Unlearn ✓

@UnlearnDev · joined 15 Mar 2017

Built for developers who want to unlearn outdated defaults and start building engineering judgment. Powered by @Bitter_Brains

44 612Followers

165Following

4 688Posts total

9.7KViews on collected posts

Derniers posts

Unlearn ✓@UnlearnDev11 Sep

Your tests can stay green while your app breaks. Ask an agent to tidy up a file with no rules in place, and it'll happily change behaviour. We show exactly this at the start of Workflow 7 (Refactoring with an AI Agent), then spend the rest of the workflow making sure it doesn't 970 views · 1 likes · 0 reposts · 0 replies Open on X →

Unlearn ✓@UnlearnDev9 Sep

A one-line bug report, no repro steps. You guess, poke around, hope it sticks. Half the time it doesn't, because you never proved you had the actual bug. Workflow 06: Debugging and Performance fixes that. Live now on Unlearn - learn more: https://t.co/KHP5IEqefY https://t.co

1:00

1.4K views · 2 likes · 1 reposts · 0 replies Open on X →

Unlearn ✓@UnlearnDev3 Sep

Most people decide what to refactor by opening a file and not liking how it looks. 💡 A better starting point? Files you or your agent have to keep going back into. They cost time and money. Use this to find them: git log --name-only --pretty=format: -- 'app/*' | grep -v '^$' 1.5K views · 2 likes · 0 reposts · 0 replies Open on X →

Unlearn ✓@UnlearnDev31 Aug

AI writes race conditions all the time. They’re some of the hardest bugs to spot in review because the code often looks perfectly reasonable. 1.5K views · 1 likes · 0 reposts · 0 replies Open on X →

Unlearn ✓@UnlearnDev24 Aug

Learn more about Spec-driven development with OpenSpec in our deep dive: https://t.co/KHP5IEqefY 230 views · 2 likes · 0 reposts · 0 replies Open on X →

Unlearn ✓@UnlearnDev24 Aug

Finally you archive it, folding the change into the living spec so the next one starts from what the app actually does. 209 views · 1 likes · 0 reposts · 1 replies Open on X →

Unlearn ✓@UnlearnDev24 Aug

Once you're happy, the agent implements against it. You're then checking the result against something you'd already agreed to rather than trying to remember what you meant. 176 views · 2 likes · 0 reposts · 1 replies Open on X →

Unlearn ✓@UnlearnDev24 Aug

You propose it first. A short doc with the what, the why, the design and the tasks (the thinking upfront you'd otherwise do halfway through reviewing a diff). 299 views · 2 likes · 0 reposts · 1 replies Open on X →

Unlearn ✓@UnlearnDev24 Aug

Spec-driven development is pretty simple: write down what the change is and how it should behave before the agent writes any of it. 🧵 1.5K views · 3 likes · 2 reposts · 1 replies Open on X →

Unlearn ✓@UnlearnDev21 Jul

🔴 Live today at 15:00 CEST. @alexdotgs hosts a free, 2-hour session on how the best developers direct AI, and catch what it gets wrong. 🎁 Everyone who shows up keeps The AI-Era Developer Playbook, too. See you there! https://t.co/ppnC2AWevM 1.9K views · 3 likes · 2 reposts · 0 replies Open on X →

Face aux comptes de taille comparable

10 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. en dessous de ses pairs à la fois en portée et en engagement.

Vues médianes1 182ce compte1 043médiane pour 10K–100K

Portée, %2.65%ce compte3.67%médiane pour 10K–100K

Engagement, %0.33%ce compte1.68%médiane pour 10K–100K

Indicateur	Ce compte	Médiane pour 10K–100K	Rapport
Vues médianes par post	1 182	1 043	1.13×
Portée (vues ÷ abonnés)	2.65%	3.67%	0.72×
Taux d'engagement	0.33%	1.68%	0.20×

Autres comptes de cette tranche → Comparer avec un autre compte → Comment ces repères sont établis →

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

1.9K21 Jul

1.5K24 Aug

299

176

209

230

1.5K31 Aug

1.5K3 Sep

1.4K9 Sep

97011 Sep

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.27%21 Jul

0.39%24 Aug

1.00%

1.70%

0.96%

0.87%

0.07%31 Aug

0.14%3 Sep

0.22%9 Sep

0.10%11 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.68%.

What the audience does

Likes63.3%19 in total

Reposts16.7%5 in total

Replies13.3%4 in total

Bookmarks6.7%2 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.

Derniers posts

Face aux comptes de taille comparable

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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