. KP argues the next five years aren't defined by how good your Claude skills are. They're defined by who you're sitting next to. Are you in a firm where Opus 4.8 launching makes everyone's Slack light up with memes and excitement? Or are you somewhere people still think AI is a threat? The gap between those two environments is the gap between relevance and obsolescence. The conversation also unpacks skills files as potentially employee-owned IP (not company-owned), why structural engineers still double-check software calculations in Excel despite working for billion-dollar firms, and why Zero's training program spends two-thirds of its time on mental models and thinking frameworks, not AI mechanics.

Key questions answered:

• Why are OpenAI and Anthropic launching consulting practices and partnering with PE firms?
• What are the three tiers of value capture in AI consulting (billable hours, risk fees, equity)?
• Where does the best consulting talent go: hourly billing or equity models?
• Do you own your skills files, or does your company?
• Should companies make employees sign IP agreements for marketing coordinators building AI workflows?
• Why do structural engineers still double-check software calculations in Excel?
• What's Zero's training curriculum focused on: AI tools or thinking frameworks?
• Why does ambition and optimism matter more than technical AI skill?
• How should you choose between working at a forward-leaning AI firm versus a traditional one?
• What happens when Opus 4.8 launches: does your team's Slack light up or stay silent?
• Why would you sell a $250M/year AI consulting firm when you're banking $50M annually?
• What's Ramp tracking now: token spend by industry?

If you're deciding between firms based on AI adoption, wondering whether your skills files are actually your IP, or trying to figure out whether billable hours still work in an AI-enabled consulting world, this episode will make you realize the technology matters less than the ambition and optimism of the people around you.

Listen now.