Publication Targets — Outreach Strategy

This document analyzes potential publications for guest posts and syndication, with audience profiles and messaging angles that would resonate.


Tier 1: High Reach, High Effort

Pragmatic Engineer (Gergely Orosz)

Audience:

  • Senior engineers and engineering managers at scale
  • Strong Big Tech / high-growth startup representation
  • Pragmatic, skeptical of hype, value concrete experience
  • ~500k+ subscribers

What resonates:

  • Real-world experience, not theory
  • Contrarian takes backed by evidence
  • “Here’s what actually happened when…”
  • Deep dives on how things work in practice

Angle for The Long Run:

  • “What happens to code review when context is infinite?” — concrete observations from teams using AI agents
  • “The IC role is splitting in two” — observable patterns, not predictions
  • Avoid: philosophical framing. Lead with the observation, let implications emerge.

Pitch approach: Gergely occasionally features guest posts. Best route is to build relationship via comments/engagement first, then pitch a specific piece that fills a gap in his coverage.


LeadDev

Audience:

  • Engineering managers, directors, VPs
  • People navigating the “management vs IC” boundary
  • Care about team health, delivery, career growth
  • Conference-connected community

What resonates:

  • Leadership challenges with practical frameworks
  • “How do I help my team with X?”
  • Human side of engineering — growth, communication, change
  • Not too abstract; needs to connect to a manager’s Monday morning

Angle for The Long Run:

  • “How do you evaluate work you can’t see?” — the management challenge of ambient collaboration
  • “Onboarding when the codebase explains itself” — what changes for new team members
  • “The always-on cost isn’t compute” — team dynamics with persistent AI agents

Pitch approach: LeadDev accepts pitches via their website. They want actionable pieces for managers. Reframe philosophical points as management challenges.


InfoQ

Audience:

  • Enterprise architects, senior developers
  • Decision-makers evaluating tools and practices
  • Want depth and nuance, not hype
  • Strong Java/cloud-native contingent but increasingly polyglot

What resonates:

  • Technical depth with strategic context
  • “Here’s what this means for your architecture”
  • Honest tradeoffs, not advocacy
  • Long-form (2,000-4,000 words welcome)

Angle for The Long Run:

  • “The IDE as intervention surface” — what it means for enterprise tooling strategy
  • “When context encodes intent” — implications for governance and compliance
  • “Development used to be synchronous” — reframing for enterprise teams

Pitch approach: InfoQ has editors for different topic areas. Find the AI/ML or DevOps editor, pitch with a clear thesis and why their audience needs this now.


Tier 2: Medium Reach, Medium Effort

The New Stack

Audience:

  • DevOps, platform engineering, cloud-native practitioners
  • Hands-on builders who also think about trends
  • Mix of IC engineers and tech leads

What resonates:

  • How new tools change workflows
  • Platform engineering perspectives
  • Concrete tech + strategic implications
  • Vendor-aware but not vendor-driven

Angle for The Long Run:

  • “AI agents as the new CI/CD” — continuous work, not continuous integration
  • “The platform team’s new customer” — when agents are the primary API consumers
  • Focus on infrastructure/platform implications of ambient AI

Pitch approach: Open to contributed articles. Pitch via their contributor form with a clear hook.


Hacker Noon

Audience:

  • Broad tech audience, skews younger
  • Founders, developers, crypto/AI-curious
  • Tolerant of opinion pieces and thought leadership
  • Less rigorous editorial filter

What resonates:

  • Bold takes, clearly stated
  • “Why X is over” / “The real reason Y”
  • Accessible writing, not too dense
  • Okay with more speculative framing

Angle for The Long Run:

  • Could republish existing articles with minimal adaptation
  • Good for pieces with a strong hook/headline
  • “Why your dev workflow is about to feel ancient”

Pitch approach: Easy to publish — submit via their platform. Good for expanding reach with low effort. Use canonical links.


DZone

Audience:

  • Professional developers, enterprise-leaning
  • Heavy tutorial/how-to orientation
  • Want practical, applicable content
  • Less interested in philosophy

What resonates:

  • “How to think about X” frameworks
  • Patterns and anti-patterns
  • Connects to daily dev work

Angle for The Long Run:

  • Would need to reframe as more practical
  • “3 questions to ask before your team adopts AI coding agents”
  • Less natural fit, but useful for backlinks and reach

Pitch approach: Open contributor platform. Lower editorial bar but also lower signal value.


Dev.to

Audience:

  • Developers at all levels
  • Community-oriented, supportive vibe
  • Mix of tutorials and opinion pieces
  • Strong early-career representation

What resonates:

  • Authentic voice, not corporate
  • “Here’s what I learned”
  • Welcomes longer think-pieces
  • Engages in comments

Angle for The Long Run:

  • Can cross-post with canonical links
  • Slightly more accessible framing helps
  • Community will engage if you engage back

Pitch approach: No pitch needed — just publish. Use canonical URL to your site. Engage with comments to build community presence.


Tier 3: Medium Publications

Better Programming

Audience:

  • Working programmers
  • Career-focused, want to level up
  • Mix of tutorials and industry perspective

What resonates:

  • “How good developers think about X”
  • Career and craft orientation
  • Not too abstract

Angle for The Long Run:

  • “What ‘staying technical’ means when the technical is shifting”
  • “The craft is moving” — what skills matter in an AI-augmented world

Pitch approach: Submit to the publication (not just post on Medium). They curate, which helps distribution.


Towards Data Science

Audience:

  • ML practitioners, data scientists
  • Technical but varied depth
  • AI-curious general tech readers

What resonates:

  • AI implications explained clearly
  • Not too much jargon
  • “Here’s what this trend means”

Angle for The Long Run:

  • More technical AI-angle pieces could fit
  • “What LLM context windows mean for development workflows”

Pitch approach: Submit to publication. Canonical links accepted but may reduce distribution.


Quick Reference

PublicationAudienceBest AngleEffortBacklink
Pragmatic EngineerSenior eng/EMConcrete observationsHighHigh value
LeadDevEng managersManagement challengesMediumHigh value
InfoQEnterprise architectsStrategic depthMediumHigh value
The New StackPlatform/DevOpsInfrastructure implicationsMediumGood
Hacker NoonBroad techBold takesLowMedium
DZoneEnterprise devsPractical frameworksLowMedium
Dev.toAll developersAuthentic voiceLowLow (nofollow)
Better ProgrammingProgrammersCareer/craftMediumMedium
Towards Data ScienceML/AI curiousAI implicationsMediumMedium

Community Platforms

Hacker News

Audience:

  • Senior developers, founders, tech leaders
  • Skeptical, allergic to self-promotion
  • Values substance over polish
  • Can drive massive traffic if a post hits

How it works:

  • Submit link, community votes
  • You don’t “pitch” — you submit and pray
  • Better if someone else submits your work (looks less promotional)
  • Comments matter as much as posts for building reputation

Strategy:

  1. Engage genuinely in HN comments on related threads first
  2. Build presence over 2-4 weeks before submitting own content
  3. Submit the Phase A synthesis, not individual articles
  4. A strong, complete argument beats scattered pieces

Relevant HN topics to engage with:

  • AI coding assistants / Copilot discussions
  • “Future of software development” threads
  • Developer productivity debates
  • LLM/agent capability discussions

Reddit

Best subreddits:

SubredditAudienceVibeSelf-promo rules
r/ExperiencedDevsSenior devs, 5+ YOEThoughtful, nuancedStrict — must be active member
r/programmingGeneral devNoisy, link-heavyModerate — 10:1 rule
r/SoftwareEngineeringCareer/practice focusProfessionalModerate
r/MachineLearningML practitionersTechnicalResearch-focused
r/artificialAI curiousMixed qualityMore lenient

Strategy:

  1. Comment genuinely on other threads for 2-3 weeks first
  2. Build karma and recognition in the community
  3. Then share content — framed as discussion, not promotion
  4. r/ExperiencedDevs is the best fit for The Long Run’s tone

Distribution Strategy

Reposting Strategy

For Dev.to / Hacker Noon:

  • Don’t dump all articles at once — looks spammy
  • Pick 2-3 with the strongest hooks/headlines
  • Space out: one per week
  • Track which topics resonate before committing more effort

Best candidates for reposting:

  • Articles with a clear “wait, what?” moment in the title
  • Standalone pieces that don’t require series context
  • Check analytics: which got most LinkedIn engagement?

Phase A Synthesis Strategy

Once Phase A (articles 1-5) is complete:

Create a single synthesis piece: “What’s actually changing about software development”

This is NOT a compilation — it’s a new argument that draws on the observations:

  • Original framing and structure
  • Synthesizes the pattern across all 5 pieces
  • Can reference the individual articles as “further reading”

Why this works:

  • Higher-tier publications want original, not reposts
  • A synthesis demonstrates coherent thinking, not scattered observations
  • Perfect hook: “I spent 3 months observing X, here’s what I found”

Pitch targets for synthesis:

  1. LeadDev — “How do you lead through this shift?”
  2. InfoQ — “What this means for enterprise teams”
  3. Pragmatic Engineer — “I observed X across teams, here’s the pattern”

Timing: Complete Phase A → write synthesis → pitch within 2 weeks while themes are fresh


Phase 1: Foundation (Now)

Cross-post to low-effort platforms:

  • Pick 2-3 articles with strongest hooks
  • Post to Dev.to and Hacker Noon with canonical links
  • Space out: one per week
  • Track which topics/headlines resonate

Start community engagement:

  • Comment on 3-5 relevant Reddit threads per week
  • Engage on HN discussions about AI/dev tools
  • Build genuine presence before promoting

Phase 2: Synthesis (After Phase A complete)

Create the Phase A synthesis piece:

  • “What’s actually changing about software development” — single cohesive argument
  • Original framing, not just compilation
  • This becomes the anchor for higher-tier pitches

Pitch sequence:

  1. LeadDev — management angle (“How do you lead through this shift?“)
  2. InfoQ — enterprise angle (“What this means for your team/architecture”)
  3. The New Stack — platform angle (“Infrastructure implications”)

Submit to community platforms:

  • HN: the synthesis piece (ideally have someone else submit)
  • Reddit: r/ExperiencedDevs discussion post

Phase 3: Relationship Building (Ongoing)

Pragmatic Engineer path:

  • Engage with Gergely’s content consistently
  • Comment thoughtfully on his posts
  • After 2-3 months of presence, pitch the synthesis or a follow-up piece
  • Frame: “I’ve been observing X across multiple teams, here’s what I found”

Reddit Threads to Engage With

Article → Discussion Topic Mapping

ArticleCore InsightReddit Discussion Angle
001 Desktop as centreWork happens around the IDE, not just in it”Where does the work actually happen now?“
002 Work continues without youAgents generate work, not just support it”What changes when progress doesn’t require presence?“
003 Development was synchronousAsync breaks tight feedback loops”Flimsy understanding” — the cognitive cost of reviewing vs writing
004 IDE as intervention surfaceIDE shifts from creation to correction”Are we becoming editors of AI work rather than authors?“
005 Faster feedback not whole storyContinuity > speed”Is ‘faster’ the wrong metric?”

Active Threads Mapped to Your Content (Feb 2026)

r/ExperiencedDevs:

  1. “AI is working great for my team, and y’all are making me feel crazy”

    • https://reddit.com/r/ExperiencedDevs/comments/1qq8y8u/
    • 967 upvotes, highly active
    • Connects to: Articles 002, 004
    • Your angle: They describe work continuing via agents/skills — validate this, then raise the question from 004: “What’s interesting is the shift from doing to reviewing. I’ve noticed the IDE becomes more about intervention than creation. Anyone else finding the skill is now knowing when to step in?”
  2. “Anthropic: AI assisted coding doesn’t show efficiency gains”

    • https://reddit.com/r/ExperiencedDevs/comments/1qqy2ro/
    • 1022 upvotes, 433 comments
    • Connects to: Article 003 (synchronous → async, feedback loops)
    • Your angle: “The ‘flimsy understanding’ point resonates. Development used to be synchronous — small changes, immediate feedback, you understood because you were there for each step. When you’re reviewing chunks of generated code, you skip that incremental understanding. It’s not about speed; it’s about what you lose in the cognitive process.”

r/programming:

  1. Same Anthropic paper thread
    • https://reddit.com/r/programming/comments/1qqxvlw/
    • 3889 upvotes, 676 comments — massive reach
    • Connects to: Article 003
    • Your angle: Shorter version: “The paper highlights something real — it’s not just about efficiency, it’s about what kind of understanding you build. Writing code line-by-line vs reviewing chunks are different cognitive processes.”

Additional Threads (Feb 2026)

  1. “Handling AI code reviews from juniors”

    • https://reddit.com/r/ExperiencedDevs/comments/1r0iepg/
    • 30 upvotes, active
    • Frustration with juniors passing AI-generated review comments
    • Connects to: Article 003 (understanding), 004 (intervention)
    • Your angle: The review quality issue — AI can generate comments but can’t judge what matters. Seniority is knowing what to care about.
  2. “Is ‘agentic coding’ working better than follow-along?”

    • https://reddit.com/r/ExperiencedDevs/comments/… (search for “agentic coding”)
    • Asking about agentic vs manual review approach
    • Connects to: Article 002, 004
    • Your angle: Different modes for different work — the skill is knowing which context needs which approach.

Posting Frequency

Cadence:

  • 2-3 quality comments per week — enough to build presence, not enough to seem obsessive
  • Never multiple comments on the same topic in the same day
  • Space out by 2-3 days between comments on similar themes
  • Vary the angle — don’t repeat the same insight; use different articles’ perspectives

Engagement rhythm:

  1. Post comment
  2. Check back in 4-6 hours for replies
  3. Respond thoughtfully to 1-2 replies (shows you’re genuine, not drive-by)
  4. Move on — don’t get into extended debates

Avoid looking like a broken record:

  • Rotate between articles 002, 003, 004, 005 perspectives
  • If you commented about “authoring → supervising” this week, use “feedback loops” or “continuity” next week
  • Let threads age — don’t comment on every AI thread that appears

Comment Strategy

Do:

  • Share a genuine observation or question
  • Add nuance the thread is missing
  • Reference your own experience (not your articles)
  • Engage with replies thoughtfully
  • Validate the OP before adding your perspective

Don’t:

  • Drop links to your articles
  • Sound like you’re promoting
  • Write essay-length comments (save that for your articles)
  • Argue — add perspective, then disengage
  • Comment on every thread about AI

Template approach:

“I’ve been thinking about this too. What strikes me is [observation that connects to your writing]. In my experience, [genuine insight]. Curious if others are seeing [question that invites discussion].”

Ongoing Search Terms (Mapped to Articles)

Check weekly for threads that connect to your content:

Search TermConnects to
AI coding review / reviewing AI codeArticle 003, 004
developer productivity AIArticle 005
AI pair programming / copilot workflowArticle 002, 004
future software developmentPhase A synthesis
junior developer AI / learning to code AIArticle 003 (understanding)
AI generated code qualityArticle 003, 004
async development / working asyncArticle 003
developer experience AIArticle 001, 004

Subreddits to monitor:

  • r/ExperiencedDevs (primary — senior audience, thoughtful)
  • r/programming (secondary — broader, noisier)
  • r/SoftwareEngineering (occasional — career/practice focus)

LinkedIn Engagement

LinkedIn requires manual searching (can’t be scraped), but here’s the strategy:

People to Follow & Engage With

Tier 1 — High relevance, large audience:

  • Gergely Orosz (Pragmatic Engineer)
  • Kent Beck
  • Kelsey Hightower
  • Charity Majors
  • Will Larson
  • Addy Osmani

Tier 2 — AI/dev tools space:

  • Simon Willison (LLM/AI tools)
  • Swyx (AI engineering)
  • People posting about Cursor, Copilot, Claude Code

Search Terms for Finding Posts

Search these weekly on LinkedIn:

  • “AI coding” / “AI developer”
  • “Copilot productivity”
  • “Claude Code” / “Cursor AI”
  • “future of software development”
  • “developer experience AI”
  • “code review AI”

Engagement Strategy

What to comment on:

  • Posts about AI coding tools (pro or con)
  • “Hot takes” about developer productivity
  • Discussions about how dev work is changing
  • Posts from target publication editors/writers

Comment approach:

  • Shorter than Reddit — 2-4 sentences
  • Add a specific observation, not just agreement
  • Ask a question that invites the author to respond
  • Don’t pitch — let your profile do the work

Frequency:

  • 3-5 comments per week on others’ posts
  • Space throughout the week, not batched
  • Prioritize posts from people with large followings (your comment gets seen)

Profile optimization:

  • Bio should mention “writing about [your themes]”
  • Link to thelongrun.dev
  • Pin your best LinkedIn post or article link

Created: February 2026