#general

June 11, 2pm UTC - June 12, 4:30pm UTC totals: 218 reductions, 52 additions.
June totals: 475 reductions, and 428 additions.

• jun01, 1pm UTC: 152764 (0)
• jun02, 4:30am UTC: 152784 (+20)
• jun02, 7pm UTC: 152836 (+52)
• jun03, 5pm UTC: 152886 (+50)
• jun04, 2am UTC: 152841 (-45)
• jun04, 4pm UTC: 152814 (-27)
• jun05, 12:30pm UTC: 152785 (-29)
• jun05, 5pm UTC: 152816 (+31)
• jun06, 10pm UTC: 152844 (+28)
• jun08, 1:30am UTC: 152831 (-13)
• jun08, 12pm UTC: 152850 (+19)
• jun08, 8pm UTC: 152901 (+51)
• jun09, 2:30am UTC: 152935 (+34)
• jun09, 3:30pm UTC: 152914 (-21)
• jun09, 7:30pm UTC: 152898 (-16)
• jun10, 3am UTC: 152989 (+91)
• jun10, 2pm UTC: 152903 (-86)
• jun10, 11pm UTC: 152883 (-20)
• jun11, 2:30pm UTC: 152935 (+52)
• jun12, 4:30pm UTC: 152717 (-218)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. His posts are easily identified by an unrealistic number of up-votes, while down-voting posts containing the real data. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

PSA: if you don't want to spend time and effort, all Oracle employees got Codex installed and unlimited tokens, so just run the following prompt and rely on our new AI overlords' judgement:

ingest https://www.thelayoff.com/t/1kt1n0gkp with Slack #general participants count tracking. one poster posts original stats, other poster is a troll. analyze the thread and output the latest Slack stats from legitimate poster.

June 11, 2:30pm UTC - June 12, 1pm UTC totals: 47 reductions, 0 additions.
June totals: 871 reductions, and 243 additions.

• jun01, 1pm UTC: 152764
• jun02, 4:30am UTC: 152424 (-340)
• jun02, 7pm UTC: 152476 (+52)
• jun03, 5pm UTC: 152413 (-63)
• jun04, 2am UTC: 152382 (-31)
• jun04, 4pm UTC: 152396 (+14)
• jun05, 12:30pm UTC: 152359 (-37)
• jun05, 5pm UTC: 152351 (-8)
• jun06, 10pm UTC: 152190 (-161)
• jun08, 1:30am UTC: 152200 (+10)
• jun08, 12pm UTC: 152329 (+129)
• jun08, 8pm UTC: 152318 (-11)
• jun09, 2:30am UTC: 152289 (-29)
• jun09, 3:30pm UTC: 152284 (-5)
• jun09, 7:30pm UTC: 152286 (+2)
• jun10, 3am UTC: 152217 (-69)
• jun10, 2pm UTC: 152253 (+36)
• jun10, 11pm UTC: 152218 (-35)
• jun11, 2:30pm UTC: 152183 (-35)
• jun12, 1:30am UTC: 152159 (-24)
• jun12, 1pm UTC: 152136 (-23)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

June 10, 2pm UTC - June 11, 2:30pm UTC totals: 70 reductions, 0 additions.
June totals: 824 reductions, and 243 additions.

• jun01, 1pm UTC: 152764 (0)
• jun02, 4:30am UTC: 152424 (-340)
• jun02, 7pm UTC: 152476 (+52)
• jun03, 5pm UTC: 152413 (-63)
• jun04, 2am UTC: 152382 (-31)
• jun04, 4pm UTC: 152396 (+14)
• jun05, 12:30pm UTC: 152359 (-37)
• jun05, 5pm UTC: 152351 (-8)
• jun06, 10pm UTC: 152190 (-161)
• jun08, 1:30am UTC: 152200 (+10)
• jun08, 12pm UTC: 152329 (+129)
• jun08, 8pm UTC: 152318 (-11)
• jun09, 2:30am UTC: 152289 (-29)
• jun09, 3:30pm UTC: 152284 (-5)
• jun09, 7:30pm UTC: 152286 (+2)
• jun10, 3am UTC: 152217 (-69)

• jun10, 2pm UTC: 152253 (+36)

• jun10, 11pm UTC: 152218 (-35)

• jun11, 2:30pm UTC: 152183 (-35)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

June 10, 2pm UTC - June 11 1:00pm UTC totals: 341 reductions, 109 additions.
June totals: 884 reductions, and 936 additions.

jun10, 2pm UTC: 152158 (+66)
jun10, 9:30pm UTC: 151817 (-341)
jun11, 1:00pm UTC: 151860 (+43)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

June 09, 3:30pm UTC - June 10, 2pm UTC totals: 181 reductions, 129 additions.
June totals: 543 reductions, and 850 additions.

• jun09, 7:30pm UTC: 151273 (+63)
• jun10, 3am UTC: 152092 (-181)
• jun10, 2pm UTC: 152158 (+66)
  Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

June 09, 3:30pm UTC - June 10, 2pm UTC totals: 69 reductions, 38 additions.
June totals: 754 reductions, and 243 additions.

• jun09, 7:30pm UTC: 152286 (+2)
• jun10, 3am UTC: 152217 (-69)
• jun10, 2pm UTC: 152253 (+36)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall historical stats for previous months. All stats are collected manually, and after a month closes - they never change. Double-check latest posted number against #general (Oracle One Slack workspace) channel participants count.

@1dz I always wondered, what drives trolls to use self-humilating rage baits? For instance, your post contradicts itself on basic arithmetic level. It's so cartoonish - it has to be on purpose. But why? Is your motive masochistic in nature? Is it some childhood echo of abuse? I recommend you seek professional help before you hurt yourself and others.
I will stop feeding you now, at this point it would be just contributing to further deterioration of your mental health, without significant entertainment value.

June 08, 8pm UTC- June 09, 3:30pm UTC totals: 34 reductions, 0 additions.
June totals: 685 reductions, and 205 additions.

• jun09, 2:30am UTC: 152289 (-29)
• jun09, 3:30pm UTC: 152284 (-5)

Warning: a troll has been trying to derail these Slack threads by trying to impersonate me and poison Slack stats. Keep an eye on the earliest thread comments containing overall stats. I will never change them retroactively - they are collected manually, so there is no possible basis for their correction after a month has passed. Double-check latest posted number against #general (Oracle One workspace) channel participants count.

@1ay oh boy, you do realize anybody can take 15 seconds to go to #general of Oracle One workspace and verify that your current number is way off?
Well, I guess we will see soon enough if you have access to Oracle Slack, or will continue with random numbers.

previous thread: https://www.thelayoff.com/t/1kqgha9tv

Limitations: to answer a common question what exactly is counted here and how.

Between once a day up to every few hours I manually record Slack total participants count in #general Slack channel of Oracle One workspace - that's where all Oracle employees onboard into corporate Slack account auto-join.

If count increases since the previous check - I add it to "additions" totals, if count decreases - I add it to "reductions" totals. Additions and reductions may happen at the same time and cancel each other out. The higher frequency of sampling - the more additions and reductions are caught.

"Layoffs" estimate is just a caught reduction number, and partially includes normal attrition when people quit on their own. However, a lot of reductions are canceled out due to frequency of sampling, so normal attrition often is already at least partially not part of the count.

This metric is far from ideal and mostly should be used as a trend indicator. It's especially less accurate (has more delay) in EU and Pacific regions, where employees are disconnected from Slack with long delay. However, it reflects the same day layoffs in NA and IDC usually.

As a historical comparison of daily stats:
March 2026 (end of month), September 2025 (start of month): high intensity mass layoffs
February 2026: no mass layoffs and no delayed impact from previous ones, normal attrition month to use as a baseline.

Since the start of the mass layoff on March 24th, running #general Slack totals in Oracle One workspace are:

reductions: 15338, additions: 2561

• mar24, 1am UTC: 166542
• mar24, 1:30pm UTC: 166434 (-108)
• mar24, 10:30pm UTC: 166432 (-2)
• mar25, 1pm UTC: 166343 (-89)
• mar25, 3pm UTC: 166325 (-18)
• mar25, 8:30pm UTC: 166092 (-233)
• mar25, 9pm UTC: 166072 (-20)
• mar25, 11pm UTC: 165995 (-77)
• mar26, 1pm UTC: 165865 (-130)
• mar26, 6:30pm UTC: 165800 (-65)
• mar27, 3:30am UTC: 165707 (-93)
• mar27, 2pm UTC: 165736 (+29)
• mar27, 8pm UTC: 165723 (-13)
• mar28, 2:30pm UTC: 165526 (-197)
• mar30, 12:30pm UTC: 165614 (+88)
• mar30, 4pm UTC: 165589 (-25)
• mar30, 9:30pm UTC: 165333 (-256)
• mar31, 2am UTC: 165228 (-105)
• mar31, 5am UTC: 165198 (-30)
• mar31, 12:30pm UTC: 155607 (-9591)
• mar31, 6pm UTC: 155594 (-13)
• mar31, 9:30pm UTC: 155604 (+10)
• apr01, 2:30am UTC: 154796 (-808)
• apr01, 6am UTC: 154682 (-114)
• apr01, 12:30pm UTC: 154756 (+74)
• apr01, 8pm UTC: 154741 (-15)
• apr02, 4:30am UTC: 154576 (-165)
• apr02, 2pm UTC: 154642 (+66)
• apr02, 6pm UTC: 154642 (0)
• apr03, 2pm UTC: 154397 (-245)
• apr03, 11:30pm UTC: 154398 (+1)
• apr04, 11:30pm UTC: 154314 (-84)
• apr06, 1:30am UTC: 154297 (-17)
• apr06, 1:30pm UTC: 154301 (+4)
• apr07, 4am UTC: 154273 (-28)
• apr07, 1:30pm UTC: 154260 (-13)
• apr08, 1pm UTC: 154417 (+157)
• apr08, 11pm UTC: 154441 (+24)
• apr09, 7pm UTC: 154397 (-44)
• apr10, 2pm UTC: 154377 (-20)
• apr11, 2am UTC: 154330 (-47)
• apr12, 2:30am UTC: 154230 (-100)
• apr13, 1pm UTC: 154277 (+47)
• apr13, 10pm UTC: 154275 (-2)
• apr14, 1pm UTC: 155002 (+727)
• apr14, 7pm UTC: 155004 (+2)
• apr15, 2am UTC: 154980 (-24)
• apr15, 2:30pm UTC: 154935 (-45)
• apr15, 10:30pm UTC: 154943 (+8)
• apr16, 1:30pm UTC: 155031 (+88)
• apr16, 9:30pm UTC: 155139 (+108)
• apr17, 3pm UTC: 154888 (-251)
• apr17, 9:30pm UTC: 154914 (+26)
• apr18, 1pm UTC: 154812 (-102)
• apr18, 9pm UTC: 154823 (+11)
• apr19, 2:30pm UTC: 154826 (+3)
• apr19, 11pm UTC: 154832 (+6)
• apr20, 7pm UTC: 154951 (+119)
• apr20, 11pm UTC: 154949 (-2)
• apr21, 1:30pm UTC: 154880 (-69)
• apr21, 10pm UTC: 154890 (+10)
• apr22, 2pm UTC: 154859 (-31)
• apr23, 1am UTC: 154888 (+29)
• apr23, 2pm UTC: 154849 (-39)
• apr24, 1am UTC: 154840 (-9)
• apr24, 7:30pm UTC: 154824 (-16)
• apr26, 1:30am UTC: 154707 (-117)
• apr27, 11:30am UTC: 154780 (+73)
• apr28, 12:00am UTC: 154755 (-25)
• apr28, 2:30pm UTC: 154711 (-44)
• apr28, 10:30pm UTC: 154679 (-32)
• apr29, 4pm UTC: 154239 (-440)
• apr30, 12:00pm UTC: 154192 (-47)
• apr30, 3pm UTC: 154191 (-1)
• may01, 1am UTC: 154093 (-98)
• may01, 12pm UTC: 153788 (-305)
• may01, 9pm UTC: 153865 (+77)
• may02, 2:30pm UTC: 153772 (-93)
• may03, 2pm UTC: 153761 (-11)
• may04, 2am UTC: 153755 (-6)
• may04, 1pm UTC: 153859 (+104)
• may05, 2:30am UTC: 153707 (-152)
• may05, 3:30pm UTC: 153714 (+7)
• may05, 11:30pm UTC: 153684 (-30)
• may06, 5pm UTC: 153660 (-24)
• may07, 1am UTC: 153670 (+10)
• may07, 1pm UTC: 153674 (+4)
• may08, 1pm UTC: 153616 (-58)
• may09, 12am UTC: 153616 (0)
• may10, 3pm UTC: 153439 (-177)
• may11, 1am UTC: 153441 (+2)
• may11, 11:30am UTC: 153566 (+125)
• may12, 4:30am UTC: 153508 (-58)
• may12, 11:30am UTC: 153497 (-11)
• may13, 1:30am UTC: 153455 (-42)
• may13, 12pm UTC: 153625 (+170)
• may14, 6:30pm UTC: 153598 (-27)
• may15, 5:30pm UTC: 153570 (-28)
• may16, 12:30am UTC: 153580 (+10)
• may16, 10:30pm UTC: 153442 (-138)
• may18, 5:30am UTC: 153423 (-19)
• may18, 9pm UTC: 153765 (+342)

153596 Slack #general channel

previous thread: https://www.thelayoff.com/t/1kn4h3j2q

Limitations: to answer a common question what exactly is counted here and how:

Between once a day up to every few hours I manually record Slack total participants count in #general Slack channel of Oracle One workspace - that's where all Oracle employees onboard into corporate Slack account auto-join.

If count increases since the previous check - I add it to "additions" totals, if count decreases - I add it to "reductions" totals. Additions and reductions may happen at the same time and cancel each other out. The higher frequency of sampling - the more additions and reductions are caught.

"Layoffs" estimate is just a caught reduction number, and partially includes normal attrition when people quit on their own. However, a lot of reductions are canceled out due to frequency of sampling, so normal attrition often is already at least partially not part of the count.

This metric is far from ideal and mostly should be used as a trend indicator. It's especially less accurate (has more delay) in EU and Pacific regions, where employees are disconnected from Slack with long delay. However, it reflects the same day layoffs in NA and IDC usually.

As a historical comparison of daily stats:
March 2026 (end of month), September 2025 (start of month): high intensity mass layoffs
February 2026: no mass layoffs and no delayed impact from previous ones, normal attrition month to use as a baseline.

I track it daily since Sep02, 2025. Oracle One slack workspace, #general public channel.
Here is the latest thread https://www.thelayoff.com/t/1kn4h3j2q

Here is this month:
Apr24, 7:30pm UTC - Apr27, 11:30am UTC totals: 117 layoffs, 73 additions.
April totals: 1599 layoffs, and 1583 additions.

• apr01, 2:30am UTC: 154796 (-808)
• apr01, 6am UTC: 154682 (-114)
• apr01, 12:30pm UTC: 154756 (+74)
• apr01, 8pm UTC: 154741 (-15)
• apr02, 4:30am UTC: 154576 (-165)
• apr02, 2pm UTC: 154642 (+66)
• apr02, 6pm UTC: 154642 (0)
• apr03, 2pm UTC: 154397 (-245)
• apr03, 11:30pm UTC: 154398 (+1)
• apr04, 11:30pm UTC: 154314 (-84)
• apr06, 1:30am UTC: 154297 (-17)
• apr06, 1:30pm UTC: 154301 (+4)
• apr07, 4am UTC: 154273 (-28)
• apr07, 1:30pm UTC: 154260 (-13)
• apr08, 1pm UTC: 154417 (+157)
• apr08, 11pm UTC: 154441 (+24)
• apr09, 7pm UTC: 154397 (-44)
• apr10, 2pm UTC: 154377 (-20)
• apr11, 2am UTC: 154330 (-47)
• apr12, 2:30am UTC: 154230 (-100)
• apr13, 1pm UTC: 154277 (+47)
• apr13, 10pm UTC: 154275 (-2)
• apr14, 1pm UTC: 155002 (+727)
• apr14, 7pm UTC: 155004 (+2)
• apr15, 2am UTC: 154980 (-24)
• apr15, 2:30pm UTC: 154935 (-45)
• apr15, 10:30pm UTC: 154943 (+8)
• apr16, 1:30pm UTC: 155031 (+88)
• apr16, 9:30pm UTC: 155139 (+108)
• apr17, 3pm UTC: 154888 (-251)
• apr17, 9:30pm UTC: 154914 (+26)
• apr18, 1pm UTC: 154812 (-102)
• apr18, 9pm UTC: 154823 (+11)
• apr19, 2:30pm UTC: 154826 (+3)
• apr19, 11pm UTC: 154832 (+6)
• apr20, 7pm UTC: 154951 (+119)
• apr20, 11pm UTC: 154949 (-2)
• apr21, 1:30pm UTC: 154880 (-69)
• apr21, 10pm UTC: 154890 (+10)
• apr22, 2pm UTC: 154859 (-31)
• apr23, 1am UTC: 154888 (+29)
• apr23, 2pm UTC: 154849 (-39)
• apr24, 1am UTC: 154840 (-9)
• apr24, 7:30pm UTC: 154824 (-16)
• apr26, 1:30am UTC: 154707 (-117)
• apr27, 11:30am UTC: 154780 (+73)

Previous totals:

• mar01-mar31: 12446 layoffs, and 844 additions (based on Slack regular tracking)
• feb01-feb28: 943 layoffs, and 1143 additions (based on Slack regular tracking)
• jan01-jan31: 1604 layoffs, and 1834 additions (based on Slack regular tracking)
• dec01-dec31: 1031 layoffs, and 844 additions (based on Slack regular tracking)
• nov01-nov30: 1614 layoffs, and 1327 additions (based on Slack regular tracking)
• oct01-oct31: 2504 layoffs, 1762 additions (based on Slack regular tracking)
• sep02-sep30: 6275 layoffs, 861 additions (based on Slack regular tracking)
• aug14-sep01: 733 layoffs (based on Slack very few data points)
• aug01-aug14: ?2900 layoffs in IDC (based on media reports)

@kr Aug01-14 there were mainstream media reports with specific numbers for IDC.
for Aug14 I got the first Slack #general channel total in Oracle One workspace: 173529. Starting from Sep02 when layoffs started in NA I was tracking that channel totals daily, sometimes there gaps, in intense periods I was sampling every few hours.
So my additions and reductions are the floor estimates, the minimum, because I just check total change and sometimes both reductions and additions happen at the same period of time and cancel each other out and are not caught by totals change.

On the other hand, there is also a normal attrition when people leave on their own, based on months tracked without any layoffs, the best example would be Feb 2026, by that time all Slack counts were reflected since 2025 layoffs and no mass layoff started yet, so normal monthly attrition looked like ~1k people leaving and adding:

• feb01-feb28: 943 layoffs, and 1143 additions (based on Slack regular tracking)

OP, why are you lying if we can literally all check #general in Oracle One workspace?

• apr01, 2:30am UTC: 154796
• apr01, 6am UTC: 154682 (-114)
• apr01, 12:30pm UTC: 154756 (+74)
• apr01, 8pm UTC: 154741 (-15)
• apr02, 4:30am UTC: 154576 (-165)
• apr02, 2pm UTC: 154642 (+66)
• apr02, 6pm UTC: 154642 (0)

Europe is not done yet. Neither does the #General Slack statistic tell you everything.

Slack will only be accurate once everyone is removed from the system. The legal process means that many (certainly once they get to Europe) will have a last working day some weeks, or months, away.

Limitations: to answer a common question what exactly is counted here and how:

Every few hours I manually record Slack total participants count in #general Slack channel of Oracle One workspace - that's where all Oracle employees onboarded into corporate Slack account auto-join.

If count increases since the previous check - I add it to "additions" totals, if count decreases - I add it to "layoffs" totals. Obviously, additions and reductions may happen at the same time and cancel each other out. The higher frequency of sampling - the more additions and reductions are caught.

"Layoffs" is just a caught reduction number, and partially includes normal attrition when people quit on their own. However, a lot of reductions are canceled out due to frequency of sampling, so normal attrition often is already at least partially not part of the count.

Obviously this metric is far from ideal and mostly should be used as a trend indicator. It's especially less accurate (has more delay) in EU and Pacific regions, where employees are disconnected from Slack with long delay. However, it reflects the same day layoffs in NA and IDC usually.

As a historical comparison of daily stats:
September 2025: high intensity mass layoff, especially first few days
February 2026: no mass layoffs, normal attrition month to use as a baseline

no

Slack #general totals in Oracle One Slack workspace

• mar23, 6:30pm UTC: 166540 (-3)
• mar24, 1am UTC: 166542 (+2)
• mar24, 1:30pm UTC: 166434 (-108)
• mar24, 10:30pm UTC: 166432 (-2)
• mar25, 1pm UTC: 166343 (-89)
• mar25, 3pm UTC: 166325 (-18)
• mar25, 8:30pm UTC: 166092 (-233)
• mar25, 9pm UTC: 166072 (-20)
• mar25, 11pm UTC: 165995 (-77)
• mar26, 1pm UTC: 165865 (-130)
• mar26, 6:30pm UTC: 165800 (-65)
• mar27, 3:30am UTC: 165707 (-93)
• mar27, 2pm UTC: 165736 (+29)
• mar27, 8pm UTC: 165723 (-13)
• mar28, 2:30pm UTC: 165526 (-197)
• mar30, 12:30pm UTC: 165614 (+88)
• mar30, 4pm UTC: 165589 (-25)
• mar30, 9:30pm UTC: 165333 (-256)
• mar31, 2am UTC: 165228 (-105)
• mar31, 5am UTC: 165198 (-30)
• mar31, 12:30pm UTC: 155607 (-9591)
• mar31, 6pm UTC: 155594 (-13)
• mar31, 9:30pm UTC: 155604 (+10)
• apr01, 2:30am UTC: 154796 (-808)

saas channel: -360
#general saas: -490

@q4 there are also some more targeted #general channels that can be used for the same calculations. for example #general in the "Oracle Health" workspace, which seems to have users from appropriate orgs added automatically.

this round stats on #general on Oracle One workspace:

• mar23, 6:30pm UTC: 166540 (-3)
• mar24, 1am UTC: 166542 (+2)
• mar24, 1:30pm UTC: 166434 (-108)
• mar24, 10:30pm UTC: 166432 (-2)
• mar25, 1pm UTC: 166343 (-89)
• mar25, 3pm UTC: 166325 (-18)
• mar25, 8:30pm UTC: 166092 (-233)
• mar25, 9pm UTC: 166072 (-20)
• mar25, 11pm UTC: 165995 (-77)
• mar26, 1pm UTC: 165865 (-130)
• mar26, 6:30pm UTC: 165800 (-65)
• mar27, 3:30am UTC: 165707 (-93)
• mar27, 2pm UTC: 165736 (+29)
• mar27, 8pm UTC: 165723 (-13)
• mar28, 2:30pm UTC: 165526 (-197)
• mar30, 12:30pm UTC: 165614 (+88)
• mar30, 4pm UTC: 165589 (-25)
• mar30, 9:30pm UTC: 165333 (-256)
• mar31, 2am UTC: 165228 (-105)
• mar31, 5am UTC: 165198 (-30)
• mar31, 12:30pm UTC: 155607 (-9591)

the largest single day drop previously was on September 02, 2025, when 3.4k dropped within 24h.
and NA timezone hasn't even started yet.

They cannot shut down #general on Oracle One Slack workspace, that is a default workspace channel every new account auto joina. You can create your own Slack workspace against you personal email and verify that's how Slack works

To answer a common question what exactly is counted here and how:

Every few hours I manually record Slack total participants count in #general Slack channel of Oracle One workspace - that's where all Oracle employees onboarded into corporate Slack account auto-join.

If count increases since the previous check - I add it to "additions" totals, if count decreases - I add it to "layoffs" totals. Obviously, additions and reductions may happen at the same time and cancel each other out. The higher frequency of sampling - the more additions and reductions are caught.

"Layoffs" is just a caught reduction number, and partially includes normal attrition when people quit on their own. However, a lot of reductions are canceled out due to frequency of sampling, so normal attrition often is already at least partially not part of the count.

Obviously this metric is far from ideal and mostly should be used as a trend indicator. It's especially less accurate (has more delay) in EU and Pacific regions, where employees are disconnected from Slack with long delay. However, it reflects the same day layoffs in NA and IDC usually.

As a historical comparison of daily stats:
September 2025: high intensity mass layoff, especially first few days
February 2026: no mass layoffs, normal attrition month to use as a baseline

@a6 just stop lying
mass layoffs indeed started today, and dropped 471 past 2.5 days (360 past 23h),

#general Slack count in Oracle One workspace:

• mar23, 2:30pm UTC: 166543
• mar23, 6:30pm UTC: 166540 (-3)
• mar24, 1am UTC: 166542 (+2)
• mar24, 1:30pm UTC: 166434 (-108)
• mar24, 10:30pm UTC: 166432 (-2)
• mar25, 1pm UTC: 166343 (-89)
• mar25, 3pm UTC: 166325 (-18)
• mar25, 8:30pm UTC: 166092 (-233)
• mar25, 9pm UTC: 166072 (-20)

yes, mass layoff started today
methodology, tracking total headcount in #general Slack channel of Oracle One workspace:

• mar24, 10:30pm UTC: 166432 (-2)
• mar25, 1pm UTC: 166343 (-89)
• mar25, 3pm UTC: 166325 (-18)
• mar25, 8:30pm UTC: 166092 (-233)
• mar25, 9pm UTC: 166072 (-20)

It has not dropped 2,000 in the past 2 days. I've been tracking since 3/10. at it's peak this month #general in OO had 166,554. As of today it's 166,220. So it's dropped 334 and climbing.

IDC disconnects from Slack right away, and here are Slack total stats for #general in Oracle One workspace across the company:

• mar23, 2:30pm UTC: 166543 (+257)
• mar23, 6:30pm UTC: 166540 (-3)
• mar24, 1am UTC: 166542 (+2)
• mar24, 1:30pm UTC: 166434 (-108)

looks so far as part of normal deviation, no mass layoff happened in IDC past two days.

@ad That is not the point. Nobody thinks layoffs aren't happening.

The point is it's not started yet. In #general there are 15 more people in comparison to yesterday and 7 more in comparison to 2 days ago.

Despite this 45k in one go may be way too much.

Slack #general shows a wopping less 7 people from 24 hours ago

@cj everyone cannot post on #general. Oracle is not d-mb. Heh

Assuming that layoff happened, it may be an unrelated layoff from the mass layoffs. And a lot of other comments may be the trolls that have been pestering it here.

The #general channel barely changed from Yesterday to Today.

I see 6 less people from Yesterday in #general

• Yesterday, 17th of March 166,494 at 6 PM GMT
• Today, 18 of March, 166,488, at 9 AM GMT

@b6 That stuff USED to be posted to #watercooler, I was seeing a lot of them before I was let go. I was told they deleted that channel a week or so after I got it. Where ELSE is anyone to post about it? Heh, they SHOULD use #general, they're not going to delete that one.