Co-founder here. Want to add some context on a decision the article doesn't cover: why Slack.
We tested two surfaces early on - a standalone web app and Slack. The web app: clean UI, full control over the experience. But a lot of friction - why open a browser if you can speak to Viktor in the way you speak to your team? Also, in the webapps, users are used to immediate answers. And Viktor needs time to think/work - like your coworker. In slack we're used to longer wait times. In the end - we speak to humans.
Slack won because it's where work already happens. The agent reads the same channels your team does (crucial for the magical moments!), responds in threads, reacts to messages. There's no context switch. When someone asks the agent to "check what John said about the Q3 budget," it can actually go look - because it's already in the channel where John said it.
The tradeoff is real though. You inherit every Slack UX limitation. You can't build custom UI components. Your entire interaction model is text, threads, buttons, and emoji. We've had to get creative - approval workflows through button clicks, rich output through uploaded files, progress updates through emoji reactions. It's constraining, but the constraint forces simplicity that users actually prefer.
The other thing I'd highlight: the skill system is a compounding moat we didn't fully appreciate at first. Every time any user on a team corrects the agent or teaches it something, that knowledge persists for everyone. Six months in, a team's Viktor knows their project IDs, their naming conventions, which endpoints are broken, who prefers what format. A new hire gets the benefit of all that accumulated context on day one. That's not something you get from a chatbot with a system prompt.
The flea-scope's hybrid FPGA/MCU architecture for USB streaming is clever - using FPGA pipelining to handle 100MS/s capture paired with an STM32 for protocol translation is sweet cost-wise. BUT, the 8-bit ADC resolution and lack of input protection networks (compared to Rigol's 1MΩ//20pF frontends with overvoltage clamping) make it risky in case of unattenuated signals.
The Python analysis toolkit using NumPy/SciPy for FFTs instead of baked-in DSP shows cool resource partitioning - could see Jupyter soon.
Boom’s real challenge isn’t just showing they can go supersonic—it’s designing an engine and airframe combo that can operate at scale, hit reasonable ticket prices, and address stricter environmental policies than Concorde ever faced. The XB-1 proves they’re capable of building a small supersonic jet, but the gap between a funded prototype and a viable passenger fleet is enormous. Unless they can tackle those regulatory hurdles (especially around overland noise), keep operating costs competitive, and deliver a new engine that supports their performance claims, we’re still not much closer to a reliable Mach-plus commercial service than we were in the 1970s. It’s progress, but we shouldn’t confuse a cool proof-of-concept with a profitable flight network.
Any case - truly impressed by their persistance. Pushing something for such a long time despite being so far from any commercial traction feels insance to me.
Agree with most of that. yet, I think there is a lot of value in intuitively understanding the 'fors' and the 'ifs' in a way that's different than a combination letters.
Always reminding yourself that 'if' means 'jezeli' (or paste if in your lang) before writing is an extra cognitive load, quite annoying for a kid in the age of dopamine disruption.
We tested two surfaces early on - a standalone web app and Slack. The web app: clean UI, full control over the experience. But a lot of friction - why open a browser if you can speak to Viktor in the way you speak to your team? Also, in the webapps, users are used to immediate answers. And Viktor needs time to think/work - like your coworker. In slack we're used to longer wait times. In the end - we speak to humans.
Slack won because it's where work already happens. The agent reads the same channels your team does (crucial for the magical moments!), responds in threads, reacts to messages. There's no context switch. When someone asks the agent to "check what John said about the Q3 budget," it can actually go look - because it's already in the channel where John said it.
The tradeoff is real though. You inherit every Slack UX limitation. You can't build custom UI components. Your entire interaction model is text, threads, buttons, and emoji. We've had to get creative - approval workflows through button clicks, rich output through uploaded files, progress updates through emoji reactions. It's constraining, but the constraint forces simplicity that users actually prefer.
The other thing I'd highlight: the skill system is a compounding moat we didn't fully appreciate at first. Every time any user on a team corrects the agent or teaches it something, that knowledge persists for everyone. Six months in, a team's Viktor knows their project IDs, their naming conventions, which endpoints are broken, who prefers what format. A new hire gets the benefit of all that accumulated context on day one. That's not something you get from a chatbot with a system prompt.