Not everyone reacts the same way to agentic development. Some teams adopt eagerly: they’re experimenting within days, sharing prompts, iterating on workflows. Others hold back: they use the tools sparingly, if at all, and express skepticism or anxiety about what it means for their roles.

The difference isn’t random. Certain conditions predict lean-in versus resistance. Understanding them helps you cultivate desire before the rollout, not after.

What Predicts Lean-In

Identity rooted in outcomes, not mechanics.
People who define themselves by what gets built—“I ship products that users love”—tend to embrace agents. The agent is a means to that end. People who define themselves by the mechanics—“I write clean code,” “I’m a React expert”—feel more threatened. Their identity is tied to the work the agent now does. Desire grows when we help people reconnect their identity to outcomes: craft, judgment, coherence.

Psychological safety and experimentation culture.
Teams that already try new tools, share learnings, and tolerate failure adopt agents faster. The agent is “another thing to try.” Teams with high stakes, blame culture, or rigid processes see agents as risk. Building desire means building safety first—or rolling out in the safest corners of the org.

Autonomy and ownership.
People who control their own workflow can integrate agents on their terms. They experiment, refine, and adopt. People whose work is heavily prescribed—tickets, strict processes, approval gates—have less room to play. Desire emerges from agency. Where possible, loosen the reins so people can own their adoption path.

Visible upside.
When early adopters share concrete wins—“I shipped this in half the time,” “the agent caught an edge case I missed”—others see the upside. Abstract promises (“AI will make you more productive”) don’t land. Desire is contagious when the benefits are specific and visible.

What Predicts Resistance

Fear of obsolescence.
”If the agent can do my job, what happens to me?” That fear is real. Addressing it requires the queue-to-craft narrative: your job isn’t going away; it’s shifting. The premium is on judgment, not implementation. Desire won’t grow until that fear is acknowledged and reframed.

Loss of competence.
People who’ve invested years in skills that agents now replicate can feel devalued. Desire requires a path forward: new skills, new roles, new ways to contribute. “Your expertise in X is now table stakes; here’s where you add unique value” is the message that unlocks desire.

Distrust of outputs.
Some resistance is rational. “I’ve seen the agent hallucinate. I don’t trust it.” Desire follows trust. Trust follows quality: good tooling, good defaults, good feedback loops. Investing in quality and transparency—“here’s how we validate agent output”—reduces rational resistance.

Cultivating Desire Before Rollout

Don’t assume desire will emerge after the tool ships. Create the conditions first: narrative alignment, psychological safety, early wins for willing experimenters, and honest conversation about fear and identity. The teams that lean in are usually the ones where those conditions were already present—or intentionally built.