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Grammarly Engineering Blog

Company blog · tech.grammarly.com/blogprogrammingsystems

Grammarly Engineering Blog is the company blog at tech.grammarly.com, writing about programming and systems. Since 2015, 17 different Hacker News readers have linked it 30 times, most often “Running Lisp in Production (2015)”. It is still writing: the last post was on 2026-09-28, and you can follow it by feed.

Visit the blog
30mentions?
17HN people?
2015–2019first – last linked?
Links on Hacker News per year · peak 13 in 2017

Too few sampled comments (9) to say how often HN recommends it.?

Why HN links it

HN readers link the Grammarly engineering blog as a source on running Common Lisp (SBCL) in production, including GC settings, and on its use of Clojure for ETL pipelines. Most mentions are pointers within Lisp discussions.

Summarised by Claude from a sample of 9 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Learn more about Grammarly's AI-powered writing assistant and the complex technical challenges we’re solving to build sophisticated products that scale.

Most-linked posts?

  1. Running Lisp in Production (2015)
    5 people · 6 mentions · first linked 2017-05-09
  2. Building ETL pipelines with Clojure and transducers
    4 people · 6 mentions · first linked 2017-05-04
  3. Running Lisp in Production
    4 people · 5 mentions · first linked 2015-06-26
  4. Building Browser Extensions at Scale
    3 people · 3 mentions · first linked 2017-10-09

What Hacker News says?

  1. azrazalea · 2017-03-29Recommends
    This talks about GC settings that worked for them in SBCL for production, not sure if you already tried the same kind of stuff but may be an interesting read http://tech.grammarly.com/blog/posts/Running-Lisp-in-Product... . If you can make an easy to run example of the garbage collector not working correctly, the folks in #sbcl on freenode are very responsive and have commit access to fix it.

    Comment linking /blog/posts/Running-Lisp-in-Production.html

    on “How to write Common Lisp in 2017 – an initiation manual”
  2. Submitted Running Lisp in Production as a story · 397 points

    HN discussion
  3. No interpreters used, mostly SBCL and CCL. Folks over at Grammarly have a blog post which mentions few reasons for the combo http://tech.grammarly.com/blog/posts/Running-Lisp-in-Product... I write portable code and use libraries which abstract away implementation specific stuff so it will be easy to run on any other conforming implementation should the need arise. The community is quite responsible when it comes to…

    Comment linking /blog/posts/Running-Lisp-in-Production.html

    on “How to write Common Lisp in 2017 – an initiation manual”
  4. Submitted Running Lisp in Production (2015) as a story · 167 points

    HN discussion
  5. hydandata · 2019-09-17Recommends
    I used it at work[0] for a few years and it was great, but I did not scale that project to large number of people, mainly because it did not need to. Folks at Grammarly have a writeup about how they are using it, it might have more relevant information for you[1]. I would definitely consider using it again, but proper buy-in takes time, and I have simply been moving too fast since then. I am still not a big fan of C…

    Comment linking /blog/posts/Running-Lisp-in-Production.html

    on “Why Go and Not Rust?”
  6. Submitted Running Lisp in Production (2015) as a story · 138 points

    HN discussion
  7. I think you are missing the implications of working with image-based language runtimes. The CI or even the client can attaches the live image of the error, the programmer opens up the image when he opens the ticket and has the full venerable introspection tools of CL or Smalltalk. This directly addresses the reproducability issue you raised in said paragraph. There are indeed occasions where you need a proper rr-lik…

    Comment linking /blog/running-lisp-in-production

    on “Debuggers Suck”
  8. Submitted How to Split Sentences (2014) as a story · 88 points

    HN discussion
  9. fheld · 2019-10-17Recommends
    might be interesting for you, Lips in production: https://tech.grammarly.com/blog/running-lisp-in-production

    Comment linking /blog/running-lisp-in-production

    on “Why Isn't Functional Programming the Norm? [video]”
  10. Submitted Paving the way for human-level sentence corrections as a story · 72 points

    HN discussion
  11. Grammarly is pretty recent: http://tech.grammarly.com/blog/posts/Running-Lisp-in-Product...

    Comment linking /blog/posts/Running-Lisp-in-Production.html

    on “New Common Lisp website”
  12. Submitted Deploying Containers in the Real World: Part 2 of Grammarly's Docker Journey as a story · 46 points

    HN discussion
  13. They use clojure as well (instead?). https://tech.grammarly.com/blog/building-etl-pipelines-with-... https://www.grammarly.com/jobs/engineering/software-engineer...

    Comment linking /blog/building-etl-pipelines-with-clojure

    on “How Grammarly Grew to 6.9M Daily Users in 9 Years”
  14. Submitted Running Lisp in Production (2015) as a story · 26 points

    HN discussion
  15. A little-known fact is that Grammarly is a Common Lisp app: https://tech.grammarly.com/blog/running-lisp-in-production

    Comment linking /blog/running-lisp-in-production

    on “How Grammarly Grew to 6.9M Daily Users in 9 Years”
  16. Submitted From lawyer to coder as a story · 17 points

    HN discussion
  17. They also use Clojure (2017): https://tech.grammarly.com/blog/building-etl-pipelines-with-...

    Comment linking /blog/building-etl-pipelines-with-clojure

    on “Running Lisp in Production (2015)”
  18. Submitted Making Docker Rock at Grammarly as a story · 15 points

    HN discussion
  19. Submitted Building Browser Extensions at Scale as a story · 13 points

    HN discussion
  20. Submitted Petabyte-Scale Text Processing with Spark as a story · 13 points

    HN discussion
  21. Submitted Building ETL pipelines with Clojure and transducers as a story · 8 points

    HN discussion
  22. Submitted Building a versatile analytics pipeline on top of Apache Spark as a story · 5 points

    HN discussion
  23. Submitted Building ETL pipelines with Clojure and transducers as a story · 4 points

    HN discussion
  24. Submitted Building Browser Extensions at Scale as a story · 3 points

    HN discussion
  25. Submitted Running Lisp in Production as a story · 3 points

    HN discussion
  26. Submitted Building ETL pipelines with Clojure and transducers as a story · 3 points

    HN discussion
  27. Submitted Building ETL pipelines with Clojure and transducers (2017) as a story · 2 points

    HN discussion
  28. Submitted Building Browser Extensions at Scale as a story · 2 points

    HN discussion
  29. Submitted Decoupling a Monolithic Server Application as a story · 2 points

    HN discussion
  30. Submitted Petabyte-Scale Text Processing with Spark as a story · 1 points

    HN discussion

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