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How pro bono work in the technology industry can help nonprofits

How pro bono work in the technology industry can help nonprofits
How pro bono work in the technology industry can help nonprofits

Nonprofit leaders want to adopt the best technologies, but they are often hampered by a lack of talent, tools and resources.

At AlleyCorp, our Non-profit organisation ENG(INE) The initiative provides $1 million in engineering support to four nonprofits each year. The donated work hours help nonprofits operate more efficiently, and in return, our engineers benefit from having helped others.

3 Benefits of Pro Bono Work for a Nonprofit

  1. Lending your expertise to a nonprofit organization can make a significant contribution to its mission.
  2. Applying your technical skills in a completely different business context sharpens your decision-making.
  3. Helping in the community can stimulate creativity and inspire new approaches to daily work.

In 2023, we partnered with Teaching Lab, Podsie, Magpie Literacy, and Trans Lifeline to help these nonprofits rethink their tech stacks and find meaningful ways to scale their mission through technology. I hope the lessons and examples from this work can inspire engineers and top talent to dedicate their own time, expertise, and energy to important causes.

Related reading31 companies that donate to nonprofit organizations

Teaching Lab & Magpie Literacy: Supporting Experiments

Teaching laboratoryan organization that trains and supports teachers Educational Technology Ideas, wanted to expand its technical infrastructure to integrate AI.

We initially set out to develop a set of features that would enable a development team within the Teaching Lab to large language models (LLMs) to test edtech tools and pilot them under research-based guidance from teachers and students. However, we soon realized that Teaching Lab’s needs for LLMs needed to constantly evolve. The speed at which Teaching Lab’s development team had to act to redesign features based on feedback collected in real time required a better development experience.

So instead of focusing on a single set of features, we started building tools for experimenting with LLMs and made a number of additional improvements that allowed the team to test a wider range of hypotheses. This meant that with each successive revision, developers could ship products faster.

BI Elster literacy, As an organization that develops digital literacy tools for children in kindergarten through fourth grade, we also set out to develop a machine learning model to solve a specific task: mapping a text to the literacy skills needed to read it, and vice versa. However, we quickly realized that training the model would be an ongoing need and that the organization would benefit from human-in-the-loop tools as well as experiment tracking infrastructure.

In both cases, the investments in infrastructure enabled the organizations to extend what we had built with them and even develop entirely new applications using AI.

Podsie: Prioritizing design

Better design can often solve a problem that you think is purely technical in nature.

The tech team of Podsiea personalized and automated learning tool for spaced repetition (a learning technique) in the classroom, had asked us to build a platform that generated math equations for the early years of high school. The solutions to this worked about 98 percent of the time. We could have spent months, honestly maybe even years, improving this code to get it to a perfect 100 percent, but all we really had to do was rethink our design from the user’s perspective.

This design feature was a feedback loop. By encouraging Podsie to Feedback loop By using the platform that allowed students to report incorrect question/solution sets to remove those prompts from rotation and alert the teacher to the problem, we were able to correct that 2 percent inaccuracy.

The cost of this design solution was also much lower than if we had solved the problem by engineering or rewriting the code. It helped confirm the ultimate value of the feature (instead of spending ages perfecting the functionality) and allowed the Podsie team to rethink the internal structure of their team and recognize the need for a full-time designer.

Sometimes the best thing engineers can do is ask a designer to reframe the problem from scratch. Many of us have learned this lesson the hard way, and it underscores the importance of building a balanced, well-structured team of engineers and designers.

Further informationGiving season has begun. Prepare your company.

Trans Lifeline: Technical Mentoring

Our work with Trans Lifelinean organization that connects trans people with community support, focused on completely overhauling their tech stack. What made this partnership particularly unique, however, was the way our support led to an even more impactful outcome, from a technical Mentoring Perspective.

Our team spent many hours helping Trans Lifeline’s three engineers select a new technology stack that met their business needs, operating budget, and existing knowledge and preferences. The Trans Lifeline team benefited more from the partnership because our team guided them through the process, explaining the variables of each key decision and the subsequent implementation steps. By spending time helping them with this type of decision-making, the team was able to continue to develop their new platform in a self-sustaining manner.

In the first four months of working with the Trans Lifeline team, the biggest success was not building a new engineering network, but connecting our engineers with theirs. It was an inspiring lesson to see the non-technical impact that partnering with a nonprofit can have.

Many philanthropic organizations cannot afford the high salaries and costs of permanent engineers with decades of experience. This means that teams sometimes lack the guidance they need to Promoting young talent and maintain an organization over the years.

Technical mentorship is important and it is an accessible path for any experienced Technical Manager to help a non-profit organization.

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