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We are taking the games we grew up playing, in courtyards, living rooms, school grounds and around family tables, and rebuilding them as modern hybrid casual experiences for mobile. The goal is not to simplify away what made those games special, but to preserve their character, competition and familiarity while making them more approachable, expressive and enjoyable on a phone.

That means combining the rules and cultural memory of traditional games with today's mobile craft: tactile interactions, satisfying animation, real physics, distinctive characters, fast onboarding and the kind of visual feedback players now expect from polished mobile games. We want each game to feel immediately familiar to someone who grew up with the original, while still being inviting to someone discovering it for the first time.

Two titles are currently in development.

The first reimagines chess around one problem we have seen repeatedly: for a new player, chess can feel abstract before it ever becomes exciting. Thirty-two pieces appear on a board, many represented by similar symbolic forms, and beginners are expected to learn what every piece is, how it moves and why it matters before they can really enjoy the game.

We are changing the presentation without changing the game.

Every chess piece becomes a recognizable character with its own identity, movement and animation, designed so that its role becomes easier to understand at a glance. Knights still move like knights. Rooks still command files and ranks. Bishops still cut across diagonals. Every legal move, rule and strategic possibility remains intact.

Underneath, it is still real chess: tournament-honest and mechanically unchanged. What changes is the way the board communicates with the player.

Movement becomes more expressive. Captures have physicality. Pieces feel alive. The relationship between character and function becomes easier to understand, particularly for children and first-time players. Instead of asking new players to decode the board before enjoying it, the game helps the board explain itself.

The ambition is simple: preserve everything that makes chess deep enough to last centuries, while removing some of the visual and emotional friction that stops people from getting through their first few games.

The first title is planned to ship in the coming months.

The second takes the same philosophy into another traditional game we grew up with. That one is ours to talk about later.

First title in a few months

We are developing bio-inspired soft robots that crawl through rubble, climb broken structures, move through floodwater and, in time, fly across terrain before deploying into spaces too small, unstable or dangerous for people.

The problem is painfully familiar at home in Nepal. After floods, landslides and structural collapses, finding survivors is often not a question of having enough rescuers. It is a question of access: the people you need to reach may be behind metres of debris, inside a flooded room, beneath a collapsed building or deep in a tunnel no one else can safely enter. The recent floods on the Trishuli made that brutally clear, with hydropower tunnels packed with mud, rock and floodwater while crews searched for workers trapped underground.

So instead of one large, expensive rescue robot, we are working toward many small, deliberately low-cost machines that spread through a site together. Walkers squeeze through rubble and voids. Climbers inspect walls, pipes and vertical shafts. Swimmers enter flooded rooms and culverts. Fliers cross open ground and carry sensing where roads have disappeared.

Each robot is a small sensing node. Thermal imaging looks for heat where an ordinary camera sees nothing. On-board vision flags human cues, a face, a hand, clothing, movement or a light, instead of sending hours of raw footage back to an operator. Microphones listen for tapping. Environmental sensors warn about gases before a crew goes in.

We are also exploring micro-motion radar, which picks up the tiny movements of breathing with no line of sight. The technology is real: larger microwave-radar systems have found survivors through rubble, including after Nepal's 2015 earthquake. Our hard question is how much of that fits into a payload small and efficient enough for a soft robot.

Underground, inside concrete or underwater, a link back to an operator cannot be assumed, so obstacle handling, recognition and navigation run on the machine itself. Each robot keeps a rough record of where it has been and what it found, then passes that to its neighbours. It is closer to an ant colony than a fleet of remote-controlled machines.

The robotics and greenhouse projects share the same bio-inspired swarm architecture, but not the same sensor payload.

A rescue robot needs to search for people: thermal vision, cameras, motion sensing and eventually compact radar. A greenhouse robot has a different job. We are developing small mobile sensing units carrying CO2, temperature, humidity, light and other environmental sensors, moving through the crop instead of leaving every measurement to fixed sensors mounted at a handful of points.

That matters because a greenhouse is not one uniform environment. Temperature, humidity and CO2 can change from one row to another, between the floor and the canopy, around dense foliage, beside a vent or underneath artificial lighting. A fixed sensor tells us what is happening where the sensor is. A moving swarm can tell us what is happening across the greenhouse.

Each unit samples the environment as it moves, attaches those readings to a location and shares them with the rest of the group. Together, the swarm can build a live spatial picture of the greenhouse: finding hot spots, humid pockets, low-CO2 areas and other microclimate differences that a sparse fixed network can miss.

Some units carry more than sensors. A small pair of jaws lets a robot act on what it has just seen: a leaf going grey with mould, a lower leaf shading a truss, or the side shoot a tomato plant pushes out every week whether or not anyone has time to remove it. De-leafing and de-suckering are among the most labour-intensive jobs in a glasshouse, and the Dutch answer so far is a single 425 kg machine working its way down the rows. A swarm comes at it from the other end: many small cutters, already standing beside the plant that needs one.

Cutting is the harder half of the problem. Every cut is an open wound, wet for hours, and Botrytis uses leaf scars as its route into the stem, so a blade that walks from plant to plant can carry an infection as easily as a hand can. Where to cut, when to leave a leaf alone, and how a machine keeps its jaws clean between plants are part of what we are researching, not details to be added later.

The same collective behaviour we are developing for search and rescue applies here in a completely different way: many small machines, each carrying the sensors its mission requires, sharing what they learn so the group understands a larger environment.

For rescue, that means searching rubble and tunnels. For agriculture, it means sensors that move through the crop, and the means to act on what they find.

We are building sensor-driven hydroponic and aeroponic greenhouses, for Nepal first and eventually for anywhere that needs more fresh food from less land and water.

The problem is bigger than putting vegetables under glass. Growing reliably means managing a whole living system: the air around the plant, the water at its roots, the nutrients it takes up, the light it receives, the disease developing before anyone can see it, and whether the crop will still have a market when it is ready to harvest.

So we bring all of it into one closed loop. Plants grow without soil in recirculating hydroponic and aeroponic systems, and whatever the plant does not use stays in the loop instead of draining into the ground. Our own sensor network continuously measures what actually decides how a crop develops: light, air and water temperature, humidity, CO2, pH, electrical conductivity, nutrient strength and what the roots are drinking.

Those readings are not there to make a dashboard look intelligent. They drive the greenhouse. Pumps regulate feeding. Misters control the root environment. Fans manage heat, humidity and airflow. Lamps supplement what the sun cannot give. Dosing systems correct pH and concentration. The grower sets the conditions the crop needs and the control system holds the house close to them, day and night, without anyone walking every row to turn a valve.

Over time we want it to do more than hold conditions. We want it to understand what the plants are doing inside them. Cameras and environmental data together look for disease and stress before they spread. Growth models follow a plant through its development instead of treating every day the same. Nutrition models learn from what the crop actually takes up, so feeding follows the plant rather than a calendar. The aim is a house that can answer what normally needs an experienced grower standing beside the crop: is this plant developing normally, is something starting to go wrong, does it need more water, less nitrogen, different light.

One more signal matters: the market outside. A perfect tomato is only useful if somebody needs it the week it is picked, so our market models combine crop cycles with prices, seasonality and demand to inform what to plant, when, and when a harvest is likely to be worth most. That counts especially in Nepal, where mountain geography and seasonal production make fresh supply uneven, and vegetables that are cheap one month are scarce the next.

Closed-loop growing also changes the economics of the land itself: substantially more food from a given footprint on a fraction of the irrigation water, and more still from stacked and vertical systems. We do not want to solve water and land by ignoring energy, so the design leans on natural light, efficient pumps, renewables and climate strategies suited to where the greenhouse is actually built. The point is not to copy an energy-hungry European glasshouse into Nepal, but to take the science of precision horticulture and rebuild it around local economics, materials and conditions.

It shares a stack with our robotics work. The same low-power sensor boards, cameras, thermal sensing, edge intelligence and IoT that help a robot read an unknown space help a greenhouse read a crop. Fixed sensors report single points; mobile sensing can eventually move between plants, inspect leaves and map temperature and humidity, giving the house eyes that travel through the crop instead of staying bolted to a wall.

The work is at R&D stage: building and testing the sensing platform, control loops, nutrient systems, dashboards and plant models against real growing conditions. Next come pilot greenhouses in Nepal. The ambition is not simply to automate farming. It is a greenhouse that knows what its plants need, uses only what they need, spots trouble early and helps growers produce the right food at the right time, on less land, with less water and less guesswork.

Some of what we build starts with the things we wanted as children and never had. This line is our own hardware, designed and built in the studio, from the circuit board to the finished product.

Our drones are multipurpose and designed in-house: the frame, the flight electronics and the software that flies them. They share parts and lessons with the flying units in our robotics research.

The ride-on cars are small vehicles children can actually sit in and drive, the kind we always wanted to ride as kids. Alongside them are mechanical and electronic toys, cars, trucks and dozers that steer, carry and dig like the machines they are modelled on.

We design the printed circuit boards ourselves and 3D print the parts, so the electronics, the mechanics and the software all come from one bench, and any of them can be changed when a design needs to improve.

Our solar cookers are automated and multipurpose: one unit works as both an oven and a cooker. The structure comes from an origami design, so it folds flat to carry and opens to catch the sun, and automation takes over the work that usually needs a person standing beside it.

Further ahead, the same workshop will build advanced fruit pickers, bringing in what we are learning from our robotics research.