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Recruiting Timeline:
Banking:
Where We’re At:
SA 2027: LionTree and Perella Weinberg opened their applications this week. 8 banks are actively recruiting for SA 2027
FT 2026: No new updates here. 67 firms are actively recruiting for FT 2026. This process is pretty dead at this point
If you need some interview support or just need a place to vent, check out our Coaching Program: Coaching for banking, consulting, and buyside recruiting | The Pulse. 95%+ of those coached for the summer 2026 recruiting season received offers!
New SA 2027 Applications:
LionTree Advisors: Strong M&A boutique (SA 2027)
PWP: Elite boutique (SA 2027)
New FT 2026 Applications:
None
See below to gain access to our premium database, updated weekly, which houses the application processes for over 300+ banks/consulting/buyside firms! Gain an edge over everyone else by not having to spend countless hours tracking applications and deadlines.
Consulting:
Where We’re At:
Another quiet week. Smaller firms will continue to release applications into early 2026.
SA 2026 released apps:
None
SA 2027 released apps:
None
FT 2026 released apps:
Guidehouse - Consultant (FT 2026)
Buyside:
Where We’re At:
SA 2027: No updates here. There are currently 11 buyside firms actively recruiting for SA 2027
New SA 2027 released apps:
None
Premium Database:
The database is updated weekly and contains 300+ Investment Banking and Consulting internships/full-time positions along with:
Interview tips for specific companies
Interview prep material
Applications and deadlines linked so that you can apply with one click
Insider information about the application process
Professionals to network with
Buyside deadlines, interview prep, and people to network with for the sweatiest of students
We send the updated dataset every week with the latest banking and consulting job postings. We released our 129th update today.
Students we have been helping have already landed roles at Blackstone, Goldman, J.P. Morgan, Jefferies, Citi, and Solomon.
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Market Update:
AI Capex
If you look at the most recent third-quarter earnings from the largest tech companies, the biggest takeaway is that everyone is in a full-blown spending frenzy on AI.
These companies are throwing down massive amounts of cash to build out data centers, buy GPUs, and scale the infrastructure that powers large models.
In Google’s Q3 update, the company raised its 2025 capex guidance to about 91 to 93 billion dollars, which is way above what it was expecting earlier in the year. Meta did something similar, lifting its full-year capex outlook to 70 to 72 billion dollars, even after already spending more than 19 billion in Q3 alone.
Microsoft also showed huge numbers, reporting over 21 billion dollars in capex for its fiscal Q3, and its leadership was pretty straightforward that AI demand is forcing them to expand data-center capacity nonstop.
Hyperscaler Capex (Source: OpenAI)
Even OpenAI, which is not public, is part of the story. Analysts estimate that its long-term compute needs could run into the hundreds of billions, which puts even more pressure on partners like Microsoft to build out infrastructure as fast as possible.
The other interesting part that is unique to OpenAI is that they have very little revenue, given their Capex and valuation. The OpenAI bet is simply that they will be the biggest player down the line and will have massive amounts of revenue, so investors are willing to look past their current revenue (or lack thereof) figures.
Because all these companies are scaling so aggressively at the same time, you can see the impact across their financial statements. Depreciation and server/network equipment purchases are jumping, and nearly every executive on these earnings calls keeps saying some version of, “AI demand is higher than we expected, so we have to invest more.” It has turned into an arms race, and no one wants to be the company that underspent and fell behind.
Investors get the logic, but the reactions have been all over the place. When Google posted strong results while raising capex, investors barely flinched. But when Meta raised its spending, its stock dipped because people were worried about the hit to short-term profit margins.
Source: Bloomberg
Microsoft fell somewhere in the middle, with investors supporting the AI strategy but still somewhat concerned with how quickly these costs are stacking up. Basically, if a company can show that AI revenue is growing fast enough to justify the burn, investors are more comfortable.
Source: Reuters
AI is such a promising technology that companies know the demand is coming, and they’re betting that whoever builds the most capacity now will control the market later. That’s why capex numbers across Alphabet, Meta, and Microsoft are exploding at the same time and why OpenAI’s massive compute appetite keeps driving the cycle.
Bottom line: AI is fueling one of the biggest infrastructure buildouts tech has ever seen. Everyone is spending big, everyone is trying to out-invest everyone else, and investors are hoping the payoff comes fast enough.
Disclosure: Nothing written here is financial advice or should be used for investment decisions.
Learning Point of the Week:
BBs vs. EBs. MBB vs. Big 4. Mega Fund vs. MM.
What are the differences?
Heavily requested topic to breakdown everything you need to know about the different types of firms (oldie, but goodie). This week, we will discuss the core components of different firm classifications across banking, consulting, and the buyside.
Starting with banking.
BB=Bulge Bracket. EB=Elite Boutique.
Characteristics of a BB:
Examples: JPM, Citi, GS, BofA, Wells Fargo, etc
Actively uses its balance sheet to lend money
Work on the largest deals
Many different departments and roles outside of just investment banking
They pay well, but not great. Starting salary ~$100-$115k. Bonus ~40-80%.
More people = better WLB (marginally better by ~10-15 hours/week)
Interview processes are less technical, but interviews are harder to get than EBs
Great exit opportunities to PE/VC/Credit. Also, good exit opps outside of finance given the brand name
Some BBs like JPM, have a stickier culture where fewer analysts leave the firm in search of “greener” pastures
Characteristics of an EB:
Examples: Evercore, Moelis, PJT, Perella Weinberg, etc
Mostly specialize in pure-play investment banking. Strictly advisory services
Heavily index on product roles like M&A or Restructuring (Restructuring is significantly better at EBs than BBs)
Smaller deals, leaner deal teams. Arguably better exposure
Better pay than BBs. Starting salary $110-$130k. Bonus ~50-100%.
Less people = shittier WLB. These guys work around the clock, 7 days a week ngl
Interview processes are more technical and interviews can be easier to get if you went to a target school
Better exit opportunities within finance, especially to PE. Less opportunities outside of finance
Typically a 2-year culture at the analyst level. Most people leave
Now, onto consulting.
MBB = McKinsey, BCG, and Bain. Big 4 = Deloitte, EY, PWC, and KPMG
Characteristics of MBB:
Examples: Bain, BCG, and McKinsey
The most sought-after firms to work for within management consulting
Pure strategy consulting firms that serve top-tier, large clients
Leaner teams with a more collegial environment
Higher starting salary ~$100-$140k (inclusive of bonus). McKinsey is a strong outlier with higher pay even amongst the MBB
Shittier WLB (still far better than banking)
Interviews are much more technical / case-heavy
Exit opportunities are better
Characteristics of Big 4:
Examples: PWC, EY, Deloitte, and KPMG
Strong management consulting programs, but there are many other departments and roles outside of consulting
Also work alongside large clients within the Fortune 500
Larger teams, arguably worse exposure
Starting salary ~$75-$100k (inclusive of bonus). KPMG is an outlier and pays like shit
Better WLB because there are more people (can be a 40-50 hour/week job)
Interviews are less technical and less competitive
Exit opportunities are worse than MBB
Now, onto the buyside.
For the sake of simplicity, we are only discussing PE.
Mega Fund = AUM of $100bn+ and typically work on deals of $1bn+.
MM = Middle-Market. Broad term to describe firms with less than $100bn AUM. Fund size usually $10-$50bn. Deal size $50-$500mm.
Mega-Fund:
Examples: KKR, Blackstone, Apollo, Warburg Pincus, etc
Work on the largest transactions with much larger teams
Huge fund size = big transactions
Typically many other roles available outside of PE (credit, infrastructure, insurance)
Worse exposure and very difficult to work your way up the ladder given concentration of upper-middle management (some are strictly 2-year associate programs)
Better pay. Likely similar to EB pay for junior analysts. Admittedly, I only have numbers for the associate level. Apollo is known to be an outlier paying far above market
Known to be banking 2.0. Shitty WLB
Interviews can be super sweaty and always have a modeling exercise
Exit opportunities can be more concentrated than banking because of specialization and worse brand name compared to BB
Middle Market:
Examples: Alpine Investors, Trinity Hunt Partners, Spectrum Equity, Orion, etc
Smaller transactions, smaller teams, and a smaller fund size
Usually better exposure and more responsibility at the junior level
Typically a focus on a particular asset class (infrastructure, tech, healthcare, etc)
Typically a focus on a particular type of investing (PE-only, credit-only, distressed debt only)
More mobility regarding promotion
Typically worse pay then mega-funds. However, some middle-market funds will pay far above market
Better WLB (case-dependent)
Interviews are either super sweaty with complex modeling or sometimes much easier than banking with a heavy behavioral focus
Exit opportunities highly constrained to other roles within finance given lack of brand name. Working at a portco is common
Going Forward:
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