LinkedIn Strategy
ποΈ 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.
π§© Key findings:
Format
- Default: ugcPost (original content) β avg 1,056 impressions, 4.13 saves/post, 1.83% ER
- Share format weak on saves β 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 doesnβt work
- Reposts (virtually no growth effect)
- Lifestyle/non-tech content
- Rhetorical questions or fluff
π Three content pillars
- Illusion β AI quality parity with fashion photoshoots (Qamera)
- Economy β cost/time benefits (98% cheaper, 25x faster)
- Backstage β building in public, challenges, learnings
π Further reading
- Build in Public
- Richard van der Blom β external LinkedIn algorithm research and Algorithm Insights Report
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