Interview with an industry expert on how AI is changing the way software gets built ($MSFT, $ANT, $GOOGL):
- The expert says Copilot use has grown sharply this year because people now trust AI far more than they did in 2024, when the expert would have written code by hand rather than spent hours checking a model’s output. Models have matured so much that the expert now hands them a proper spec and only validates a few things, pointing to $ANT's Opus and Fable models as well ahead on software intelligence.
- According to the expert, employees are now fully using AI to build and keep asking for more credits, because with nobody interested in writing code by hand, running out of budget leaves them idle. Each person gets a monthly budget for Copilot and Claude, while Gemini works on a flat fee with automatic throttling. Unused credits flow to others, and extra use goes through leadership approval. The expert expects this spend to double within a year and possibly reach four times today's level in about three years, if it starts producing revenue.
- According to the expert, the return from AI shows up directly in how fast features reach customers. When a client needs a new product capability, the work normally passes through a number of units, which takes many months. With tools like Claude and Copilot, the same team can hand over the architecture and requirements and have features built, tested, documented, and submitted for review in days, cutting delivery time sharply.
- The expert emphasizes that $GOOGL has tried to challenge GitHub, building its own coding environment around Gemini, but is nowhere close to displacing it. GitHub has been the source of truth for code for many years, and the volume of code and solved problems committed there is unmatched, which the expert compares to the gap between Chrome and Bing, where people go to the leader for a reason. The expert also highlights that Copilot works as an interface connecting many models, including those from $ANT, $GOOGL, and open-source providers, so developers are not tied to a single one.
- The expert sees Claude Code and Claude Cowork as well ahead of any other agentic system for software engineering, mainly on accuracy and on integration at speed and scale, and his main advice to the Copilot team is to copy that approach. He believes GitHub is better placed than anyone to close the gap, since codebases across the globe already sit there, so a Claude-like agentic experience in the Copilot desktop app, even at a higher price per license, would be easier to adopt than bringing in Claude, which still has to connect to GitHub. GitHub could also offer the same capability across models beyond $ANT's.
With the help of @AlphaSenseInc's SuperAnalyst we curated recent expert call content on AI infrastructure.
See our SuperAnalyst dashboard ⬇️
https://t.co/5vwoD6xtVJ
The common thread is that hyperscalers still borrow cheaply and are shifting more of their builds into JVs and leases, while lenders are pulling back from neoclouds.
$NVDA $CRWV $META
Good color from lots of ad agencies on what's happening with $GOOG search.
Why CPCs rising? Likely tied to AI overviews.
Bear case - reduced invy makes remaining invy more expensive
Bull case - AI overviews not yet monetized
(btw -- query growth highest in last 5 years -- is that including AI expansions of queries?)
$ANT has a few key debates going into its IPO: whether Claude can keep its price premium, whether margins hold up against the compute commitments, and whether the Q3 slowdown was a blip. @AlphaSenseInc Expert Insights and Channel Checks address questions around pricing and how deeply Claude is getting into enterprise customers.
Check out our primer, built by SuperAnalyst: https://t.co/YqeGAWp7lJ
And the Channel Check Breakdown Here: https://t.co/wGYTAAcAUX
solana:56DeqXiADWY2Y3iD8pdbpTi9jhXXneofTY5dp4Xjpump $GOOG $META
The $ANT S-1 is public. SuperAnalyst built the primer, and it's now live on our site.
This primer not only draws on the S-1, but our Tegus expert interviews, news coverage, and our proprietary Canalyst model for #Anthropic.
Inside, you will find the full company snapshot, compute commitments, the competitive benchmark from enterprise buyers, registered risks and the bull and bear cases side-by-side.
Explore the dashboard: https://t.co/PZEo2m5e9N
Updated Token Consumption Tracker
For Anthropic S-1 day, breaking out the surge in Ant tokens based on usage on AlphaSense
Update your models accordingly
$AMD channel checks, Q3 2026: demand is strong
Digging into @AlphaSenseInc channel checks on $AMD, drawing on roughly two dozen expert calls with distributors, server OEMs, integrators, and AI cloud providers. The signal is another beat for AMD, but the story is demand-positive and supply-constrained, not pricing-led. Key debates around component availability and the Helios ramp remain top of mind going into the quarter.
Full Breakdown ⬇️
https://t.co/L1UB8H6Bjy
$NVDA $MU
My Investment Memo builder in SuperAnalyst is now 🔥 – beats out what I was doing as a HF analyst. I’m looking for people that want to collaborate to draw smaller and smaller circles.
It uses a Canalyst model on my behalf. It reasons to assumptions (depending on type of company, builds out TAM and penetration, models cyclicality, etc), researches what experts are saying about key debates, builds to a valuation framework taking into account Comps / multiple history, etc. Full companion model / backup in excel.
Roll this forward a bit and it’s obvious HFs will be built trading on the back of something like this (much higher volume of getting to decisions faster, neutrally). I’d especially love to collaborate with some of you building AI HFs.
DM if interested – must have AlphaSense account (the skill calls our tools)
We’ve officially launched Channel Check Intelligence
The best new source of Idea Gen
AlphaSense began structured channel checks a bit over a year ago, already scaled to 3k per month (compliance reviewed, no embargo). Already much more than anyone could read but high signal if you can make sense of it.
Channel Check Intelligence makes sense of it —> what sectors, companies are inflecting, pricing / invy better or worse etc. Not only the numbers, but the why.
CCI is another form of pre-compute where we use continually use LLMs to structure the data once, for everyone. Soon, when you build your Earnings Previews with SuperAnalyst, the system will know to bring in CCI - and even use as an input to the assumptions in your model - without needing to rebuild the analysis from scratch (accuracy, time, tokens)
We are investing aggressively in scaling and development -- it's going to get pretty crazy in a year.
@AlphaSenseInc channel checks on $NOW show a healthy demand backdrop: renewals are strong, expansion is robust, and AI driving pipeline. But experts see a push on pricing and packaging (new Foundation, Advanced, and Prime tiers, plus consumption models) just as budget scrutiny and data readiness are in focus.
Full Breakdown ⬇️
https://t.co/6TRgyEof70
$MSFT $TEAM $CRM