You’ve likely heard of the “10x engineer”, that mythical unicorn that outperforms their peers and single-handedly helps projects launch within the deadline. They might be a meme at this point, but 10x teams are very much a thing.
Can one team of professionals really be so much more proficient than another? Yes. Provided they’re allowed to develop into one. Here are four key areas that ordinary teams struggle with, which 10x teams have mastered.
Key Takeaways:
- Clear ownership drives speed – projects are completed faster when individuals take responsibility for their execution and outcomes.
- Autonomy trumps approval – leadership should guide and advise, while individual team members thrive on decision autonomy.
- Streamlined workflows matter – focusing on task completion and quick, frequent feedback leads to better outcomes.
- Automation multiplies output – leaving repetitive work in the hands of automation systems and AI agents lets team members tackle deep, meaningful work.
Clarity of Ownership
How teams handle ownership is the most decisive feature distinguishing plodding teams from fast-moving ones.
Traditionally, the concept of ownership is vague. Responsibility for a project’s completion is shared between several people, or even several departments. As decision-making is exclusively a group effort, work stalls because meetings need to be set up to resolve disputes and hammer out action plans. Worse yet, problems get passed around instead of being resolved.
Fast teams sidestep these issues by assigning clear, individual ownership. The person in charge takes responsibility for outcomes, not just task completion. Most importantly, they’re given the authority to assemble cross-functional teams and see projects through from ideation to launch. Decisions are made when and where necessary, meaning fewer meetings, less friction, and fewer chances of higher-ups becoming bottlenecks.
Decision-Making Autonomy
Risk aversion is at the heart of slow teams’ decision-making processes. Higher-ups get to make the big decisions, often causing team members lower on the totem pole to spin their wheels. If this sort of culture is pervasive, even day-to-day and inconsequential work stalls while waiting for approval.
Fast teams thrive on autonomy instead. Each member is empowered to make certain decisions and is aware of where this authority stops. Leadership takes on a more advisory role. They set up guardrails and highlight priorities without descending into micromanagement. Other than the most impactful ones, decisions generally aren’t finite. This lets teams seamlessly pivot mid-project if targets or circumstances change.
Workflow Philosophy
Unsurprisingly, ownership and decision-making woes translate into workflow inefficiencies. Tasks get carried out strictly step-by-step, usually only after another round of delays. One team’s output is another’s direct input. Handoffs are unpredictable, so people lose focus when they suddenly have to jump from one high-priority task to another.
Efficient teams take a faster, streamlined approach. They’re already cross-functional, meaning they’re less dependent on outside inputs. They get stuff done faster by prioritizing and completing tasks instead of working on several projects at once. Feedback is immediate and gets acted on much faster. The iteration process is quicker and becomes incremental since core features are already approved and in place.
Automation Approaches
Aversion to risk means aversion to change, so teams that already lag behind are missing out on all the modern force multipliers. Processes are mostly still manual, leading to time wasted on grunt work. Tools work in isolation, and their functions overlap, causing needless expenses. If automation does exist, it’s limited to trigger-based workflows and rarely covers the entire process. People end up spending more time covering the gaps.
10x teams treat automation as a strategic asset. It’s embedded into workflows from day one and uses the latest developments, like AI agents, to noticeably improve efficiency.
Learning how to build an AI agent and utilizing its inherent versatility means few workflows remain unaffected. On a basic level, they handle repetitive tasks like report generation and build testing. However, AI agents can also coordinate otherwise disconnected tools to streamline execution. Most notably, they can provide team members with data-driven insights, forecasts, or optimization suggestions without the need to involve new specialists.
Conclusion
Essentially, some teams are able to perform so much better than others because they have set up systems that make the difference possible. They’re not necessarily smarter or more experienced. Rather, teams that excel do so because they’re empowered, connected, and replace uncertainty with structure.