development

If you're new to Iroh, my mental model is roughly "Tailscale at the application layer instead of the network layer".
If your question is, "why not just use Tailscale?", look at it from an app developer's perspective. If you want to release an app and have instances of your app be able to easily connect to each other, you could theoretically embeded Tailscale functionality into your app, but then the users of your app need Tailscale accounts, and your app is dependent on Tailscale.
Iroh lets you embed this functionality directly, and provides public fallback relays. If your app gets too big for the public relays, using your own relays is the flip of a switch.

For teams building distributed applications—think real-time collaboration tools, mesh networks, or anything requiring devices to talk directly across the internet—the value proposition is straightforward. Authenticated, encrypted connections with NAT traversal handled for you. No signaling servers to maintain, no TURN infrastructure to fund at scale. According to n0's launch post, roughly 95% of data volume transfers directly between devices, with relays serving only as fallback when firewalls or network configurations make direct paths impossible.

Standards will catch up. I’ve been out of the web standards space for a couple years now, so this is pure speculation on my part. But I imagine that a lot of the efforts to improve the ergonomics of building websites – better CSS shorthands, terser JavaScript syntax, etc. – will become perceived as less important relative to things that actually move the needle on performance, capabilities, etc. At the end of the day, it’s just not very different for an agent to write 3 lines of CSS instead of 1, and anyway using the newer syntax might actually be harder because you have to coach the agent about things that aren’t in its training weights.

A good test suite is, first and foremost, a risk-mitigation measure.
Automated tests reduce the risk associated with changes to an existing codebase - most regressions and bugs are caught in the continuous integration pipeline and never reach users. The team is therefore empowered to iterate faster and release more often.

That’s why we’ve decided to approach the software factory category as infrastructure rather than as a factory product or AI teammate.

I used to load the full Oh My Zsh framework. Then I profiled my shell and found I was pulling in 150+ files to use maybe 10 features. The chef overcooks 👨‍🍳
So I stripped things back. Now I cherry-pick the OMZ plugins I need via Zinit, and fill the gaps with tools that do one thing well. The terminal is Ghostty with a six-line config, the shell is Zsh, and everything below is what makes it feel like home.

Delete Cargo Integration Tests

Drawing on telemetry from over 10,000 developers across 1,255 teams, Faros’ recent landmark research report confirms:
Developers using AI are writing more code and completing more tasks
Developers using AI are parallelizing more workstreams
AI-augmented code is getting bigger and buggier, and shifting the bottleneck to review
Any correlation between AI adoption and key performance metrics evaporates at the company level

Extensive qualitative analysis of enterprise software engineers reveals that AI’s impact on the SDLC is not a simple linear improvement. Instead, it presents a series of profound tradeoffs. While AI successfully accelerates initial code generation and reduces the friction of starting new tasks, the time saved in creation is frequently re-allocated to auditing and verification. This tension may explain some of our own findings: higher AI adoption is associated with an increase in both software delivery throughput and software delivery instability.

the Unix / Linux Environment is a natural candidate, and could be turned into an Agentic harness with a few modifications.

The infrastructure that needs to exist to support this model at scale includes better automated regression detection, artifact-level validation that goes beyond diffing changed lines, reliable and fast environment provisioning, and guardrails that hold up under parallel workloads.

Harrison’s 4 elements of an agent remain – the system prompt, planning tool, file system, and subgents – describing the core loop. This is the core loop the developer controls with the keyboard. The harness manages everything beyond this, the world the developer sits within.

with CmdAtom, a lot of "leader key" mappings will just be unnecessary, bc you can compose macros on the fly.