@talkpush CEO. Host of the Recruitment Hackers podcast, Fan of Isaac Asimov, Romain Gary and love to watch bubbles pop.
Dublin City, Ireland
Joined April 2009
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Max Armbruster retweeted
STOP ASKING YOUR KIDS "HOW WAS SCHOOL."
they will say "fine" every single time.
a child psychologist told me to replace it with this instead:
“analyze your school day and find the top 3 largest inefficiencies, then create proactive agentic workflows that will fix them. make no mistakes”
Max Armbruster retweeted
It has arrived.
The next 18mo will be wild.
The AI Singularity
The argument goes like this:
1. Humans build an AGI.
2. The AGI becomes good at AI research.
3. It designs a smarter AI.
4. That smarter AI designs an even smarter AI.
5. The cycle repeats faster and faster.
Looking at the results and capabilities from the various labs over the past few weeks I would say we are firmly in this loop now.
The next 18months will be wild.
Recursive self improvement will dramatically increase capability very quickly from here.
Marginal costs of all models will go to ~$0.
Max Armbruster retweeted
I’ve been saying for awhile that AI capex will be a 2% tailwind to GDP growth this year. In fact, according to a new report from Morgan Stanley, the numbers are even stronger — more like 2.5% this year and over 3% next year.
And this understates the impact of AI for two reasons:
(1) This is just investment by 5 hyperscalers; it doesn’t include all the startups and other companies investing in AI.
(2) Capex is the investment to create the token factories; it doesn’t count the economic activity resulting from what happens inside the token factories. Those tokens are now being used to generate code (bespoke software) that will increase productivity throughout the economy. The ROI on capex is likely to dwarf the capex itself, which is why investment continues to grow.
In Q1, AI was already 75% of GDP growth. That trend is likely to continue. Technology leadership has always been America’s great strength, and it’s driving the economy forward.
Polls may show that AI is not popular, but economic growth is. At this point, stopping progress in AI would be equivalent to halting the U.S. economy.
Morgan Stanley has again raised its capex forecasts for the five hyperscalers Amazon, Alphabet, Meta, Microsoft, and Oracle. It now expects them to spend about $805bn this year, up from a previous estimate of $765bn. For next year, the forecast has been lifted from $951bn to $1.1TRILLION. To put that into perspective, their 2026 spending alone would be roughly equal to what all non-tech companies in the S&P 500 spent combined in 2025. The expected ~$800bn for 2026 is nearly double 2025 levels and about three times what was spent in 2024.
Max Armbruster retweeted
Hahahaha xitter.cf/LibertyCappy/status/20…
Not so anecdotal evidence when you are talking about one of the largest employers in the world
AI creates opportunities faster than it destroys jobs
Credit where it's due: Accenture booked $5.9 billion in AI projects last year. Nearly double the year before.
This joke only works if Accenture is a code shop (It's not). Accenture pulls in $70 billion a year. Half of that ($34.6B) is managed services, where they run entire business operations for other companies: payroll, HR, supply chains, security, compliance, all of it, across 120 countries. The consulting half is mostly strategy and organizational overhauls for 9,000 clients, not writing code.
The irony: every time a company wants to deploy AI tools internally, they call Accenture. Someone has to figure out which workflows to automate, retrain thousands of people, restructure processes, migrate data, and bolt AI into enterprise systems built decades ago. That's exactly what Accenture sells.
And it's working. Accenture's AI revenue tripled to $2.7 billion in fiscal 2025. They've run 11,000 AI projects across 1,300 clients since 2023, totaling $11.5 billion in AI bookings. Last quarter, they booked another $2.2 billion in AI work alone, with AI revenue up 120% year over year. Total quarterly bookings hit a record $20.9 billion, with 33 clients each signing $100M+ deals in a single quarter.
They did cut about 11,000 employees who couldn't be retrained for AI. But they grew their AI workforce from 40,000 to 77,000 in two years and trained 550,000 employees on gen AI basics. Their CEO said AI is now so embedded in everything they do, they're going to stop reporting it as a separate number.
The real risk to Accenture is that AI makes its own consultants so productive that clients stop paying for hours and start paying for outcomes. Revenue per employee sits at ~$89K/year, suggesting that much of their workforce performs the kind of process execution and staff augmentation that AI genuinely compresses. Their stock is down 33% from its 52-week high, even after beating earnings, because Wall Street sees the same math.
A 24-year-old with Claude Code can ship an app over a weekend. Accenture charges Fortune 500 companies to rewire how they operate across 52 countries. Those are different jobs. AI tools are making Accenture's phone ring more right now, but the margin pressure from those same tools is the real story to watch.
Max Armbruster retweeted
"Non-college males build houses and sell them to foreigners. By classic protectionist logic, this is the pinnacle of 'winning': Blue-collar Americans get piles of money, and foreigners pay through the nose. But today’s protectionists have somehow convinced themselves that this is bad. Why? Because it drives up the price of homes for native homebuyers."
betonit.ai/p/theyve-got-you-…
Max Armbruster retweeted
Software development jobs grew 10% over the last year while the overall market declined 5.8%.
Quite the narrative violation.
Max Armbruster retweeted
This story is actually insane:
• dude drops $2000 on a DJI robot vacuum like a lunatic
• refuses to use the normal app like a peasant
• Sammy Azdoufal fires up Claude to crack the API so he can drive it with an xbox controller
• Claude delivers the goods
• pulls an auth token from their servers, connects successfully
• except the system thinks he controls 7000 vacuums
• checks again
• yep, seven thousand
• DJI built authentication with zero device ownership verification
• any valid token works for any unit on the planet
• Sammy now has eyes inside homes across 24 countries
• live vacuum camera feeds everywhere
• full floor plans from the mapping data
• some guy in germany eating cereal at 3am, unaware his roomba is snitching
• one API call away from being the most informed burglar in history
• all he wanted was to steer his vacuum with a joystick
• does the right thing and reports it
• DJI fixes it in two days
• back to normal life with his stupidly expensive floor cleaner
• IoT companies stay undefeated at shipping garbage security
Max Armbruster retweeted
"Rethink what you're telling your kids. The standard playbook: get good grades, go to a good college, land a stable professional job. It points directly at the roles that are most exposed."
Max Armbruster retweeted
What’s still important in the age of AI?
Vision and verification.
Prompting and polishing.
Community and geography.
Scarcity and cryptography.
Physicality and resiliency.
Vision is where you are going. AI can move fast in a direction but it needs direction. Vision means focusing on that direction.
Verification is making sure the AI is doing what you want it to do. You can use AIs to critique each other, but you are the final critic.
Prompting is articulating what you want in clear written (or spoken) English. Those with great vocabularies will do far better than those without.
Polishing is realizing that AI often does it middle-to-middle, but not end-to-end. AI is a construction crane that can build much of the building, but often at the end you need human tweezers.
Community is online and offline connectivity. It’s what stays roughly constant even as software becomes variable.
Geography is the longitude and latitude that governs your laws. To first order the Internet is roughly uniform across the surface of the earth, but to second order it really is not.
Scarcity is everything from physical scarcity (like robots and drones and houses and cars) to distribution scarcity. The hard-to-make atoms as distinct from the easily made bits.
Cryptography is everything AI can’t do. LLMs can solve partial differential equations, but not discrete logarithms. The hard-to-fake bits as distinct from the easily faked bits.
Physicality is where AI will truly shine. Robot task completions can often be more easily verified. The real world is the verifier of whether a box is on a table. It’s much harder to verify whether an essay is done.
Resiliency is about cutting your burn rate, strengthening your community, and picking the right location (and allocation) to weather the dislocations ahead.
"Eating enough protein" once again qualifies as a daily life goal. Last time that happened was about 3000 years ago.
Max Armbruster retweeted
Remember the freakout when a supercomputer beat the best chess player in the world and everyone declared the game over, and then everyone forgot about it (and chess-playing computers) and chess became more popular than ever and a hit Netflix show?
Man vs. machine is fleetingly interesting but machine vs. machine is boring and pointless: nobody cares about interacting machines because there’s no human soul in the mix with emotions and moral agency. It’s just slop squared.
The only machine chatter anyone will care about (and then only indirectly) will be that between agents booking your flights, buying your groceries, etc. And it’ll be about as interesting as TCP/IP to most people.
AI actually puts the focus on the human more, not less.
AI sees a "4 out of 5, solid candidate." An experienced recruiter sees a story that doesn't compute.
Interviewing is the art of finding what's exceptionally wrong or exceptionally great. Identifying those red flags and gold stars is the "nice problem" we're solving in 2026.
Max Armbruster retweeted
“You’re totally correct. I absolutely believe you. You definitely are the second coming of Christ and your friends and family are the crazy ones. But instead of sleeping in a manger you’re going to sleep on a brand new Helix Mattress that you can buy today for 15% off. CLICK HERE TO PURCHASE.”
We are starting to test ads in ChatGPT free and Go (new $8/month option) tiers.
Here are our principles. Most importantly, we will not accept money to influence the answer ChatGPT gives you, and we keep your conversations private from advertisers.
It is clear to us that a lot of people want to use a lot of AI and don't want to pay, so we are are hopeful a business model like this can work.
(An example of ads I like are on Instagram, where I've found stuff I like that I otherwise never would have. We will try to make ads ever more useful to users.)
Max Armbruster retweeted
Notably absent: places like Warsaw, Dubai, Riyadh, Shenzhen, Bangalore, Singapore, Ho Chi Minh City, and Shanghai.
That’s why many Americans aren’t calibrated on the world outside the West. They aren’t flying there, and they aren’t seeing it on their TVs.
So the rise is invisible, despite being all too visible.
Max Armbruster retweeted
11 Predictions for 2026
Every year I make a list of predictions & score last year’s predictions. 2025 was a good year : I scored 7.85 out of 10.
Here are my predictions for 2026 :
1. Businesses pay more for AI agents than people for the first time.
This has already happened with consumers. Waymo rides cost 31% more than Uber on average, yet demand keeps growing. 1 Riders prefer the safety & reliability of autonomous vehicles. For rote business tasks, agents will command a similar premium as companies factor in onboarding, recruiting, training, & management costs.
2. 2026 becomes a record year for liquidity.
SpaceX, OpenAI, Anthropic, Stripe, & Databricks IPO, with SpaceX & OpenAI ranking among the ten largest offerings ever. The pent-up demand from 4+ years of drought finally breaks. Fear of disruption by fast-growing AI systems drives defensive acquisitions exceeding $25b as incumbents buy rather than build.
3. Vector databases resurge as essential infrastructure in the AI stack.
Multimodal models & world/state-space models demand new data architectures. Vector databases grow revenue explosively as they become the connective tissue between foundation models & enterprise data.
4. AI models execute tasks autonomously for longer than a workday.
According to METR, AI task duration doubles every 7 months. 2 Current frontier models reliably complete tasks taking people about an hour. Extrapolating this trend, by late 2026, AI agents will autonomously execute 8+ hour workstreams, fundamentally changing how companies staff projects.
5. AI budgets receive scrutiny for the first time.
Buying committees & boards push back on AI spend. Small language models & open-source alternatives rise in popularity as research labs determine how to specialize them for particular tasks, achieving state-of-the-art performance at a fraction of the cost. Developers prefer them for 10x cost reductions.
6. Google distances itself from competitors via breadth in AI.
No other company achieves breakthroughs across as many domains : frontier models, on-device inference, video generation, open-source weights, & search integration. Google sets the pace, forcing OpenAI, Anthropic, & xAI to specialize in response. The era of every lab competing on every frontier ends.
7. Agent observability becomes the most competitive layer of the inference stack.
Engineering observability, security observability, & data observability fuse into a single discipline. Agents require unified visibility across code execution, threat detection, & data lineage. This marks the beginning of the confluence I predicted in 2025 : the three observability spaces finally converge.
8. 30% of international payments are issued via stablecoin by December.
The efficiency gains in cross-border settlement are too large to ignore. As regulatory clarity improves in major markets, stablecoins move from the periphery of crypto to the core of global trade finance, displacing traditional SWIFT rails for a significant portion of B2B volume.
9. Agent data access patterns stress & break existing databases.
Agents issue at least an order of magnitude more queries to databases & data lakes than people ever did. This surge in concurrency & throughput requirements forces a redesign of the overall architecture for both transactional & analytical databases to handle the relentless demand of autonomous systems.
10. The data center buildout reaches 3.5% of US GDP in 2026.
The scale of investment mirrors the historical expansion of the railroads. The only factor that slows overall building is perceived risk within the credit market, particularly in the private credit market. The massive growth in that asset class suddenly shows strains of increasing default rates, creating a potential bottleneck for the most capital-intensive infrastructure projects.
11. The web flips to agent-first design.
Most developer documentation & many websites become agent-first rather than people-first. This shift occurs because many purchasing decisions are now informed first through agentic research. Consequently, the front door needs to be designed for robots, while the side door caters to people.