LinkedIn Strategy
🗒️ Description
My approach to LinkedIn content, based on data from 31 posts analyzed (Feb-Apr 2026). Target audience: founder/operator-focused IT market. Geographic focus: Poland.
🧩 Key findings:
Format
- Default: ugcPost (original content) — avg 1,056 impressions, 4.13 saves/post, 1.83% ER
- Share format weak on saves — use only for quick reach
Timing
- Best day: Tuesday (2.93% ER, 29.7 avg interactions)
- Secondary: Friday, Thursday
- Post at 6:00 AM (morning commute)
- One post max per day (batching cannibalizes)
- Target: ~15 posts/month
What works
- Technical insights with data (model comparisons, context window findings)
- CTO / Agentic Coding perspective (operational, not theoretical)
- Architectural patterns from real products (Qamera AI examples)
- Build in Public content
What doesn’t work
- Reposts (virtually no growth effect)
- Lifestyle/non-tech content
- Rhetorical questions or fluff
🔗 Three content pillars
- Illusion — AI quality parity with fashion photoshoots (Qamera)
- Economy — cost/time benefits (98% cheaper, 25x faster)
- Backstage — building in public, challenges, learnings
📖 Further reading
- Build in Public
- Richard van der Blom — external LinkedIn algorithm research and Algorithm Insights Report
- Social Media Algorithms — Maximizing Reach in 2026 — cross-platform 2026 reference; LinkedIn section covers the 360Brew LLM ranker, dwell time, and saves as the top signals
- High-Signal AI Voices to Follow (2026) — the consumption side: evidence-based, ship-proven AI/second-brain builders to follow
Template: knowledge_note_info