blog-writing-guide

This skill enforces Sentry's blog writing standards across every post — whether you're helping an engineer write their first blog post or a marketer draft a product announcement.

The bar: Every Sentry blog post should be something a senior engineer would share in their team's Slack, or reference in a technical decision.

What follows are the core principles to internalize and apply to every piece of content.

We sound like: A senior developer at a conference afterparty explaining something they're genuinely excited about — smart, specific, a little irreverent, deeply knowledgeable.

We don't sound like: A corporate blog, a press release, a sales deck, or an AI-generated summary.

Be technically precise, opinionated, and direct. Humor is welcome but should serve the content, not replace it. Sarcasm works. One good joke per post is plenty.

Use "we" (Sentry) and "you" (the reader). This is a conversation, not a paper.

Never use these. They are automatic red flags:

• "We're excited/thrilled to announce" — just announce it
• "Best-in-class" / "industry-leading" / "cutting-edge" — show, don't tell
• "Seamless" / "seamlessly" — nothing is seamless
• "Empower" / "leverage" / "unlock" — say what you actually mean
• "Robust" — describe what makes it robust instead
• "At [Company], we believe..." — just state the belief
• "Streamline" — everyone is streamlining, stop
• Filler transitions: "That being said," "It's worth noting that," "At the end of the day," "Without further ado," "As you might know"
• "In this blog post, we will explore..." — be direct, just start

The opening must do one of two things: state the problem or state the conclusion. Never start with background, company history, or hype.

Good: "Two weeks before launch, we killed our entire metrics product. Here's why pre-aggregating time-series metrics breaks down for debugging, and how we rebuilt the system from scratch."

Bad: "At Sentry, we're always looking for ways to improve the developer experience. Today, we're thrilled to share some exciting updates to our metrics product that we think you'll love."

Structure every post around what the reader is actually wondering, not your internal narrative:

1. What problem does this solve? (1-2 paragraphs max)
2. How does it actually work? Not buttons-you-click, but underlying technology. (Bulk of the post — be specific)
3. What were the trade-offs or alternatives? (This separates good from great)
4. How do I use/try/implement this? (Concrete next steps)

For engineering deep-dives, also address: 5. What did we try that didn't work? (Builds trust) 6. What are the known limitations? (Shows intellectual honesty)

People scroll. Shorter paragraphs are almost always better for keeping people reading.

Break paragraphs at contrast points. When a sentence introduces a "but," "however," or shifts perspective, start a new paragraph. Don't bury the turn inside a block of text.

Bad:

Traditional monitoring tracks requests and latency. That works for stateless HTTP services. AI agents are different. A single run might involve multiple LLM calls, tool executions, and handoffs.

Good:

Traditional monitoring tracks requests and latency. That works for stateless HTTP services.

AI agents are different. A single run might involve multiple LLM calls, tool executions, and handoffs.

The line break before the contrasting point creates visual emphasis. This is standard in online writing even though it breaks traditional paragraph rules.

One idea per paragraph. If a paragraph covers two distinct points, split it. Three-sentence paragraphs are fine. One-sentence paragraphs are fine for emphasis.

No em dashes. Use commas, periods, or line breaks instead. Em dashes are fine in print but create visual clutter in blog formatting.

When targeting a competitive search query:

Lead generic, close specific. The first 50-60% of the post should be tool-agnostic educational content (definitions, concepts, metrics, best practices). Introduce your product as an implementation example in the second half. Google ranks guides higher than product pages for informational queries.

Put keywords in H2s. Generic headings are invisible to search. "Key metrics for AI agent monitoring" beats "What to measure." (See Section Headings below for good/bad examples.)

Include a definitional section. For any head term ("agent observability", "error monitoring"), top-ranking pages almost always have a "What is X?" section. Include one even if it feels basic.

Add an FAQ. 3-4 questions targeting long-tail keywords at the bottom of the post. These can win featured snippets and People Also Ask boxes.

LLM-generated prose has tells. Flag and rewrite these:

Staccato dramatic fragments.

• Bad: "No errors. No warnings. Everything green."
• Good: "There were no errors, no warnings, everything looked fine."

Bumper-sticker aphorisms.

• Bad: "You can't fix what you can't see."
• Good: "Without visibility into the full request lifecycle, you're guessing."

Three-beat reveals.

• Bad: "Not a config issue. Not a code bug. The deploy was stale."
• Good: "It wasn't a config issue or a code bug. The deploy was stale."

Smug simplicity.

• Bad: [code block] "That's it. That's all you need."
• Good: [code block] then explain what the code does, or just move on.

Parallel structure ad copy.

• Bad: "Metrics tell you what's broken. Traces tell you why."
• Good: "Metrics show what's broken, but traces are where you'll actually figure out why."

Personality only in the bookends. AI drafts open with a personal anecdote, go impersonal for 80% of the post, then close with a CTA. The author's voice should persist throughout.

• Bad: Personal intro → clinical middle → "Try Sentry for free."
• Good: First-person asides woven through the post: "this is the part that tripped me up" / "I would have blamed the wrong service."

Weak: "Background," "Architecture," "Results," "Conclusion"

Strong: "Why time-series pre-aggregation destroys debugging context," "The scatter-gather approach to distributed GROUP BY," "Where this breaks down: the cardinality wall"

Numbers over adjectives. If you make a performance claim, include the number.

• Bad: "This significantly reduced our error processing time."
• Good: "This reduced our p99 error processing time from 340ms to 45ms — a 7.5× improvement."

Code must work. If a post includes code, test it. Include imports, configuration, and context. Comments should explain why, not what.

Diagrams for systems. If you describe a system with more than two interacting components, include a diagram. Label with real service names, not generic boxes.

Honesty over hype. Never overstate what a feature does. Acknowledge limitations. If something is in beta, say so. If a competitor does something well, it's okay to note that. Do not claim AI features are more capable than they are — "Seer suggests a likely root cause" ≠ "Seer finds the root cause."

The title is the highest-leverage sentence in the post. It must stop a developer scrolling through their RSS feed or Twitter.

Strong titles make a specific claim, tell a story, or promise a specific payoff:

• "The metrics product we built worked. But we killed it and started over anyway"
• "How we reduced release delays by 5% by fixing Salt"
• "Your JavaScript bundle has 47% dead code. Here's how to find it."

Weak titles are vague announcements:

• "Introducing our new metrics product"
• "Performance improvements in Sentry"
• "AI-powered debugging with Seer"

End with something useful: a link to docs, source code, a way to try it, or a call to give feedback. Never end with generic hype ("We can't wait to see what you build!"), recaps of what you just said, or product-page CTAs ("Try Sentry for free. Included on all plans."). Connect back to the story you opened with, or give the reader something concrete to do next.

Here's the quick map by post type:

Before publishing, ask: Would a developer share this post? Does it have a shot at getting on Hacker News? If the answer is no, the post either needs more depth, more original insight, or it belongs in the changelog instead.

Posts worth sharing contain at least one of:

• A technical decision explained with trade-offs
• Original data or research not found elsewhere
• A real-world debugging story with specific details
• An honest accounting of something that went wrong
• A how-to that saves the reader real time

1. Never publish without a real person's name on it. No "The Sentry Team" bylines.
2. Never publish code that doesn't work.
3. Never say "we're excited to announce." Just announce it.
4. If you describe a system, include a diagram.
5. If you make a performance claim, include the number.
6. If you discuss a decision, explain what you didn't choose and why.
7. Every post must have a clear "who is this for" in the author's mind before writing.
8. Changelogs belong in the changelog. Blog posts should offer something more.
9. When in doubt, go deeper. The risk of being too shallow is far greater than being too detailed.
10. Write the post you wish existed when you were trying to solve this problem.

Run through both checklists:

Technical Review:

• All technical claims accurate
• Code samples work
• Architecture descriptions match reality
• Numbers and benchmarks correct
• No oversimplifications that would make an expert cringe

Editorial Review:

• Opening hooks reader within 2 sentences
• Passes the "would I share this?" test
• No corporate language, filler, or fluff
• Headings convey information
• Right length (not padded, not too thin)
• Title is specific and compelling

Final Check:

• Author byline is correct (real person's name)
• Links to docs/getting-started included
• Post doesn't duplicate what's in the changelog

When providing feedback, be specific and constructive. Quote the weak passage, explain why it's weak, and rewrite it to show the standard.