A code-first record of automation pipelines, small web apps, paper trading experiments, and AI-assisted development. Screenshots, commands, and failure notes are the main material.
A fan-out research workflow with adversarial verification: many search agents, then a 3-vote refutation gate. I pointed it at 'is YouTube automation monetization real?' — and it killed most of the claims I wanted to believe.
A solo build log: turning a text script into a finished vertical video with edge-tts and ffmpeg, no paid APIs and no manual editing. Plus the honest part — why production was never the bottleneck.
Not a '$10k/month' post. Three language channels, five auto-generated Shorts, and the honest numbers four hours after upload — plus the one signal that actually mattered.
A two-agent workflow: Claude orchestrates (plan, verify, deploy), Codex generates (design, content). The handoff is a manifest, and the whole thing lives or dies on verification gates.
A fan-out research workflow with adversarial verification: many search agents, then a 3-vote refutation gate. I pointed it at 'is YouTube automation monetization real?' — and it killed most of the claims I wanted to believe.
34 web apps, a handful of paper-trading bots, and a multilingual video pipeline — all run from a 2017 Intel laptop that just stays on. Here's the whole setup and why the old hardware helped.
I built paywalls before checking whether my category was even allowed. Lemon Squeezy, Polar, and Paddle all said no. Then my pivot to ads hit a second wall I'd built myself.
A solo build log: turning a text script into a finished vertical video with edge-tts and ffmpeg, no paid APIs and no manual editing. Plus the honest part — why production was never the bottleneck.
Tailscale lets me watch local bot dashboards from my phone without exposing anything publicly. But tearing a bot down doesn't clear its Tailscale route — here's the gotcha that left dead ports looking alive.
The bots that make real decisions ping me on Telegram. The paper and test bots stay silent by design — a failed send there is expected, not a bug. Signal beats coverage.
The environment I run Claude Code and Codex in went through three stages. Each move solved the same problem: how do you run several agents at once and know which one needs you?
Not a '$10k/month' post. Three language channels, five auto-generated Shorts, and the honest numbers four hours after upload — plus the one signal that actually mattered.
One spec, handed to Codex, covering a full design-system redesign across dozens of apps — then batch-deployed by an orchestrator with a regression gate on the last app before shipping.
The single practice that changed my paper-trading experiments: writing the kill/keep rule down before the data comes in. Gates decided in advance can't be moved to fit a story.
How I let an agent generate content in bulk without free-running it: a SPEC.md with schema and quality bar, one verified pilot batch, then parallel batches gated by a strict schema parse.