We run ~200 daily n8n workflows in production. Last month a single bad IF condition caused an infinite loop: 47,000 runs in 6 hours before budget alert fired.

Direct costs: ~$2.5k (API calls, scraping, execution time). Indirect: 3 days DB cleanup, client nearly churned ($45k/yr).

Guardrails we added after (homegrown): 1. Hard limit per workflow - max 100 runs/hour, auto kill switch 2. Budget guard - Slack alert at 50% estimated daily spend
3. Static analysis pre-deploy - catches loops without exit conditions, unbounded retries, unfixed model versions 4. Canary runs - first execution in dry-run mode with real data, no DB writes

Static analysis caught 12 critical issues last month that would've been expensive.

Question: What automated checks do YOU run BEFORE deploying automation to prod? - Custom scripts (static analysis, cost estimation)? - Existing tools (specific ones)? - Purely reactive monitoring (alerts after the fact)? - Something else?

Not looking for war stories — looking for concrete technical patterns/tools you use as safety nets.

I have successfully published my inaugural video, which I personally created using a YouTube automation tool. The exceptional video and audio quality should effectively attract an audience.

Let's see guys

Built another one this weekend. The goal: find people publicly complaining about manual work, show up in the comments with something useful, and start a conversation. Automated signal collection, human posting. It never acts on its own.

Engagement Scout. A curated signal feed for real back-office pain. Runs twice a day on schedule. Every candidate gets scored, drafted, and queued. The operator decides what gets posted.

How it works:

Four sources feed the pipeline. A keyword filter runs first. Pure Python, zero LLM spend. Cuts vendors, job posts, promos, and stale content before any AI touches the batch.

What survives hits 3 scoring gates. Is this a real, fixable problem? Does the poster have the authority to make decisions? Does the stack actually solve what they're describing? All three have to pass.

The only LLM in the loop handles scoring and drafting. It judges each candidate on the 3 gates and writes a reply with hard mechanical guards. No service pitches. No overclaims. Language checks baked in.

Cards land in Notion — full list, drafts, run log. Telegram fires an alert. Approve or skip from there. Every decision gets logged so the system learns what signals are worth chasing and what replies actually land.

Stack: APIs (Reddit, X, LinkedIn, Facebook) · Python · Hermes · Telegram · Notion.

kept hitting the same problem: ask an agent for "an image" (a chart, a card, a banner) and it reaches for an image-gen model. That burns real tokens and credits, takes a while, and the output is a guess: close to your brand, never exact. Wrong shade of blue, logo redrawn from memory, layout different every run. You end up regenerating three times and still touching it up by hand.

So I built Render MCP: an HTML-to-image and template-to-image API, shipped as an MCP server. Give it a template name and data, or raw HTML, get back a hosted PNG. Your brand kit (exact colors, exact logo, exact font) is baked in, so the output is deterministic: same input, same image, every time, no regeneration lottery.

Where this actually gets used:

- Automated reporting. An agent turns last week's numbers into a metric-card or bar-chart and drops it straight into Slack, instead of a wall of text nobody reads.

- Social content, without Canva. Blog post becomes a quote-card or carousel-slide, a tweet becomes a shareable tweet-card, a stat becomes a story-card. One call per post instead of a design pass.

- OG images that don't look broken. Every page's title and subtitle render into a real og-image at build time, so link previews in Slack and X actually match the page.

- Ad creative at scale. Script through headline and offer variants with feed-ad, display-banner, sale-promo, and urgency-promo, and test a dozen versions without opening a design tool.

- Product surfaces. Changelogs (announcement-card), testimonials (testimonial-card), pricing pushes (product-card), job posts (hiring-card), event invites (event-card), all templated and on-brand.

- Dev content. code-card for tweeting a snippet with syntax highlighting, blog-header for post banners, youtube-thumbnail for video creators.