Paul Kinlan ✓

@Paul_Kinlan · Ruthin, North Wales · joined 01 Jan 2010

Lead for Chrome DevRel @ Google. Progressive Web Apps, Mr Web Intents. Dev of many things: Twollo, Twe2, FriendDeck and https://t.co/C1nmx67K3t https://t.co/jHwOp3rPWH

23 339Followers

3 672Following

36 561Posts total

6.9KViews on collected posts

โพสต์ล่าสุด

Paul Kinlan ✓@Paul_Kinlan12 Sep

Money well spent on the advertising if you ask me https://t.co/qghi7fLZM3

971 views · 22 likes · 0 reposts · 1 replies Open on X →

Paul Kinlan ✓@Paul_Kinlan10 Sep

@Paul_Kinlan It will be case even in installed apps 29 views · 1 likes · 0 reposts · 1 replies Open on X →

Paul Kinlan ✓@Paul_Kinlan9 Sep

👀 - this is a sneak peak a future for the web. 2.2K views · 20 likes · 1 reposts · 1 replies Open on X →

Paul Kinlan ✓@Paul_Kinlan8 Sep

I really like @slicknet 's post about roles in software engineering. No doubt we will see refinement over the coming months and years but this is one of the crispest breakdowns I've read. https://t.co/QQDmqYbRMT 1.1K views · 3 likes · 2 reposts · 1 replies Open on X →

Paul Kinlan ✓@Paul_Kinlan6 Sep

I've landed on a pretty decent process with my agents in pi (+intercom) and beads. + A coordinator instance with my pi-chaos-relay. It is the agent I talk to via any input channel (telegram mostly) and it knows the status of all the agents it works with and will ask them to do 864 views · 3 likes · 0 reposts · 1 replies Open on X →

Paul Kinlan ✓@Paul_Kinlan3 Jul

Can the presence of a URL in an LLM prompt influence the output based on the content of that URL? I think, yes! But it took me weeks of experimentation and I learnt a lot about what User Agents do and what data is in the models https://t.co/zt2fPuN4mY 1.8K views · 5 likes · 0 reposts · 1 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

5 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม การเข้าถึงปกติสำหรับขนาดนี้ แต่การตอบสนองอ่อนกว่าส่วนใหญ่.

ยอดดูมัธยฐาน971บัญชีนี้924ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %4.16%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %1.01%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	971	924	1.05×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	4.16%	3.62%	1.15×
อัตราการมีส่วนร่วม	1.01%	1.52%	0.66×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

1.8K3 Jul

8646 Sep

1.1K8 Sep

2.2K9 Sep

2910 Sep

97112 Sep

Last 6 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.33%3 Jul

0.46%6 Sep

0.55%8 Sep

1.01%9 Sep

6.90%10 Sep

2.37%12 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes73.0%54 in total

Reposts4.1%3 in total

Replies8.1%6 in total

Bookmarks14.9%11 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.