The most important moment in a digital transaction may arrive after the screen says it is complete. The buyer is waiting for the goods. The seller is waiting for the money. If either person becomes unsure about what happens next, the software has a human problem to solve.

OpenFarm, co-founded by Gibson Munene and Kevin Kirima, recognised that concern early. Munene dates his involvement from September 2017 to February 2020. Farmers and buyers used the same WhatsApp number for listings and orders, while M-Pesa payments stayed in escrow until delivery was confirmed. A local grocery handled goods as a commissioned agent and offered customers a familiar collection point. ^[1]

It is a revealing choice for a young engineer. Trust was treated as part of the product’s design. The participants needed more than an introduction to one another; they needed a way to move from an agreement to a completed exchange.

Having examined OpenFarm’s possible economic benefits, this series now turns to the conditions that would make those benefits dependable. The supplied account describes the earlier venture without confirming its current operating status. Our question is what this approach would need to sustain trust if developed further, and what Munene’s other work tells us about his attention to that responsibility.

Somebody must answer the difficult call

Imagine a hypothetical order that arrives short of the agreed quantity. The buyer wants the missing produce or an adjustment. The grower believes the full order left the collection point. The person handling delivery has a different explanation. Every participant may feel certain they have done their part.

A useful service needs a way to establish what happened. That could include an agreed record of quantity, confirmation at handover and a clear route for resolving disagreements. OpenFarm’s account identifies delivery confirmation as the condition for releasing payment; it does not explain the full dispute process. That distinction matters to anyone assessing the design. ^[1]

The underlying principle is straightforward. A farmer should know whom to contact, what information to provide and how long a decision is likely to take. The same clarity should extend to the buyer and the local agent. Uncertainty becomes more bearable when a process is understandable.

This is where the human quality of engineering shows itself. An error message may be technically accurate and still leave somebody stranded. A well-designed response helps the user recover, complete the task or understand the remedy available.

There is a related concern in another of Munene’s projects. In April 2019, he and Gerry Migwi built a blockchain-based voting system under the African Blockchain Initiative. His background says it was used for a real student election and checked for double voting against both recorded votes and those awaiting validation. Within that student election, the project addressed a concrete concern: how the system could identify and prevent duplicate submissions. ^[1]

Familiar tools can still leave people out

Using recognised services can make a new product easier to approach. It cannot guarantee that everybody can participate. A person may share a phone, struggle to afford data or require assistance understanding a message. Those circumstances deserve attention at the design stage.

The Kenya National Bureau of Statistics’ summary of the 2024 FinAccess survey reported that 9.9 per cent of Kenyan adults remained financially excluded. Rural youth accounted for 45.5 per cent of that excluded group. The summary also identified lack of a mobile phone and an identity card as significant barriers. ^[2]

These figures describe the wider setting, rather than OpenFarm’s users. They nevertheless pose an important challenge to any service with rural ambitions: the people who could benefit may need different routes into the product.

OpenFarm’s local grocery agent offers one possible place to explore assistance. Its documented role was to handle goods, earn a commission and provide a collection point. ^[1] Helping users understand messages or orders could be an additional role to test, provided it preserves their control. Physical presence alone does not prove that a service is accessible to everyone.

Language and clarity matter too. A fee should be understandable before someone agrees to it. A farmer should be able to establish when payment can be released. The product’s most useful sentence may be the one that prevents an expensive misunderstanding.

A farmer is a customer with choices

There is a respectful way to think about the people a service such as OpenFarm aims to serve. Farmers already have knowledge of their crops, their buyers and the conditions around them. A new service has to earn a place within that knowledge.

Some may prefer an existing trader who offers immediate payment or collection from the farm. Others may value access to an additional buyer. The product becomes stronger when it understands those differences and makes a clear case for the circumstances in which it helps.

Munene’s decision to require no additional app fits that approach. Farmers could list produce by messaging the OpenFarm WhatsApp number. ^[1] This lowered one barrier to trying the service. The next task would be to demonstrate enough value in the trade itself to make someone return.

Listening would remain important in any future development. A complaint about collection time might reveal a practical constraint that the original design missed. A shopkeeper’s concern about storage could lead to a different handover arrangement. Those conversations are opportunities to make a service more accurate to the lives it touches.

Growth that earns another transaction

For this kind of marketplace, repeat use would be an especially meaningful signal. A person returning after a completed trade has made a judgement about the experience. Understanding why people return, and why others leave, would help distinguish lasting value from initial curiosity.

Other useful measures would include payment timing, fulfilled orders, disputes and the costs of helping users. Taken together, they could show whether the service is becoming easier to depend on. Growth that preserves that quality would give the venture a firmer foundation.

Munene’s ALA Check-in System provides another example of designing around follow-up. Residential assistants recorded students each night, and the faculty member on duty could trace anyone missing from the record. ^[1] A school residence and a produce marketplace require different safeguards. Both nevertheless need a way to notice an exception and give somebody responsibility for acting on it.

Any future for the OpenFarm approach would be built through ordinary moments: a clear agreement, produce received as expected, and a fair response when something goes wrong. Munene’s early work shows why those details deserve engineering attention. Making them repeatable would allow a promising product to become part of how people confidently make their living.

Next in the series: Part 6 looks beyond the marketplace to Elimu and Munene’s efforts to make technical learning more accessible.

Read Also: How Gibson Munene Learned to Turn Curiosity Into Useful Technology