Alex Calder

CEO @coworkerapp previously @uber

[Alex Calder @ATCalder]

Today, we dropped the price of enterprise AI by 80%.

Same frontier AI. Same chat, cowork, and code experience.

Just 5x more tokens for the same spend.

Here’s how and why. 👇 Also, we made a video. Please enjoy.

[Paul Jump @paulljump]

there is a joke @JamesCox00 @ATCalder and @HeresTheChurch used to say when we worked on uber pool together that if you could get riders to gradually walk further and further to their match, you could eventually charge them for the full walk. I think about that a lot.

[Spencer Walsh @thespencerwalsh]

Distilling my variant views on $UBER:

1) AV providers will build to trough demand in each city. Building to peak would lead to low utilization & returns. Uber’s elastic supply of human drivers will meet surges in demand (morning/evening rush hour, Fri/Sat nights, rain, concerts, holidays, etc.). An AV fleet sized to peak New Year’s Eve demand would be wildly unproductive. Consequently, we will live in a hybrid human/AV rideshare world for a long time.

2) AV technology appears to be commoditizing. If 3+ operators survive in each metro, then Uber will still capture demand-gen economics.

3) AV rollout will occur over decades. ~20 million rides occur on Uber’s network every day. It will require a fleet of 2+ million AVs across 70 countries to fully replace Uber’s Mobility business. It took the US rental car industry 40+ years to scale to over 1 million vehicles, and $CAR / $HTZ didn’t have to worry about city-level permitting and safety validation.

4) AVs will grow the rideshare market. Rideshare represents 1-2% of miles driven globally. Lower rideshare prices due to AVs (no human driver, lower insurance costs) could cause consumers to question car ownership in many cities, boosting the overall rideshare industry.

5) Half of Uber’s business is delivery. Uber’s Delivery segment represents nearly half of Uber’s bookings, a third of operating profits, and is growing fast: bookings are growing 25% in constant currency and operating profits growing 38%.

Meanwhile, Uber’s Mobility segment, which investors think is being disrupted, continues to grow bookings 20% in constant currency and operating profit 28%. Lots of ways to win owning $UBER shares at 16x ’27 earnings.

[Alex Calder @ATCalder]

@nicbstme Nicolas we’ve build that continuously learning graph brain that has all the appropriate permissions etc. DM if you want to plug it in and make things even funnier.

[Alex Calder @ATCalder]

@gabriel1 This is correct - ungodly amounts of data passes through LLMs to generate enterprise and agent context graphs across our customers’ orgs (approaching 100%) - however a very large portion of it is done on small / open models since you can optimize the pipelines

[Tom Atkinson @T__W__A__]

OM2 by @coworkerapp just dropped

[Alex Calder @ATCalder]

@SaetaMicha38987 bench those marks! very cool

[Alex Calder @ATCalder]

@tbutz3k UUGE

[Jeff Huber 🇺🇸 @jhuber]

Congrats to @coworkerapp on OM2! The next step for enterprise AI that actually works isn't a bigger model, it's memory.

[Peter Zhou @xtzhou]

Don’t use AI that forgets after every session. Bring your context to any model. Love what @ATCalder and @HeresTheChurch have built!

[Alex Calder @ATCalder]

@coworkerapp Incredible achievement from the team @coworkerapp

[Alex Calder @ATCalder]

9x cheaper, 64% faster, preferred on quality 84.5% of the time. No change to your existing workflows.

[Coworker.ai @coworkerapp]

Today we're launching OM2.

Your AI re-reads your entire company from scratch every time you ask it something.

It’s why more than 50% of your token bill isn't in the answer, but in the search for it.

OM2 gives your AI a permanent memory of your company. 🧠

[Alex Wurts @AlexWurts]

If anyone is curious what a true software factory looks like. Check out what happened to our Principal engineer's velocity after he launched our first factory.

His project was building a pipeline for printing data connectors, not just building one connector at a time.

[Danyal @DanAkarca]

It was great being on Bloomberg @business this morning to discuss all things @CallosumAI

[Alex Calder @ATCalder]

Coworker lets you chat, cowork and code with your organisational context across any model, open or closed. What a time to be alive.

[Sriram Krishnan @sriramk]

It is clear open source models and harnesses are having a moment. There's a few factors at work

1/ It is now obvious that you can catch up to near-SOTA performance and do so with a clear training lineage. See:@thinkymachines Inkling launch today.

2/ There are several well-funded, talented teams building open weight models now in the US and abroad. Along with the explosing of other near SOTA models (Grok/Cursor, Muse Spark), it is clear we are going to have a diverse ecosystem of models atleast on coding and agentic use.

3/ Organizations are increasingly looking for control over how their data is used and are willing to trade off some access to frontier level tokens for this control. Organizations and countries are increasingly nervous about the frontier labs potentially competing with them down the road and don't want their data to enable a future competitor.

4/ Open source is a slider: you could bring your own open harness, your evals, your business context and are free to pick and choose your model of choice.

5/ Companies have now actively shifted from "how do we get our people to use tokens" to being uncomfortable with their token cost ballooning without a clear line to revenue.

6/ Geo-politically, countries will be weighing open weight models as a way to get frontier-level tokens inside controlled environments that may not be otherwise possible.

All of this leads to more choice for all of us !

[Sriram Krishnan @sriramk]

It is clear open source models and harnesses are having a moment. There's a few factors at work

1/ It is now obvious that you can catch up to near-SOTA performance and do so with a clear training lineage. See:@thinkymachines Inkling launch today.

2/ There are several well-funded, talented teams building open weight models now in the US and abroad. Along with the explosing of other near SOTA models (Grok/Cursor, Muse Spark), it is clear we are going to have a diverse ecosystem of models atleast on coding and agentic use.

3/ Organizations are increasingly looking for control over how their data is used and are willing to trade off some access to frontier level tokens for this control. Organizations and countries are increasingly nervous about the frontier labs potentially competing with them down the road and don't want their data to enable a future competitor.

4/ Open source is a slider: you could bring your own open harness, your evals, your business context and are free to pick and choose your model of choice.

5/ Companies have now actively shifted from "how do we get our people to use tokens" to being uncomfortable with their token cost ballooning without a clear line to revenue.

6/ Geo-politically, countries will be weighing open weight models as a way to get frontier-level tokens inside controlled environments that may not be otherwise possible.

All of this leads to more choice for all of us !

[Alex Calder @ATCalder]

Given this is a 2.8T model, my guess is capabilities land somewhere around Fable (and well ahead of Opus 4.8). That is insane for an open model.

[Lisan al Gaib @scaling01]

IT'S HAPPENING

any second now

[Deirdre Bosa @dee_bosa]

Benchmark’s @peterfenton says 90%+ of tokens could come from open weight models in the next 18-24 months, pressuring frontier model margins.

Full convo at 12p PT/3p ET on the livestream, plus @AravSrinivas on Perplexity’s new orchestrator model and @jmorgan on why enterprises are moving toward AI models they can download and control

[Alex Calder @ATCalder]

@sriramk check out https://t.co/0S5p7Ukfew

[roman @Nozelcode]

I tried Coworker’s Open Artifacts today, and I was genuinely impressed. I asked it to build a dashboard, and it automatically selected the most suitable model for the task without needing any extra instructions.

It’s one of the few AI tools I’ve used recently that feels intuitive right from the start instead of making me wrestle with the interface.

For once, I felt like an absolute god.

[Alex Calder @ATCalder]

@paulljump Cost of living in the big city Paul

[Alex Calder @ATCalder]

Tea is being thrown into the harbor

[brenz. @brenzhills]

🚨 YOU'RE OVERPAYING FOR AI BY 5X. AND ALMOST NOBODY HAS NOTICED.

every task you run goes to the most expensive model, even when an open model one nails it for a fraction of the price (yes, the one china dropped during the Fable 5 ban benchmarks near Opus 4.8).

You can fix it and save thousands with this new tool:

→ it routes each task to the right model, open or closed, automatically
→ same frontier quality, ~5x less in tokens
→ ask for a deck, dashboard, doc or app, get better results with less.

I ran it on real client work and they couldn't tell the difference. except in the bill lol.

stop paying frontier prices for intern tasks.