The Leverage Point

AI is making recruitment fraud harder to recognize, with convincing messages, counterfeit offer letters, impersonated employees, and deceptive video interviews. This edition of The Leverage Point examines why the threat demands attention from management, HR, and security teams. Beyond candidates losing money, organizations face reputational damage, stolen personal information, and potential insider access through fraudulent hires. The episode outlines practical responses: publish clear hiring procedures, provide independent verification channels, monitor employer impersonation, strengthen identity checks, and assign responsibility across departments. Protecting candidates and securing recruitment require coordinated action before a convincing fake offer becomes a costly crisis for everyone involved.

Why do engineering organizations often struggle as they scale from 10 to 100 engineers? This topic identifies three predictable inflection points: around 15 engineers, where informal coordination breaks; around 35, where culture and engineering practices must become explicit; and around 70, where bureaucracy can slow execution. The episode argues that scaling problems are structural, not personal leadership failures. It recommends architecture decision records, stronger onboarding, management development, decision-rights frameworks, explicit ownership, senior engineering density, and deliberate feedback loops to preserve speed, judgment, culture, and purpose as organizations grow

Why do build-versus-buy decisions often go wrong in technology organizations? The episode argues that the choice should not begin with cost, speed, or vendor features, but with one central question: is the capability inside or outside the organization’s zone of differentiation? It outlines common failure modes, including poor cost comparisons, wrong decision ownership, and treating build versus buy as a simple binary. The episode then presents a seven-question framework covering total cost of ownership, urgency, lock-in, vendor risk, internal capacity, reversibility, and AI-specific uncertainty

Organizations are deploying AI faster than governance functions can adapt, creating a critical risk gap. Most companies lack visibility into their AI systems, exposing them to data privacy, liability, IP, and bias risks. The issue isn’t lack of intent but structural misalignment between speed and oversight. Leading organizations address this with cross-functional governance, real-time AI inventories, proportionate risk frameworks, and early-stage impact assessments. The goal isn’t to slow AI adoption—but to move with clarity and control. Those who build governance capabilities now will outperform those waiting for regulatory certainty that may never fully arrive.

As engineering organizations grow, the systems that once helped teams move fast can quietly become the reason they slow down. That is when many leaders decide they need a platform team. But platform teams can become either a powerful source of leverage or a frustrating internal bottleneck. The difference is not just technical skill. It is design, accountability, measurement, culture, and timing. A great platform team treats internal engineers as customers and measures success by developer outcomes, not just infrastructure performance. This article explores what separates platform teams that accelerate organizations from those that unintentionally slow them down.

In this episode we cover:

• Why technical excellence is a poor predictor of management success

• The four failure modes of accidental managers

• Why organizations are structurally complicit in this problem

• A practical framework for making the transition deliberately

Referenced: CEB/Gartner research on IC-to-manager transitions | High Output Management — Andrew Grove

Follow the show: | Connect with Timi Ogunjobi:

SPONSORSHIP: The Leverage Point reaches senior technology leaders—CTOs, engineering managers, and Staff+ professionals—engaged in high-stakes decisions around AI, strategy, and execution. It offers sponsors a focused, credibility-driven channel to connect with an audience that influences real budgets and technology direction. If your product serves serious technical leaders, this is where your message lands with impact. To explore sponsorship opportunities and position your brand where serious conversations happen, let’s connect. Email [email protected]

In this episode we cover:

• Three misconceptions that corrupt the decision before it starts
• An honest account of what Staff Engineering actually demands
• An honest account of what Engineering Management actually demands
• A five-question framework for making the decision with full information
• The hybrid path and what to do if you choose wrong

Referenced: Will Larson — Staff Engineer: Leadership Beyond the Management Track

Follow the show: | Connect with Timi Ogunjobi:

SPONSORSHIP: The Leverage Point reaches senior technology leaders—CTOs, engineering managers, and Staff+ professionals—engaged in high-stakes decisions around AI, strategy, and execution. It offers sponsors a focused, credibility-driven channel to connect with an audience that influences real budgets and technology direction. If your product serves serious technical leaders, this is where your message lands with impact. To explore sponsorship opportunities and position your brand where serious conversations happen, let’s connect. Email [email protected]

In this episode we cover:

• Why a gap exists between public AI confidence and private CTO reality
• Five things technology leaders are privately wrestling with right now
• The ROI measurement problem nobody is solving cleanly
• What the best CTOs are actually doing to navigate this moment
• What this means for engineering managers, Staff engineers, and senior leaders

Key themes: AI governance · Enterprise AI strategy · Technical leadership · Build vs. buy · AI ROI

Follow the show: | Connect with Timi Ogunjobi: ⁠https://www.linkedin.com/in/timiogunjobi/⁠

SPONSORSHIP: The Leverage Point reaches senior technology leaders—CTOs, engineering managers, and Staff+ professionals—engaged in high-stakes decisions around AI, strategy, and execution. It offers sponsors a focused, credibility-driven channel to connect with an audience that influences real budgets and technology direction. If your product serves serious technical leaders, this is where your message lands with impact. To explore sponsorship opportunities and position your brand where serious conversations happen, let’s connect. Email [email protected]

In this episode we cover:

Key themes: Product-engineering alignment ·Roadmap planning · Technical estimation · Cross-functional trust · Engineering leadership

The question to take into your next planning cycle:Did engineering contribute input before the priorities were set — or after?

Who to share this with: Your product manager.Your engineering manager. Anyone who has sat in a roadmap review and felt the gap between what was on the slide and what was real.

Follow the show: | Connect withTimi Ogunjobi: ⁠ Timi Ogunjobi | LinkedIn⁠

In this episode we cover:

Key themes:

• Technical debt
• Engineering culture
• Incentive design
• Knowledge management
• Engineering leadership
• Retention

The one question to take into your next planning cycle: What did we sustain this quarter — and did we recognize the people who did it?

Who to share this with: Any engineering leader who has had the tech debt conversation more than twice. Any product leader who has ever wondered why delivery keeps slowing down. Any engineer who has been told "we'll address that next quarter" for the last four quarters.

Follow the show: | Connect with Timi Ogunjobi: ⁠Timi Ogunjobi | LinkedIn