With AI instruments now commonplace in software program engineering, almost two-thirds (60%) of organizations are anticipated to shrink group sizes by 2029. However that doesn’t essentially spell unhealthy information for engineers, in response to Gartner.
Evaluation by the advisory agency suggests the shift towards smaller engineering groups gained’t be a cost-cutting train, however relatively a pure evolution towards extra agile, specialised items specializing in particular areas.
Gartner envisages these smaller groups being composed of specialist product managers alongside consumer expertise (UX) – or agent expertise (AX) designers, and a minimum of one ‘AI-native’ engineer.
Talking to ITPro, Gartner principal analyst Aliyah Camach, mentioned this inflow of AI has prompted a rethink of how enterprises can “actually profit from AI and people working collectively”.
“What we’re seeing is that organizations are taking a look at engineers as AI orchestrators,” Camach informed ITPro.
“One side of tiny groups is that we’re pondering of them as centered on a product or a set of options for a product, so it’s bringing collectively extra of that product administration abilities and experience onto the group.”
The idea of engineers shifting towards extra of an orchestration-style function has develop into a recurring speaking level over the past 18 months. AWS CTO Werner Vogels told ITPro earlier this year that the traditional image of developers as “code monkeys” is fading.
With AI in the mix, developers and engineers can now focus on other tasks, such as quality assurance and testing, Vogels said at the time.
Gartner’s research echoed this, noting that with the technology handling routine technical tasks, this will ultimately free up engineers to focus on “complex problem-solving and innovation”.
With tiny teams, Camach said this will essentially remove a layer of friction for engineers. Simply put, the AI does the grunt work, while engineers have time to focus on product development and refining existing software.
These teams will also have their own remit similar to product development teams, meaning they’re staying in their own lane and not getting dragged into other areas.
“What we’re predicting to be speed or velocity-type gains with tiny teams is that these small teams are fully accountable for the success of their product or feature,” she explained.
“So removing that layer of having additional approvals and coordination is one type of speed gain,” Camach added. “Then another is having fewer people on the team means that there’s less time spent in that communication and handoff type of activity.”
How tiny are we talking?
Naturally, what constitutes a ‘tiny team’ will vary wildly based on the size of the enterprise. Small teams today, also known as ‘two-pizza teams’, typically have between five and eight people, Camach said.
Generally speaking, the shift to tiny teams could take this down to five or six. Some, on the other hand, could end up with just two or three, Camach noted.
“This really varies,” she said. “Some are curious about experimenting with teams of three, and then for others a meaningful reduction in size is down to six.”
Ultimately, these changes will be made on an enterprise-by-enterprise basis, but leaders should be wary of downsizing down too much. These teams should be small enough that they’re agile but also remain effective and have enough diversity of ideas.
Not a cost-cutting exercise
Given that the last two years have seen repeated warnings about AI rendering developers obsolete, some might see a shift to smaller teams and figure this is another excuse to offload staff.
Camach noted that this isn’t a cost-cutting exercise, however. Teams will be smaller, but the consultancy predicts there will eventually be more of these tiny units working away in the background building software.
This is where communication from leadership will be vital in fostering change, Camach noted.
“I think that a huge piece of making this kind of change is communicating really clearly about what it is and is not, and the tiny teams model is not a cost optimization tactic,” she said.
“Rather, it’s a restructuring of teams to best take advantage of AI and human expertise. What we’re seeing with this idea is that team size reduces, but the number of teams may actually stay the same, or may increase, because we’re expecting more demand for complex engineering solutions at organizations.”
Room for juniors
Maintaining robust talent pipelines will also be a key focus with the shift to tiny teams, according to Gartner. If anything, junior engineers will be more crucial than ever to compensate for general attrition and to provide AI-native skills.
This is where the ‘how small is too small’ question comes into play, according to Camach.
“We absolutely believe that organisations need to continue hiring junior talent to build that pipeline for the future,” she said.
“So the way that fits with tiny teams in this context is reducing team size, but not making it too small because if the team size shrinks too much, that can pose risks.”
Long-term, the solution to developing junior talent could lie in apprenticeship-style models, she added, noting that this “could fit really well with the tiny teams model”.
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