The Curious Engineer

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benn.substack

benn.substack.com

A weekly Substack on data and technology, with some occasional conversations about culture, sports, and politics. Click to read benn.substack, by Benn Stancil, a Substack publication.

Tech news / industryEssays / personal

’21’22’23’24’25’26
Posts
277 from 2 Feb 2021 to 13 Sep 2026
Posting
weekly (43 in the last year)
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personal blog
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2026 36

  1. How to lose your mind
  2. How to find insights
  3. How to have ideas
  4. The model is man-made
  5. So that's what alignment means
  6. This is why we can't have nice things
  7. Brute intelligence
  8. Is "jobs" a four-letter word?
  9. Be a winner, or join one?
  10. To weigh a watermelon
  11. The frontier fails the Turing test
  12. Can AI make an iPhone?
  13. What will startups do in 2030?
  14. Your agent will be your undoing
  15. Be reckless
  16. Wac
  17. The bonfire of our vanities
  18. The revolution will be ticketed
  19. Leaderbored
  20. How do you make a chart?
  21. There is no pivot
  22. Post-money values
  23. Should they buy…Allbirds?
  24. Something good
  25. Compacting...
  26. It’s the people, stupid
  27. The banality of surveillance
  28. The best is still hard to be
  29. Take off
  30. Go crazy, folks, go crazy
  31. The gentle obsolescence
  32. Gas town
  33. Maybe, finally—the end of SQL
  34. Why Cowork can’t work
  35. Make it better
  36. Have you tried a text box?

2025 48

  1. Pure heroin
  2. The vibes and the noise
  3. Will there ever be a worse time to start a startup?
  4. 9-9-6-0
  5. Producer theory
  6. All you can do is play the game
  7. A strange delight
  8. An very obvious deal
  9. In the air
  10. Something in the orange
  11. We were hired to do the grunt work
  12. Is the innovator's dilemma outdated?
  13. It is the internet
  14. Stuff costs money
  15. The context layer
  16. Outdated
  17. Ban ChatGPT*
  18. Enough
  19. Can analysis ever be automated?
  20. Everyone is crazy now
  21. A cold play
  22. SaaS 2.0
  23. Ambition, fun and not
  24. Meme-company
  25. Fear and self-loathing in Silicon Valley
  26. How much agency do we actually want?
  27. Which way from here?
  28. The ads are coming
  29. We need a new…database?
  30. No, really, everything becomes BI
  31. The scorpion box
  32. A new invisible hand
  33. Startups (still) aren’t businesses (yet?)
  34. The industrialization of IT
  35. American Dynamism
  36. Live like you’re dying
  37. Copy copy revolution
  38. Most graduate degrees in analytics are scams
  39. The labor of little decisions
  40. The end of YC
  41. The return of the modern data stack
  42. Achievement, here and there
  43. For the brand, I guess
  44. Another one
  45. Good Lord
  46. Is growth still good?
  47. Hotel California
  48. The Trenderprise

2024 47

  1. Results, Actually
  2. AI companies are just SaaS companies
  3. Is this a career?
  4. Postgres in a box
  5. Searching for insight
  6. Does data quality matter?
  7. No better room
  8. Fragile
  9. Don't be evil*
  10. Is being data driven a fad?
  11. Something lost, something found
  12. Is Excel immortal?
  13. The second wolf
  14. Welcome to benn.ventures
  15. Do AI companies work?
  16. Getting away with it
  17. Just do it
  18. How a startup feels
  19. A very particular set of skills
  20. How to create a winning pitch deck
  21. Ed Harris would like to connect with you on LinkedIn
  22. Ambition, then and now
  23. It’s too many options
  24. The important thing for you to know is that it’s not my fault
  25. The vibes are weird
  26. The rise of the analytics pretendgineer
  27. Everything is still BI
  28. The design flaw at the heart of every data product
  29. Attn: Data
  30. The SaaS counterculture
  31. BI’s third form
  32. Do software companies actually have good margins?
  33. PlayerCoach.ai investor update – Q1 2024
  34. Oops
  35. All at one time
  36. Disband the analytics team
  37. The posters decide
  38. Long on shovels, short on gold
  39. Whatever, do the secondary sale
  40. LLMs shouldn’t write SQL
  41. The problem was the product
  42. Small multiplies
  43. Data arithmetic
  44. Your company's values will be used against you
  45. It's time to build
  46. Trading places
  47. How much is the news worth?

2023 51

  1. The whole scheme
  2. Playing for ourselves
  3. The modern data stack was never big enough
  4. AVG(text)
  5. Tribal accelerationism
  6. The series E(verything is fine)
  7. AI is coming for your favorite product's good user experience
  8. Why are we still surprised that startups are hard?
  9. The effects of a war
  10. Transforming into San Diego
  11. There is no post today
  12. Does venture capital ruin great products?
  13. The potential gap
  14. So you want to sell to the enterprise?
  15. The end of our purple era
  16. Category collapse
  17. Take the down round
  18. How much for that DAG in the window?
  19. The smol analyst
  20. The hunt for the Holy Grail
  21. The emotionally informed company
  22. Will we ever have clean data?
  23. How an acquisition fails
  24. We don’t need another SQL chatbot
  25. Gsnowflake
  26. To my parents
  27. 10,000 microwave enthusiasts to attend annual microwave conference in Las Vegas
  28. Should we be nice to ChatGPT?
  29. All I want is to know what's different
  30. A gambler's guide to giving talks
  31. Microsoft builds the bomb
  32. Do we still need the world wide web?
  33. The truth is out there
  34. BI by another name
  35. Clear eyes, full hearts, can't lose
  36. “Am I the Jared Kushner?”
  37. How dbt succeeds
  38. The new philosophers
  39. Large language labor markets
  40. The public imagination
  41. Too innovative to fail
  42. For immediate release: Doubling down on our data investments
  43. What happened to the data warehouse?
  44. Terror in the Skynet
  45. Customer capture
  46. The case for being biased
  47. The insight industrial complex
  48. The rapture and the reckoning
  49. Do data teams have product-market fit?
  50. The conglomerate
  51. Math is overrated

2022 52

  1. Scoring a decade of data predictions
  2. Moneyballing the World Cup
  3. The product is the process
  4. How analysis dies
  5. The worst spreadsheet I've ever made
  6. Should we be grateful for the modern data stack?
  7. The internet, 2022
  8. Data’s day of reckoning
  9. The emperor and his clothes
  10. Data's invisible hand
  11. All in one place
  12. Internal tools make lousy startups
  13. How dbt fails
  14. A rich man and his iPhone
  15. Fine, let's talk about data contracts
  16. How Fivetran fails
  17. If data is a product, what is production?
  18. How Snowflake fails
  19. The past is not precious
  20. What do we do when we get it wrong?
  21. Down with the DAG
  22. Analysts should have portfolios
  23. The powder keg of the modern data stack
  24. Do data-driven companies actually win?
  25. The data config
  26. Are we human, or are we vendor?
  27. Why do people want to be analytics engineers?
  28. Disaster
  29. iSnowflake
  30. Microsoft, Google, and the original purple people
  31. All your database are belong to us
  32. The technical pay gap
  33. Free fall
  34. The best decision is one
  35. The case for consolidation
  36. How much is 265 billion dollars?
  37. A better way to lie with statistics
  38. Has SQL gone too far?
  39. The end of Big Data
  40. We all have an audience
  41. The ghosts in the data stack
  42. Startups shouldn’t care about revenue
  43. A very big deal
  44. Work like an analyst
  45. Nothing to add
  46. Disclose your angel investments
  47. The next billion programmers
  48. Business in the back, party in the front
  49. Service pressure
  50. How to play Wordle
  51. The metadata money corporation
  52. Data's trillion dollar question mark

2021 43

  1. The more the merrier
  2. Fwd: Exec KPIs - Daily
  3. Delirium
  4. Data is for dashboards
  5. Lies, damned lies, and coffee cake
  6. The missing analytics executive
  7. Does data make us cowards?
  8. A method for measuring analytical work
  9. Data and the almighty dollar
  10. The future of operational analytics
  11. BI is dead
  12. Chasing ghosts
  13. The intergalactic data stack
  14. Who is “the community?”
  15. Is BI dead?
  16. Tilt and tilted
  17. The data OS
  18. The calendar takes its tax
  19. The Modern Data Experience
  20. The unspoken gerrymandering of the modern data stack
  21. The third rail
  22. Analytics is at a crossroads
  23. Self-serve is a feeling
  24. How to feel about a tie
  25. Data's big whiff
  26. In defense of analogies
  27. The case against SQL formatting
  28. When are templates going to happen?
  29. The self-serve shibboleth
  30. To the man in 18A: Open the window, you degenerative cusk eel
  31. Analytics is a mess
  32. It's hard to hate up close
  33. Is Minerva the answer?
  34. Optimizing your Twitter profile picture
  35. The missing piece of the modern data stack
  36. Data’s horizontal pivot
  37. Why is self-serve still a problem?
  38. A brief programming note
  39. A season without bats
  40. Where are the Instagram apologies?
  41. The misleading math of a startup wealth tax
  42. A slur on Clubhouse
  43. Social media's runaway train