Side project ideas: real-world problems to solve

Who lives with itOwners of small businesses without a security team · the IT and web suppliers that set up and look after their systems · customers whose data is taken in a break-in · the banks and insurers that carry the losses

Why nowAn ENISA survey of small and medium enterprises, carried out during the pandemic, found that around nine in ten expected serious harm to their business within a week of a cyber incident and that over half believed it would likely end the business, against a backdrop of low security budgets and a lack of in-house cyber skills. BleepingComputer reported on 23 September 2026 that the security firm Gambit traced one operator who used open-source AI agents to breach at least 27 companies in five days and take more than 600,000 card records, at an average of $25.46 per completed scan. The UK government's Cyber Security Breaches Survey, published in April 2026, shows the defending side split by size: 76% of large businesses had a formal plan for handling an attack, against 21% of micro businesses

Why it mattersAn existential risk to the firms that make up the overwhelming majority of businesses, where the binding constraint is operator time rather than money or intent. Security that needs nobody to watch it is a different product from the one being sold. Security products assume someone to run them: alerts to sort, tests to commission, fixes to make. Small firms buy what their IT or web supplier offers, and many already pay one for security. A small team could start with one case where the stakes are clear, such as small online shops whose checkouts draw card thieves: constant, automated checks of the site, priced for a small firm and sold through the suppliers that already look after it.

Who lives with itClerical, administrative and business support workers · employers holding the institutional knowledge in those roles · public employment services

Why nowThe ILO finds 29% of female-dominated occupations carry exposure to generative AI against 16% of male-dominated ones, with exposure reaching around 41% of jobs in high-income countries versus 11% in low-income ones, and women more exposed than men in 88% of the countries analysed.

Why it mattersThe measurement is done and the response is missing, which is an unusually clear place to build. Mapping what an exposed role actually contains onto roles needing those same capabilities is a matching problem, and matching problems are tractable.

Who lives with itTeachers and lecturers redesigning assessment alone · students wrongly suspected · institutions whose credentials depend on the answer

Why nowA UNESCO survey found 19% of higher education institutions had formal AI guidance with a further 42% developing it, while more than half reported uncertainty about how to apply AI pedagogically and one in four had already encountered ethical problems including authorship disputes.

Why it mattersThe question has moved from catching misuse to evidencing learning, and nothing is built for the new question. Making a student's reasoning visible, cheaply and without treating them as a suspect, solves what detection never could.

Who lives with itGrowers and packers · distributors and independent retailers · redistribution charities working the same corridors

Why nowFAO estimates that 13.3% of the world's food was lost in 2023 after harvest and before retail, on farms and in transport, storage, wholesale and processing, up slightly from 13.0% in 2015 when global monitoring began.

Why it mattersMeasurement at the handover is the wedge, and it is cheap: the produce is already photographed, weighed and scanned on both sides of every transfer. Nobody is joining those records, because each side owns only its own.

Who lives with itCustomers in genuinely unusual situations · the few remaining human agents · support leaders flying blind

Why nowAutomated support is now the default first line almost everywhere, while the escalation path behind it has often been thinned.

Why it mattersThe savings are measured precisely and the losses are invisible entirely, which is why the balance keeps tipping the wrong way. Detecting the moment a conversation has stopped working is a narrow, concrete capability, and whoever builds it is selling the missing half of every deployment.

Who lives with itOwners of trades, care and hospitality businesses · local jobseekers and career changers · the boards that serve neither well

Why nowHiring has concentrated onto national platforms optimised for volume and for employers who can pay to be seen, which is the opposite of what a local employer with two vacancies needs.

Why it mattersThis is a matching failure rather than a shortage, and matching failures are solvable. Local, skills-first matching remains underbuilt because the large platforms are built for a different customer.