Building AI products beyond the demo. Thinking out loud about tech, business, investing and sports.
Athens | Berlin | Munich
Joined February 2010
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Managers: 90% of tasks exposed to AI in theory. 14% show up in real Claude usage.
Two indexes, two different questions. OpenAI's asks whether an LLM could make a task 2x faster. Anthropic's asks whether people actually use Claude for it at work. The gap between them is not capability. It is adoption, workflow and trust.
Even the most used group, Computer & math, sits at 38% of what is possible. Exposure is not replacement. A task an LLM can speed up is not a job it can own.
So the real question is not whether tech, finance and management disappear. It is what stays scarce once producing code, analysis and reports gets cheap.
1. Problem selection. Picking the 3 things worth doing out of 30.
2. Accountability. Someone signs, and owns the downside when it goes wrong.
3. Context. The data, history and workflows a model never sees.
Trust. Customers still buy from people they believe.
My bet: the jobs don't vanish, the ratio flips. Less time producing, more time judging. The people at risk are the ones whose value was the production step, not the judgment on top of it.
Cheaper code has so far meant more software, not fewer builders. I expect the same here.
🫣🫣
Generative UI for conversational agents.
Combining @aisdk with Chat SDK and 𝚓𝚜𝚘𝚗-𝚛𝚎𝚗𝚍𝚎𝚛, you can go straight from LLM to UI on platforms like Slack and Teams.
I believe this will become the dominant Human-Agent Interaction (HAI) paradigm:
vercel.com/changelog/json-re…
algorand:native ftw
Quantum technology could unlock new possibilities in drug discovery, materials design, and robotics. As commercial applications advance, businesses have an opportunity to build capabilities and gain a competitive edge.
Explore the three horizons: mck.co/4BBwNkW
There is so much charting created by Claude here that is hard to keep up. Knowledge and intelligence is already largely commoditized. Pity
The cheapest agent optimisation is not a better model. It's moving housekeeping off the expensive one.
Claude Code's background subagents now get their status lines from Haiku 5.5 working off short notes: about 99% cheaper per update, about 6% more prompts on the same limit.
Every call that summarises, labels or reports progress deserves the same audit.
teapawt.net/ClaudeDevs/status/2118…
Το 55% των εταιρικών δαπανών σε AI APIs πάει πλέον σε μία εταιρεία: την Anthropic.
Νέα έκθεση της Menlo Ventures (επενδυτής της Anthropic, κράτα το αυτό):
1. Εταιρικές δαπάνες σε AI: από $33 δισ. σε $176,8 δισ. σε έναν χρόνο.
2. Μερίδιο στα APIs: Anthropic από 40% σε 55%, OpenAI από 27% σε 31%, Google από 21% σε 9%.
3. Τα open-source μοντέλα κάνουν το 19% της χρήσης, αλλά μόνο το 4% της δαπάνης.
Τι σημαίνει για μια ελληνική ή ευρωπαϊκή εταιρεία: οι αγοραστές πληρώνουν για ικανότητα, όχι για φθηνά tokens. Αν όμως το προϊόν σου στηρίζεται σε έναν πάροχο με 55%, η διαπραγματευτική δύναμη δεν είναι δική σου.
Χτίσε έτσι ώστε να αλλάζεις μοντέλο σε μια εβδομάδα, όχι σε ένα τρίμηνο.
The SaaS at risk isn't the $600 tool. It's the expensive one whose core is a workflow and a table.
Cory rebuilt a $600/yr app with Opus in 4 to 5 hours. The math only improves as the price goes up.
Niche B2B survives on proprietary data and accountability, not features.
teapawt.net/czue/status/2117182098…
Για πρώτη φορά, το compute της Anthropic μεγαλώνει πιο γρήγορα από τα έσοδά της.
Αναθεωρημένο S-1 (2 Νοε), Q3:
1. Έσοδα $16,96 δισ., +47% σε σχέση με το Q2.
2. Κόστος compute $9,86 δισ., +77%.
3. Το compute ανέβηκε από 48% σε 58% των εσόδων. Το λειτουργικό αποτέλεσμα γύρισε από κέρδος $974 εκ. σε ζημία $567 εκ.
Τι σημαίνει για μια ελληνική ή ευρωπαϊκή εταιρεία που χτίζει πάνω σε AI: μην γράφεις στο business plan ότι η τιμή ανά token θα πέφτει για πάντα. Μέτρα κόστος ανά ολοκληρωμένη εργασία, κράτα τη δυνατότητα να αλλάξεις μοντέλο, και μην υπογράφεις ετήσια δέσμευση πριν δεις τα δικά σου νούμερα χρήσης.
Ο πάροχος θα περάσει το κόστος κάπου. Μέτρησέ το πρώτος.
Grokbot used to reset every Monday but it is Tuesday already and still 100% - you can’t convince me that there is not something way off
Loved GrokBot, as of yesterday the usage limits vanish in minutes. Man this is a blocker to major adoption. Prefer that they revise their plans. Come on $SPCX
Is it me or transferring seamlessly context from one AI to another would be a HUGE business. Anyone working on that?
The rise of AIpreneurship. Playing seriously with the idea letting GrokBots build a full business themselves with almost no oversight.
Technically, get a bot for each role and let them work together. Scary part is...imagining 5 years from now. 1 persons multiple bots for workers
Token costs doubling every 45 days is a ~275x bill in a year. No output curve keeps up with that.
Chamath says his CTO told him exactly this, while output gains barely move. That is the real AI budget problem: spend scales with every agent you switch on, output doesn't.
What I'd do on Monday:
1. Budget AI per task, not per seat.
2. Default to the cheapest model that passes your eval. Escalate only on failure.
3. Switch off any agent that can't show its cost per outcome.
Cheap tokens didn't make AI cheap. They made waste cheap.
teapawt.net/SiliconValleyPX/status…
Chamath says his company's AI token bill is doubling every 45 days while output gains barely move.
"I sat down with my CTO today, I said how are we doing on token spend. And he said the most incredible thing, he said right now, our token costs are doubling every 45 days. I said well what is the downstream productivity? And he said maybe 5% max."
"So my costs are doubling every 45 days, my upside is essentially flat. He said honestly, what we're finding out is that you need to use a lot more tokens to get to this next iteration of improvement because we've effectively already asymptoted."
"We're going to take a step back and try to figure out what to do. I don't know how many other companies will actually go through this reckoning now, but the point is everybody in the next three or four years will for sure go through it."
"I suspect that if you can get out now, you should get out now before all of that starts to seep into the water table. Because I think that's probably what allows you to get out at a huge price and raise a huge amount of money."
Interested in AI?
Follow @SiliconValleyPX and never fall behind.
I track ChatGPT, Claude, and how every new agent is changing how we work and think, then hand you the pure signals.
Ο Αντίνο έχει 6 assists φέτος και από τους κορυφαίους σε ανακτήσεις όντας ακραίος χάφ. Έτσι για τους doubters…#paofc
Αύριο ξεκινά το πιο υποτιμημένο AI νέο της χρονιάς στην Ελλάδα: η ηλεκτρονική τιμολόγηση.
Από 2/11 γίνεται υποχρεωτική για επιχειρήσεις με τζίρο έως 1 εκατ. ευρώ. Η ΑΑΔΕ λέει ότι 655.000 (σχεδόν 70%) είναι ήδη μέσα. Μεταβατικό ως 31/1/2027.
Γιατί έχει σημασία για μια ελληνική ή ευρωπαϊκή εταιρεία:
1. Τιμολόγιο σε δομημένα δεδομένα σημαίνει ότι ένας AI agent δεν χρειάζεται OCR. Συμφωνία τραπεζών και ταμειακές ροές γίνονται αυτοματισμός.
2. Από 1/1/2027 και τα ψηφιακά δελτία αποστολής περνούν σε φάση Β. Τιμολόγιο και διακίνηση, ίδιο σύστημα.
3. Η ΕΕ ακολουθεί: από 1/7/2030 το e-invoice γίνεται υποχρεωτικό στο ενδοκοινοτικό B2B.
Η συμμόρφωση είναι το κόστος. Τα δεδομένα είναι η ευκαιρία.
Anthropic says writing code is no longer its bottleneck. This week's most viral agent post says activity isn't progress. Both are true.
Facts:
1. Anthropic merged about 2,500 code changes a day in May 2026 and over 30,000 a day in September. 12x in four months.
2. Git broke first: about 25 million CI checkouts a day. Seven people moved the monorepo to an in-house system, Scion, in five months.
3. Thariq Shihipar on Oct 30, 1.2M+ views: with coding agents it can feel like a lot gets done while nothing really happens.
If you build with agents:
1. Count shipped outcomes, not merges.
2. Fund the pipeline first: review, CI, source control.
3. Treat reviewer attention as the scarce input.
