AM is critical for emergency scenarios. When Hurricane Maria hit Puerto Rico, all our infrastructure was completely devastated.
The only way to receive news or bulletins for weeks was just one remaining AM radio station that kept broadcasting even as the storm hit and their building began to flood.
> Have the courage to go slowly, especially when everyone else is telling you that you need to go fast and cut corners.
I've been struggling to figure out what "slower" would look like when working in industry. If everyone's working 2x faster, how do you slow down meaningfully without getting axed?
I built my own harness on Elixir/Erlang[0]. It's very nice, but I see why TypeScript is a popular choice.
No serialization/JSON-RPC layer between a TS CLI and Elixir server. TS TUI libraries utilities are really nice (I rewrote the Elixir-based CLI prototype as it was slowing me down). Easy to extend with custom tools without having to write them in Elixir, which can be intimidating.
But you're right that Erlang's computing vision lends itself super well to this problem space.
This looks nice, congrats on the launch. I'm trying this at work on Monday, I suffer from this problem for tons of MCP tools that are MCP only, not CLI, and completely fill my context window.
First thoughts: it seems the broader community is moving towards Agent Skills as a "replacement" for MCPs to tackle the context pollution problem.
Agent harnesses like Pi don't ship with MCP support as an intentional design choice. MCP servers[0] are being rewritten as pure CLIs in order to support this new scenario.
Papers like these are much needed bucket of ice water. We antropomorphize these systems too much.
Skimming through conclusions and results, the authors conclude that LLMs exhibit failures across many axes we'd find to be demonstrative of AGI. Moral reasoning, simple things like counting that a toddler can do, etc. They're just not human and you can reasonably hypothesize most of these failures stem from their nature as next-token predictors that happen to usually do what you want.
So. If you've got OpenClaw running and thinking you've got Jarvis from Iron Man, this is probably a good read to ground yourself.
The tasks tool is designed to validate a DAG as input, whose non-blocked tasks become cheap parallel subagent spawns using Erlang/OTP.
It works quite well. The only problem I’ve faced is getting it to break down tasks using the tool consistently. I guess it might be a matter of experimenting further with the system prompt.
I don't know. LLMs are great at writing code; but you have to have the right ideas to get decent output.
I spend tons of time handholding LLMs--they're not a replacement for thinking. If you give them a closed-loop problem where it's easy to experiment and check for correctness, then sure. But many problems are open-loop where there's no clear benchmark.
LLMs are powerful if you have the right ideas. Input = output. Otherwise you get slop that breaks often and barely gets the job done, full of hallucinations and incorrect reasoning. Because they can't think for you.
> That includes code outside of the happy path, like error handling and input validation. But also other typing exercises like processing an entity with 10 different types, where each type must be handled separately. Or propagating one property through the system on 5 different types in multiple layers.
With AI, I feel I'm less caught up in the minutia of programming and have more cognitive space for the fun parts: engineering systems, designing interfaces and improving parts of a codebase.
I don't mind this new world. I was never too attached to my ability to pump out boilerplate at a rapid pace. What I like is engineering and this new AI world allows me to explore new approaches and connect ideas faster than I've ever been able to before.
In the interest of saving myself an hour of time uploading a video, I’ll attest that yes—that street view is as “average day on Pike” as it gets.
To be clear, there are homeless who walk around the area… and Capitol Hill isn’t exactly the nicest area these days. 3rd and Pike isn’t nice. But Seattle in 2025 isn’t real-life World War Z.