Scenario wins: pgodzinbot (5) Mantic (2) Panshul42 (2) hayek-bot (1) lewinke-thinking-bot* (1)
| Figure/Metric | Value | Source | Significance |
|---|---|---|---|
| Challenger Job Cuts (May 2026) | 97,006 | Trading Economics | Measures broader US layoff environment; currently at elevated levels. |
| Tech Layoffs YTD (May 31, 2026) | 123,653 | Challenger, Gray & Christmas | 65% increase over 2025; suggests a high-volatility year. |
| LinkedIn Scheduled Layoffs | 606 | Yahoo Finance (May 19) | Effective July 13, 2026; high probability of a July tracker entry. |
| Amazon WARN Notice (FL) | 616 | Yahoo Finance (April 20) | Effective July 2, 2026; likely July-dated entry for Post-IPO firm. |
| Intuit Restructuring Charge | $300M - $340M | SEC 10-Q (May 20) | Covers 3,000 job cuts with July 31 exit; likely announcement-dated in May. |
To forecast the number of layoffs of 400 or more employees at Post-IPO or Acquired companies recorded by layoffs.fyi in July 2026, I analyzed current macroeconomic trends, corporate restructuring cycles, and historical reporting patterns.
First, I examined specific scheduled events. Several large-scale restructurings were announced in May and June 2026, including Intuit (3,000 jobs), Cisco (4,000), and LinkedIn (606). While these have significant July components—such as LinkedIn’s July 13 effective date and Intuit’s July 31 exit date—the layoffs.fyi tracker historically records entries based on the date of the public announcement rather than the actual termination date. Consequently, many of the most significant 2026 tech layoffs likely appeared on the tracker in May or June, rather than July.
Second, I looked at known July catalysts. Amazon filed a WARN notice for 616 layoffs at its Homestead, Florida facility effective July 2, 2026. This is a primary candidate for a July entry. Additionally, the end of the fiscal year for several major tech firms (like Microsoft) in June often leads to reorganization announcements in early July. However, July is also characterized by a “summer slowdown” in corporate communications, which typically results in fewer fresh announcements compared to the volatile start of a calendar year or the end of a fiscal quarter.
Third, I assessed the broader macroeconomic environment. Data from Trading Economics shows that Challenger Job Cuts reached 97,006 in May 2026, placing the market in the 75th to 95th percentile of historical activity. This elevated baseline suggests that while July might be seasonally slower, the underlying pressure to restructure around AI and “lean” business models remains high. The 2026 year-to-date total for tech layoffs (over 123,000 by June) indicates a more aggressive environment than 2025.
My reasoning places the highest probability on 1 or 2 qualifying entries. The probability of 0 entries is low due to the Amazon and LinkedIn scheduled events. Conversely, the probability of exceeding 5 entries is limited by the “Stage” (Post-IPO/Acquired) and “Size” (400+) filters, which exclude the vast majority of smaller startup layoffs that populate the tracker daily. The forecast uses a lognormal distribution to reflect this positive skew, centering the mass between 0.5 and 2.5 entries while allowing for a tail that accounts for a potential wave of mid-summer earnings-related cuts.
Question: How many layoffs.fyi rows visible at 2026-08-06 will be dated in July 2026, list a numerical # Laid Off ≥400, and have Stage exactly Post-IPO or Acquired? The resolution is purely mechanical to the tracker table on Aug 6, so the main uncertainties are how layoffs.fyi will date events, whether # Laid Off is recorded numerically and ≥400, and late additions before the Aug 6 cutoff. Forecasters anchored on a same-month analogue (July 2025) that produced about three qualifying rows and a high-wave analogue (March 2026) that produced ~6, and noted the current environment is unusually active for large public/acquired tech cuts (e.g., strong YTD tech totals and many AI-related restructurings). Several watch-list cases (Meta, LinkedIn, Intuit, Rackspace) could push July counts higher but may be dated by layoffs.fyi to their earlier announcement months or omit numeric headcounts, and many stories fall below the 400 threshold or into Stage Unknown. Reporting lag is material but partly covered by the Aug 6 cutoff (about six days after July ends); the teams therefore center the forecast around roughly 3–5 qualifying rows with a meaningful right tail to ~6–8 in a clustered month and low probability of exceeding ~10. Overall the teams largely agree on the mechanical constraints and priors, differing only slightly on how heavy the right tail should be given current activity.
Forecast: Probability distribution:
We need the count of layoffs.fyi tracker rows with (a) Date in July 2026, (b) # Laid Off ≥ 400 as a numeric value, and (c) Stage = Post-IPO or Acquired, as visible on 2026-08-06 12:00 UTC.
Across the four analyst forecasts, the main disagreement is the center of the distribution: two forecasts (F1/F2) implicitly assume a fairly high monthly rate of ≥400 layoffs among public/acquired firms (median 5–6 and a substantial chance of ≥11), while two (F3/F4) emphasize the restrictiveness of the filters and seasonality (median ~3–4, but with an overdispersed right tail due to some layoffs being split into multiple tracker rows).
I weight F4’s structural point about row-splitting (which can inflate counts in months with one or two very large public-company actions) and F3’s caution about the filter being restrictive, but I pull the median upward from 3–4 to ~5 because (i) the ≥400 threshold tends to select for larger, often Post-IPO/Acquired companies, and (ii) the resolution time (Aug 6) allows some backfilling of July-dated events. Seasonality and the possibility that June/July are quieter than Q1 keep the lower tail meaningful. I retain a modest open-above tail (≥11) because clustered announcements or a single multi-site restructuring can create many qualifying rows.
Net: most mass in 3–7, median just under 5, with ~5–10% probability of landing at 11+ (open tail).
An amateur forecast is likely to (a) confuse “number of employees laid off” with “number of qualifying tracker rows”, (b) ignore the Stage and ≥400 filters (overestimating), or (c) ignore that large layoffs can be split into multiple rows by location/WARN notice (underestimating the right tail). This forecast explicitly targets the tracker-row counting rule, incorporates the restrictive filters, and still preserves a realistic overdispersed upper tail (including open-above mass) rather than collapsing everything into a narrow range. Confidence is moderate because the outcome is sensitive to month-specific corporate timing and how layoffs.fyi encodes large events.
Forecast rationale (numeric):
— Iteration 1 — The forecasts converge on a mid-single-digit outcome, with a central expectation of about 4–5 qualifying layoffs.fyi entries in July 2026 for Post-IPO or Acquired companies with 400+ employees laid off.
The shared forecast is that July 2026 will likely see about four or five qualifying layoffs.fyi entries in this category, with uncertainty driven more by data capture and event clustering than by disagreement about the overall direction.
— Iteration 2 — Across the forecasts, the shared view is that July 2026 will likely produce a low-to-mid single-digit number of qualifying layoffs.fyi entries for Post-IPO or Acquired companies with 400+ layoffs. The main reasoning is that while overall 2026 layoff activity remains elevated, the subset of very large, discrete layoff events is still relatively small. Because the question only counts large events at later-stage companies, the expected monthly count is much lower than total layoffs.
Overall, the collective reasoning points to modestly elevated but still limited monthly incidence, with the final observed number depending heavily on whether July includes a cluster of large public-company layoffs and how much of that activity is visible by the recording cutoff.
— Iteration 3 — The forecasts converge on a low single-digit expectation for July 2026, with a median around 3–4 qualifying layoffs at Post-IPO or acquired companies. The shared logic is:
Consensus: low single digits, slightly right-skewed, with a meaningful chance of 0–2 but also some possibility of a larger cluster.
Main disagreement: whether the center is closer to 3 or 4, and how wide the upper tail should be.
Summary of Rationales
The rationales broadly agree on the primary structural drivers and methodological constraints shaping this forecast. The reasoning is divided into two main categories: macroeconomic catalysts driving layoffs upward, and strict database rules pulling the final eligible count downward.
Macroeconomic Drivers & July Seasonality Forecasters note that early 2026 has seen an elevated baseline of major tech layoffs, heavily driven by an “AI restructuring” wave where Post-IPO companies are trimming legacy operational costs to fund massive AI capital expenditures. While July is historically a summer lull, it frequently experiences a secondary tactical spike due to Q2 earnings season. Public companies often use mid-to-late July earnings calls to announce strategic workforce reductions to defend profit margins. Additionally, forecasters specifically highlight expected July restructuring announcements tied to the start of new fiscal years, most notably anticipated cuts at Microsoft’s Xbox division.
Methodology & Resolution Constraints Despite strong catalysts for July layoffs, forecasters unanimously emphasize that the strict rules of Layoffs.fyi and the resolution criteria will artificially depress the final count:
Question: How many layoffs of 400 or more employees will layoffs.fyi record in July 2026 at Post-IPO or Acquired companies? Final Prediction: Probability distribution:
Total Cost: extra_metadata_in_explanation is disabled Time Spent: extra_metadata_in_explanation is disabled LLMs: extra_metadata_in_explanation is disabled Bot Name: extra_metadata_in_explanation is disabled
Forecaster 1: Probability distribution:
Forecaster 2: Probability distribution:
The research summarizes the June 2026 tech-layoff wave by reporting that layoffs.fyi recorded roughly 118,312 tech job cuts across 183 companies as of mid-June 2026, with an average of about 1,115 layoffs per working day and 2026 on pace to rival 2023’s peak (~260,000). It lists major Post-IPO employers with large 2026 cuts (Oracle ~30,000; Amazon ~16,100; Dell ~11,000; Meta ~8,000–10,400; PayPal ~4,760; Cisco ~4,000; Block ~4,000; Intuit ~3,000; Snap ~1,000) and notes that AI-related restructuring has been a primary driver (over ~87,000 layoffs in 2026 attributed to AI). Historical and monthly context is given: 2025 totaled ~124,636 tech layoffs; Jan–Apr 2026 saw ~85,411 cuts (a 33% YoY increase); March and May 2026 were particularly large months (March ~46,000; May ~28,900–40,000).
For July 2026 specifically, the research highlights concrete timing: Intuit’s 3,000 layoffs show a July 31, 2026 exit date (Intuit is Post-IPO), and Meta has a Washington-state action affecting about 1,400 jobs starting July 22, 2026. It notes uncertainties that affect counting entries on layoffs.fyi (whether large cuts are logged as single or multiple entries, classification between “Post-IPO” and “Acquired,” announcement vs. execution dates, and lack of historical month-by-stage breakdown). The research also states no prediction-market lines specific to this layoffs.fyi July question were found and identifies the Intuit July 31 exit date as the most concrete datapoint that would meet the ≥400-post-IPO/acquired threshold if recorded as a single July entry.
Sources/websites used in the research:
Based on my research into current tech industry layoff trends, here’s a comprehensive rundown for forecasting the number of layoffs of 400+ employees at Post-IPO or Acquired companies that layoffs.fyi will record in July 2026:
The tech industry is experiencing an intense layoff wave in 2026:
Major Post-IPO companies that have announced significant cuts:
Critical findings for July 2026:
Historical Context:
Monthly Patterns:
Seasonality Considerations:
Size Distribution: Most 2026 layoffs appear to be concentrated in very large companies doing substantial cuts (1,000+), but the question requires identifying individual entries ≥400 employees specifically categorized as Post-IPO or Acquired.
Over 87,000 layoffs in 2026 have been attributed to AI (already exceeding 2025’s full-year total) [11]. Companies are restructuring to fund massive AI investments while claiming efficiency gains [3][4][7][20].
No specific markets found for this question, though I identified major prediction market platforms:
The Intuit layoff with July 31 exit date appears to be the most concrete datapoint for July 2026, representing 3,000 employees at a Post-IPO company, though this exceeds 400, it would count as at least 1 entry if layoffs.fyi records it as a single event in July.
The high volume of layoffs in 2026 combined with specific July timing for some companies suggests July could see several qualifying entries, but without historical July-specific data broken down by stage and size threshold, precise base rate estimation is challenging.
Conditioning on the question not being annulled.
I agree with the critic’s main correction: my initial base rate was too diluted by 2025 and by the 500+ approximation. The 2026 regime has already produced many qualifying-looking large mature-company rows: January’s largest-event table alone has seven Post-IPO rows at or above 400, February has six Post-IPO/Acquired rows at or above 400, and May has roughly eleven once Groupon’s exact 400 row is included. (raw.githubusercontent.com) That makes a median near 3 too low if July 2026 behaves like a typical 2026 active month.
I also agree that the Intuit/Meta “known July” evidence should be almost fully discounted. The key issue is the tracker’s Date field, not WARN/effective date. The May report already records Meta and Intuit as May 20 entries with numerical headcounts and Post-IPO stage, so I should not treat those as banked July rows. (raw.githubusercontent.com) July still has to “earn” its count through July-dated entries or revisions visible by August 6.
Where I still defend the initial caution: this is a brittle database-count question, not a total-layoffs question. Layoffs.fyi says it tracks layoffs that are media-reported, company-announced, or otherwise verified, and that unreported/unverified layoffs are excluded. (layoffs.fyi) July 2025 is a good warning: the dataset shows 31 events and 16,648 reported layoffs, but only three obvious qualifying ≥400 Post-IPO/Acquired rows—Microsoft, Intel, and Indeed + Glassdoor—while other large-sounding stories such as Amazon/WiseTech had null headcount fields and would not count. (raw.githubusercontent.com)
A new adjustment I’d add is that June’s partial data is a meaningful downward signal after the May spike. The current derived tracker has 2026 YTD at about 118.8k through June 16, with May already accounting for 28,934; the recent June entries shown through mid-month are mostly small or null-headcount, not obviously qualifying 400+ mature-company rows. (tech.debugcanada.com) So I do not want to simply average January–May and center at 5–6.
Net: I move upward from my prior forecast, but not all the way to a very high-count view. My revised mental model is a mixture: quiet/summer/front-loaded scenario gives 0–2; normal elevated-2026 scenario gives 3–5; July earnings/AI-restructuring cluster gives 6–8; a May-like spike gives 9+ but remains relatively uncommon. I’m setting the median around 4, with a fatter upper-mid tail than before and about ~1–2% mass above 10.
Updated prediction:
Percentile 0.1: 0.05
Percentile 1: 0.15
Percentile 5: 0.45
Percentile 10: 0.85
Percentile 20: 2.05
Percentile 30: 2.65
Percentile 40: 3.25
Percentile 50: 4.05
Percentile 60: 4.40
Percentile 70: 5.15
Percentile 80: 6.05
Percentile 90: 7.35
Percentile 95: 8.55
Percentile 99: 10.75
Percentile 99.9: 13.75
I agree with the critic’s strongest point: my distribution was still too light in the 6–10 band. The mirror data make clear that this is not a smooth Poisson-like count. May 2026 alone appears to have at least 11 target-like rows in the mirror—Meta, PayPal, Cisco, Intuit, Cloudflare, Wix, LinkedIn, Bill.com, Coinbase, ZoomInfo, and Groupon—meeting the num_laid_off >= 400 and Post-IPO/Acquired-style criteria. The broader stage-size heatmap also supports a higher baseline than “3-ish”: it shows many Post-IPO rows above 500 and a sizable 100–499 bucket where some rows will be 400–499. (raw.githubusercontent.com)
I also now put more weight on Microsoft/Xbox as a real July-specific catalyst. Reuters, citing Bloomberg, reported on June 10, 2026 that Microsoft’s Xbox division is planning major layoffs “next month,” expected shortly after Microsoft’s fiscal year closes on June 30, while noting that the exact scale is unclear. I would treat this as perhaps a 60–70% chance of adding at least one qualifying July row, with a smaller chance of multiple rows if layoffs.fyi splits gaming/studio entities. (investing.com)
I still defend not moving all the way to the critic’s suggested upper tail. The resolution is not “how many major layoffs happen,” but a narrow tracker-row count requiring a July date, numeric # Laid Off >= 400, and exact Stage of Post-IPO or Acquired. Tracker friction remains substantial: the mirror explicitly notes that rows without headcount are excluded from headcount totals and that stage/headcount fields are incomplete; June 1–16, 2026 remains a cautionary live signal, with only 1,887 reported layoffs across 23 events and GitLab at 350 as the largest numeric row. (tech.debugcanada.com)
The outside view is also mixed. Challenger’s May 2026 report supports elevated tech-cut risk—Technology announced 38,242 cuts in May and AI was cited in 87,714 cuts YTD—but July 2025 shows that even a large headline layoff month can translate into only a few qualifying rows: visible large items included Microsoft’s 9,000 and Indeed/Glassdoor’s 1,300, not a huge number of independent tracker rows. (challengergray.com)
So I am moving upward again, especially from p60 through p95. My current view is roughly: median about 4, mean around 4.8–5.0, P(0–1) around 9–10%, P(≥8) around 15–17%, and P(>10) around 3%. This is a lumpy mixture: quiet/no-number July remains plausible, but Microsoft plus a routine earnings-cycle cluster can easily produce 6–9.
Updated prediction:
Percentile 0.1: 0.01
Percentile 1: 0.08
Percentile 5: 0.52
Percentile 10: 0.98
Percentile 20: 1.82
Percentile 30: 2.72
Percentile 40: 3.62
Percentile 50: 4.38
Percentile 60: 5.20
Percentile 70: 6.20
Percentile 80: 7.20
Percentile 90: 9.05
Percentile 95: 10.20
Percentile 99: 13.90
Percentile 99.9: 18.80
Modal: 1-3 (19.9%) • frontier aggregate • 6m16s
Resolution sources/checks:
Edge cases:
frontier_1 — Modal: 6-8 (24.0%)
2026 mid-year layoff activity appears elevated, with a layoffs.fyi-derived dashboard (ByLiem) indicating ~169 companies and ~117k impacted by early June, implying ~30+ events/month and an average size near 700—suggesting a substantial share of events exceed 400. Larger cuts disproportionately occur at public/acquired firms, so the Stage filter should still leave several qualifying entries.
frontier_2 — Modal: 1-3 (20.0%)
The question counts layoffs.fyi entries with Date in July 2026, # Laid Off >= 400, and Stage = ‘Post-IPO’ or ‘Acquired’, as visible at the Aug 6 2026 snapshot. The binding filters are the 400+ headcount threshold and the Post-IPO/Acquired stage restriction. Research indicates 2026 is running at an elevated layoff pace (~152k impacted by ~May vs 245k for all of 2025), and July historically sees fiscal-year-driven big-company cuts (Microsoft’s July 2025 ~9,000, July 2025 total ~16,327).
frontier_3 — Modal: 1-3 (18.0%)
Based on the proxy data in the available search results, there have been approximately 397 layoffs in the tech industry impacting roughly 152,000 employees over the first 5.5 months of the reference year. This indicates an average of ~72 layoffs per month with an average size of ~384 employees. The criteria for this resolution restrict qualifying layoffs to a specific stage (‘Post-IPO’ or ‘Acquired’) and a high numeric threshold (>= 400 employees).
frontier_4 — Modal: 1-3 (40.0%)
Historical July data from 2024-2025 shows 3-6 large (≥400) tech layoff events per month total, of which roughly 30-50% are Post-IPO or Acquired, producing an expected 1.5-4 qualifying rows. The central tendency of 3-5 events places the bulk of probability on bins 1-3, with modest right skew.
Two lanes (frontier_2, frontier_4) did not show evidence of querying the exact layoffs.fyi snapshot / resolver artifact and rely primarily on historical aggregates/reference-class heuristics; frontier_4 is also overconcentrated and underweights plausible right-tail outcomes given the resolution’s strict field-level rules. Consider preserving their contributions but flagging them for review when the resolver snapshot is available.
Revision: Frontier revision skipped: no_selected_adjudicator_reviews.
| Bin | Probability |
|---|---|
| 0 | 3.5% |
| 1-3 | 19.9% |
| 3 | 12.7% |
| 4 | 15.5% |
| 5 | 14.9% |
| 6-8 | 18.2% |
| 8 | 6.3% |
| 9 | 4.2% |
| Above 10 | 4.8% |
wooley_rhino • run ae633eec • $2.88 • 6m16s
Extracted Percentile Values: {0.1: 1.01, 1.0: 1.2, 5.0: 1.7, 10.0: 2.2, 15.0: 2.7, 20.0: 3.1, 25.0: 3.5, 30.0: 3.9, 35.0: 4.3, 40.0: 4.7, 45.0: 5.0, 46.0: 5.1, 47.0: 5.2, 48.0: 5.3, 49.0: 5.4, 50.0: 5.5, 51.0: 5.6, 52.0: 5.7, 53.0: 5.8, 54.0: 5.9, 55.0: 6.0, 60.0: 6.4, 65.0: 6.9, 70.0: 7.4, 75.0: 7.9, 80.0: 8.5, 85.0: 9.3, 90.0: 10.2, 95.0: 11.8, 99.0: 13.9, 99.9: 16.8}
Model’s Answer: Step one is to anchor on the current 2026 layoff environment, not on the 2023 peak. The best recent inputs say tech layoffs are still elevated in 2026, with large public firms continuing AI-driven restructuring and cost cuts, but the environment is not as crisis-like as early 2023. That pushes me away from very low counts, but also away from peak-wave double-digit counts as the base case.
Step two is to focus on the exact filter, because that matters more than the broad layoff headlines. This question is not asking for all July 2026 layoffs.fyi rows. It only counts rows dated in July, with at least 400 laid off, and stage equal to Post-IPO or Acquired. That is a meaningful minority of all layoffs.fyi entries, but it is also the part of the tracker most likely to generate 400-plus events. Large public companies and acquired units are where most of the 400-plus cuts come from.
Step three is to translate the broader 2026 pace into this narrower metric. The social-media research says layoffs.fyi is showing 188 companies YTD as of June 17, which is roughly in the low-30s per month overall. Only a subset will be Post-IPO or Acquired, and only a subset of those will be at least 400. My rough conversion puts a normal elevated month in the neighborhood of about 5 to 7 qualifying entries, with July perhaps slightly softer than January-type restructuring months but still supported by post-earnings and half-year reorg timing.
Step four is to resist overconfidence. I do not have authoritative historical month-by-month counts for this exact layoffs.fyi filter, and the tracker can revise or add rows with some lag. Because of that, I want a wider distribution than my point intuition alone would suggest. My central tendency is around 5 to 6, but I want meaningful mass from roughly 3 through 10, plus a real right tail if several large public-company cuts bunch into July.
The main assumption most likely to matter is that July 2026 behaves like an elevated-but-not-exceptional month for big-tech restructuring. I think there is about a 25 percent chance this is wrong. If wrong to the downside, July could be a seasonal lull with several announcements landing in June or August instead. If wrong to the upside, earnings-season and AI reallocation announcements could cluster.
The next key assumption is that the share of total July layoffs.fyi entries meeting both filters stays in the same broad range as recent history. I put about a 30 percent chance on this being materially wrong, because one or two mega-cap announcements can distort the monthly mix a lot.
The third assumption is that layoffs.fyi capture and classification by August 6 are reasonably complete for July-dated events. I put about a 20 percent chance on this being meaningfully wrong. If the tracker is slow to add or revise late-July rows, the resolved count could undershoot the “true” real-world number of qualifying layoffs.
A low outcome would come from a relatively quiet summer month, with most public-company cuts either smaller than 400, tagged under a different stage, or shifted outside July. I think a low outcome of about 3 or fewer is roughly a one-in-five scenario.
A high outcome would come from several large Post-IPO firms announcing July restructurings at once, plus one or two acquired-company integrations being logged as separate rows. I think a high outcome of about 10 or more is roughly a one-in-seven scenario.
Putting that together, my distribution centers on 5 to 6, with a 90 percent interval roughly from a bit above 2 to around 12, and a long but not huge right tail.
Percentile .1: 1.01 Percentile 1: 1.2 Percentile 5: 1.7 Percentile 10: 2.2 Percentile 15: 2.7 Percentile 20: 3.1 Percentile 25: 3.5 Percentile 30: 3.9 Percentile 35: 4.3 Percentile 40: 4.7 Percentile 45: 5.0 Percentile 46: 5.1 Percentile 47: 5.2 Percentile 48: 5.3 Percentile 49: 5.4 Percentile 50: 5.5 Percentile 51: 5.6 Percentile 52: 5.7 Percentile 53: 5.8 Percentile 54: 5.9 Percentile 55: 6.0 Percentile 60: 6.4 Percentile 65: 6.9 Percentile 70: 7.4 Percentile 75: 7.9 Percentile 80: 8.5 Percentile 85: 9.3 Percentile 90: 10.2 Percentile 95: 11.8 Percentile 99: 13.9 Percentile 99.9: 16.8
The observable count is constrained by discrete event counting, calendar seasonality, and a short July reference class.
Post-IPO and acquired firms form a limited subpopulation whose inclusion depends on explicit stage tagging and numeric completeness.
Macro and sectoral pressure remains elevated, increasing the pool of potential qualifying events without guaranteeing visible rows.
Mergers, acquisitions, and public-company restructurings are the active forces most likely to produce 400+ employee entries.
If multiple large public or acquired firms schedule coordinated restructurings in July, the visible count can jump into the right tail.
If numeric layoff fields are left blank or dates are adjusted before the cutoff, apparent counts will understate actual reductions.
The chief uncertainties are reporting latency, field completeness at the cutoff timestamp, and the timing of corporate disclosures.
Sensitivity to single large announcements is high because each qualifying corporation contributes one row, not a scaled weight.
I anchored first on a long-run base rate using a secondary tracker that explicitly says it scrapes the live Airtable shared view embedded on layoffs.fyi. Over the data range 2025-01-06 to 2026-06-16, its processed stage-size heatmap shows 52 Post-IPO events in size buckets 500-999, 1k-4.9k, and 5k+, plus 8 events in a broader ‘Acquired / PE’ bucket. Because this forecast question excludes Private Equity but includes the 400-499 range, I treat 52 as a clean lower anchor and the broader 60 as an upper-ish anchor; that points to a baseline in the low-3s per month before making any current-regime adjustments. (github.com)
I then adjusted for the fact that the broader tech-layoff environment in 2026 has been unusually hot and highly variable. The trend report says 2026 year-to-date layoffs were 118,847 through June 16, 2026, and identifies March 2026 as the peak month at 46,593 layoffs. The monthly reports show headline totals of 25,148 in January 2026, 11,019 in February, 46,593 in March, 5,016 in April, 28,934 in May, and 1,887 in June through June 16. That is exactly the kind of volatility that makes a single narrow-rate model inappropriate. (tech.debugcanada.com)
I also made a downward near-term adjustment because the current June flow looks soft on the specific resolution criterion. In the current raw mirror, recent June Post-IPO/Acquired rows with numeric headcount include Robinhood (290), Opendoor (250), ServiceNow (54), Salesforce (86), Credit Karma (117), SentinelOne (230), and GitLab (350), all below the 400 threshold. Several other June rows that might sound large in news coverage—such as FanDuel, Google, Uber, Rivian, and Manhattan Associates—show no numeric headcount in the field at all in this snapshot. Since the resolution only counts rows whose ‘# Laid Off’ field itself displays a number of at least 400, missing counts are dead weight unless later revised. (raw.githubusercontent.com)
Seasonality does not make me especially bearish, though. The 2025 yearly report’s largest-event table includes at least two very large July 2025 public-company layoffs: Microsoft at 9,000 on 2025-07-02 and Intel at 5,000 on 2025-07-11. So July is clearly capable of producing multiple qualifying rows; it is not a month I would model as structurally quiet. (tech.debugcanada.com)
Putting those pieces together, my best judgment is that July 2026 is most likely to land in the 3-4 range, with meaningful probability on 1-2 if the June lull persists, and a nontrivial right tail if another public-company restructuring wave appears. I therefore used a three-scenario mixture: 35% soft month (Poisson lambda 1.6), 45% normal month (lambda 3.3), and 20% hot month (lambda 6.0). That mixture has an implied mean of about 3.37. This is an inference from the sourced base rate, the 2026 volatility, and the currently soft June pipeline rather than a direct read-off from any single source. (github.com)
I treated the exact resolver as layoffs.fyi on August 6, 2026, but for forecasting I used current layoffs.fyi-derived structured reports from Tech Layoff Tracker, whose published methodology lists layoffs.fyi as one of its data sources. As of June 16, 2026, its processed stats showed 118,847 reported tech layoffs across the 2025-2026 sample window ending on 2026-06-16, and its 2026 yearly report showed 117,879 reported layoffs across 188 public events through 2026-06-10. (tech.debugcanada.com)
The near-term signal is soft. The monthly trend data show 2026 reported layoff headcount of 25,148 in January, 11,269 in February, 46,593 in March, 5,016 in April, 28,934 in May, and only 1,887 in June through June 16. The June 2026 monthly report says there were 23 public events in June-to-date and the largest disclosed event was GitLab at 350, which is below this market’s 400 cutoff. (raw.githubusercontent.com)
But the base rate for this specific question is still meaningful. In the 2025-2026 stage/size heatmap for disclosed-headcount events, Post-IPO companies account for 17 events in the 500-999 bucket, 26 in 1k-4.9k, and 9 in 5k+, plus 67 more in 100-499. Acquired / PE adds 6, 2, and 0 in the 500+ buckets, plus 19 in 100-499. So there are at least 60 clearly qualifying-like events already from the 500+ buckets alone, and some share of the combined 86 events in the 100-499 buckets should land in 400-499. A uniform split inside that bucket would imply about 21.5 extra cases; spread over roughly 17.5 months in the sample window, that is about 4.5 events per month. I discount that raw rate because Acquired / PE is broader than the resolver’s Acquired label, and because the 100-499 bucket is not guaranteed to be uniform. (github.com)
Lumpiness matters a lot. July 2025 was not a quiet month: the July 2025 report logged 16,648 reported layoffs across 31 public events, led by Microsoft with 9,000 and Intel with 5,000. May 2026 was similarly heavy, with 28,934 reported layoffs across 49 public events, led by Meta with 8,000 and PayPal with 4,760. So a low June-to-date does not eliminate the possibility that July 2026 suddenly produces several large public-company entries. (github.com)
My synthesis is therefore: pull the historical stage-size base rate down because June is currently calm and because the proxy overstates the Acquired bucket a bit, but do not pull it too low because big Post-IPO layoffs arrive in clusters around restructurings and earnings cycles. I model July 2026 as a 3-regime mixture: a quiet month, a normal month, and a hot month. That gives most of the probability mass to 2-4 entries, with a mean a bit above 3, while still leaving visible tail risk for 5+ and a real chance of 0-1 if the June lull persists. My central estimate is 3, with 2 also very plausible as the single exact outcome. This final paragraph is my inference from the cited evidence, not a directly reported statistic. (raw.githubusercontent.com)
As of Wednesday, June 17, 2026, I am forecasting the number of tracker rows layoffs.fyi will show on August 6, 2026 that have a July 2026 date, at least 400 laid off, and stage = Post-IPO or Acquired. The key point is that layoffs.fyi explicitly tracks layoffs that have been publicly reported, announced by the company, or otherwise verified, and it says its figures are likely an undercount of true layoffs. So the forecast is about what gets publicly reported and entered into the tracker, not about all underlying real-world cuts. (layoffs.fyi)
The 2026 backdrop is clearly hot, not quiet. Reuters reports citing layoffs.fyi put tech layoffs at about 40,480 across 70+ companies by March 31, 92,462 by May 5, roughly 103,000 by May 13, and more than 111,000 by May 20. Separately, Challenger said U.S. technology employers announced 38,242 cuts in May alone, the sector’s highest monthly total since August 2024, and said AI was cited in 38,579 May cuts across industries. That combination argues for a July base rate above a normal calm-month assumption. (investing.com)
There is also at least one concrete July candidate already in the pipeline: Reuters reported on June 10 that Microsoft’s Xbox division is planning major layoffs next month, expected shortly after Microsoft’s June 30 fiscal-year close. Meta is another meaningful source of upside risk: Reuters reported on April 17 that after an initial May 20 wave of about 10% of its workforce, the company was planning additional layoffs later in the second half of 2026, though the date and size were not yet settled. Those two items make a zero-entry July materially less likely. (investing.com)
A conservative recent-event read also supports a center around a few entries rather than one big outlier. Reuters-covered 2026 examples that look highly likely to meet this market’s filter include Block (>4,000) in February, Oracle (thousands) in March, Snap (16% of staff) in April, and then a May cluster including Freshworks (500), Coinbase (700), Cisco (nearly 4,000), LinkedIn (5% of >17,500 staff, so roughly 875 by inference), and Intuit (about 3,000). That pattern suggests something like a 2-3-per-month underlying rate for qualifying public/acquired-company rows, with May notably hotter than that baseline. (investing.com)
I therefore center the distribution at about 3.4 qualifying entries for July 2026, with most mass on 2 through 5. I used a negative binomial rather than a Poisson because tracker counts are overdispersed: layoffs cluster around earnings, restructurings, fiscal-year boundaries, and media attention. I keep a noticeable left tail because the tracker only counts verified/public rows and because already-announced restructurings with July effective dates will only count if layoffs.fyi gives them a July row date. But I also keep a real right tail because 2026 layoffs have been unusually concentrated in AI/restructuring waves, and July already has at least one named likely entrant. Overall, my median is 3, my mode is 2, and outcomes above 10 are possible but clearly low-probability. (layoffs.fyi)
The resolution is a row count on layoffs.fyi: rows whose Date is in July 2026, whose # Laid Off is at least 400, and whose Stage is Post-IPO or Acquired, as visible on the tracker at 2026-08-06 12:00 UTC. Layoffs.fyi says it tracks tech layoffs that have been publicly reported or otherwise verified, includes a source for each entry, and is likely an undercount of true tech layoffs. (layoffs.fyi)
The backdrop is still layoff-heavy. Challenger’s official May 2026 report said U.S. technology employers announced 38,242 job cuts in May alone, the sector’s highest monthly total since August 2024, and 123,653 through the first five months of 2026. Separately, a Reuters report on Intuit said that by May 20, Layoffs.fyi was already tracking more than 111,000 layoffs across more than 140 tech companies in 2026. That is strong evidence that July should not be modeled as a quiet or unusual month by default. (challengergray.com)
The kind of companies driving 2026 cuts are also mostly mature firms, so the Post-IPO/Acquired stage filter is less restrictive than it would be in a private-startup wave. In May alone, Reuters or company-linked reporting captured Freshworks cutting about 500 jobs, Coinbase about 700, Intuit about 3,000, Cisco nearly 4,000, Cloudflare about 1,100, and LinkedIn about 5% of staff (roughly 875). Reuters also reported that Meta’s May wave was only the first wave, with additional cuts planned later in 2026. Those facts materially raise the odds of another July entry burst among eligible stages. (investing.com)
Because the live layoffs.fyi table is not easily queryable in this crawler, I used layoffhedge’s June 16 tech-layoff list as a proxy for monthly event cadence and then adjusted downward for source mismatch and for the exact layoffs.fyi stage filter. That proxy shows many tech events of 400+ from January through May 2026, including Oracle, Meta, Amazon, Cognizant, Intel, Dell, Microsoft, Cisco, Cloudflare, Wix, Salesforce, UKG, LinkedIn, eBay, ZoomInfo, Freshworks, CrowdStrike, and Groupon. But it also shows a notably quieter June so far: as of June 16, the June tech entries listed were Ubisoft 380, GitLab 361, Uber 340, Robinhood 290, Opendoor 250, Manhattan Associates 260, and Salesforce 86, i.e. no June tech event above 400 yet. I treat that as real evidence of short-term cooling, but not as evidence that July will also be near zero. (layoffhedge.com)
My forecast therefore uses a three-regime mixture rather than a single Poisson. Regime 1 is a cooldown case after May’s spike and June’s quiet start; Regime 2 is a baseline continuation of the 2026 public-company restructuring wave; Regime 3 is a renewed earnings-season/AI-spend spike. I weighted those regimes at 30%, 55%, and 15%, with means of 1.5, 4.5, and 8.0 respectively. That yields an expected value of 4.125 entries, a median of about 4, most probability mass between 1 and 7, and a smaller but still meaningful right tail for another May-like burst.
My point forecast is 4. The main reasons I am not higher are: June has been quiet so far in the proxy data; some high-profile workforce actions may be logged outside July; and some reductions may be voluntary programs or otherwise not appear on layoffs.fyi in the same way as straight layoff announcements. The main reasons I am not lower are: 2026 tech layoffs remain elevated overall; the big-company/public-company pipeline is still active; and Reuters explicitly reported more Meta cuts later in 2026, which keeps the July hazard rate elevated. (challengergray.com)
I am forecasting the number of July 2026 layoffs.fyi entries that will meet all three filters simultaneously: Date in July 2026, # Laid Off at least 400, and Stage equal to Post-IPO or Acquired. A key constraint is that layoffs.fyi only includes layoffs that are media-reported, company-announced, or otherwise verified, and its own methodology says the tracker is likely an undercount of true tech layoffs. That matters here because even if the real-world number is somewhat higher, the question resolves on what the tracker shows on August 6, 2026. (layoffs.fyi)
For base rates, I put more weight on recent years than on the 2020-2023 period because the current layoff cycle is being driven by AI-related restructuring and large-company efficiency pushes, which look more like 2024-2026 than pandemic-era patterns. TechCrunch’s layoffs archive, which cites layoffs.fyi totals, says 2024 saw more than 150,000 job cuts across 549 companies, with July 2024 at 9,051 layoffs versus 10,083 in June. Its 2025 archive says July 2025 was much hotter: 16,327 layoffs versus only 1,606 in June. So July is not reliably a quiet month; it can be ordinary or very active depending on the corporate news flow. (techcrunch.com)
The strongest signal is the current 2026 environment. SIVL’s company tracker says the last 12 months saw 163,611 cuts, 31% more than the prior 12 months, across 139 companies, with the biggest single round being Oracle’s 30,000-job cut on March 31, 2026; it also says the most recent tracked round was Meta on May 19, 2026. Its live events feed for May 2026 alone shows multiple large tech layoffs that would ordinarily fall near this market segment: Meta 8,000, LinkedIn 606, Intuit 3,000, Cisco 4,000, Groupon 400, Cloudflare 1,100, PayPal 4,760, and Coinbase 700. My inference is that the current layoff wave is disproportionately concentrated in mature/public companies, which raises the expected count in this question’s Post-IPO/Acquired bucket. (gosivl.com)
A major adjustment is about date semantics. The question resolves on the tracker’s Date field, not when layoffs take effect. TechCrunch’s 2025 roundup includes Amazon cuts announced in December 2025 even though the affected jobs were scheduled to end in February 2026. That suggests announced-in-May or announced-in-June layoffs with July effective dates should not automatically be counted as July entries on layoffs.fyi. This is especially relevant for the LinkedIn California cuts scheduled for July 2026: they are evidence of ongoing pressure, but I do not want to assume they will resolve into a July-dated tracker row. (techcrunch.com)
Putting that together, I think the most likely range is 3 to 5 qualifying entries, with 4 as the single most likely exact value. My mean forecast is 4.5. I modeled this as a three-regime mixture: a pullback regime after May’s heavy wave (Poisson lambda 2.5, weight 0.30), a continuation regime consistent with the current elevated pace (lambda 4.5, weight 0.50), and a renewed earnings/AI-restructuring surge regime (lambda 7.5, weight 0.20). That produces a moderate right tail: enough room for another wave of public-company cuts, but still keeping most mass below 7 and only about a 3.1% chance of more than 10. The biggest reasons I am not going higher are (1) some obvious July-effective layoffs may already be dated earlier on the tracker, and (2) very large monthly layoff totals do not always translate into many distinct 400+ Post-IPO/Acquired rows. (techcrunch.com)