#2026-W19 --- ### Host T1 Build I’ve finally completed the **Host Tier 1 build** I’ve been working on for the past month. I managed to reprint most of the parts and reconfigure the hardware so I wouldn’t have to rebuild the entire machine from scratch, so I’m still using the original board and components. Before I try to make my own PCB, I wanted to create a prototype version to fine-tune the last few issues in the overall build. ![[host-t1-inside.jpg]] > *A rare glimpse into the internals of the machine* ![[host-t1-3d.jpg]] ![[host-t1-specs.jpg]] The biggest change is actually those barely noticeable new feet and their *force sensors (FSR).* I had to modify the design of the feet to route the cables, as well as the shape of the tips and the foot itself. I looked for a suitable material and settled on TPU 95A, shaped like a harmonica, which both absorbs shocks and *(relatively)* reliably presses against the sensor that registers touch. I have a feeling it will go through another revision, but for now it’s functional. From the perspective of the *machine’s perception,* the biggest new addition is the lidar, which allows for continuous scanning of the floor plan around the robot. As a result, it can walk much more safely and avoid obstacles. For the scan to be useful, the robot also needs to know which way it’s facing, so I added a 9-axis IMU *(accelerometer + gyroscope + magnetometer)* that gives it a stable sense of orientation. ![[host-t1-dasboard.png]] > *Realtime Web Dashboard ^* --- ### Speak, agent. Another small experiment with my [agent](https://kindl.work/Resources/Second+Brain+Builder). I quite often find it more comfortable to speak than to type, especially when I’m describing something half-formed or when I work in the same time. For dictation I’ve been using [Wispr Flow](https://wisprflow.ai/) and the open-source [OpenWhispr](https://github.com/OpenWhispr/openwhispr); both turn speech into clean text in any field on the system. The new addition is the other direction: a local text-to-speech wrapper built on top of [Kokoro](https://huggingface.co/hexgrad/Kokoro-82M) *(a small open-source model, English only)* that lets the agent read its answers back to me. There’s something weirdly pleasant about that, the back-and-forth feels closer to a real conversation than pure text. I’ve also started using it to narrate *longer deep-research reports* while I work on something else. Every spoken message gets archived as a timestamped MP3 in a local folder, so I can scroll back and replay anything later.