| | | 🔗 Stories, Tutorials & Articles | | | | | | | Zen: A Minimalist HTTP Library for Go | | | | | Unkey built Zen - a thin HTTP framework on Go's net/http. It restores precise middleware ordering and lets middleware run after errors to capture the final response.
Zen pools Session objects to cut allocations. It emits RFC7807 problem+json for tagged domain errors. It runs OpenAPI validation before handlers.
The team prefers a schema-first OpenAPI flow with generated types. They keep external deps minimal. Code lives at github.com/unkeyed/unkey. |
| | | | | | | | | | I deleted my laptop from my dev workflow. My iPhone does the job now | | | | | A developer ditches the laptop and SSHs from an iPhone into an always-on Mac Mini.
The phone becomes a terminal and browser. The remote runs the dev server, the Claude Code/Codex CLI, hot reload, file watching, and pushes via Tailscale.
Persistent sessions (tmux) keep AI agents and services alive across dropped connections. Neovim, lazygit, bat, and fzf make phone terminals usable. |
| | | | | | | | | | The Great Developer Divide: How AI Is Reshaping the Software Job Market Into Three Tiers | | | | | AI hiring has split dev work into three camps: Apex Tier, Hybrid Middle, and a shrinking Automatable Tail. Demand now favors AI orchestration, prompt engineering, fast code reading, and platform roles like platform engineer, fleet supervisor, and AI QA.
System shift: Organizations must rework career ladders, tighten platform stability, and refactor tooling to enable orchestration-centric hybrid roles. Ignore the change and hiring will outpace structure. |
| | | | | | | | | | We Might All Be AI Engineers Now | | | | | | The author supervises AI agents that orchestrate concurrent graph traversal, multi-layer hashing, AST parsing, and file system watchers. The agents run traversal, hashing, and watcher loops. The engineer architects system behavior, verifies outputs, and probes agents in parallel to debug. |
| | | | | | | | | | Build agents that run automatically | | | | | Agents trigger from schedules, Slack, Linear, GitHub, PagerDuty events, or custom webhooks.
They spin up cloud sandboxes. They run configured MCPs and models. They verify outputs. They use a memory tool.
Cursor automates security audits on pushes. Scores PR risk and auto-approves low-risk changes. Runs PagerDuty and Datadog triage that proposes PR fixes. Creates tests. Sends weekly digests.
System shift: Autonomous agents run builds, tests, audits, and triage in isolated cloud sandboxes. CI shifts toward continuous, agent-driven maintenance. |
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