TezLab retweeted
I cannot believe what will happen on 10/10.
The world’s largest Tesla enthusiast event.
@theXtakeover
TezLab retweeted
And some stats.
Unfortunately only discovered @TezLabApp half way through ownership… so around 50% of driving stats here!
TezLab retweeted
You can’t make this up. 😂
Tesla now has 420 Model Y Robotaxis and 69 Cybercabs registered in Texas.
The prophecy has been fulfilled.
TezLab retweeted
If you'd like to jump straight into the early integration demo of Grok Bot from the Tesla onboard Grok voice before reading the article, here's the short video.
It's only the tip of the proverbial iceberg.
I am doing so much more now after a few weeks of testing and the early enhancements with everyone that was testing and providing feedback.
i.e. While on this @DinerDash2026 road trip, I can tell Grok to order me food or drinks at say, Starbucks, ahead of time and it will even make the paymnt for me and I get the points in my Starbucks account.
Coffee is ready when I arrive.
And this is just a mundane use case. For actual work stuff, you can delegate work to any of your bots, gets status, reports, etc.
TezLab retweeted

Sawyer Merritt@SawyerMerrittAug 30
United States!
United StatesConnected via United States App StoreLocation may be affected by a proxy or VPN.Account-level information, not a live location or per-post device.
Next week will mark the first time that a purpose built Robotaxi (Cybercab) with no steering wheel or pedals that can be mass produced will offer rides to members of the general public in North America, and 99% of the population has zero clue this is about to happen.
TezLab retweeted
A new paper "Stealing Reasoning Traces from Proprietary LLM APIs" will make you look at hidden reasoning differently
Hidden reasoning is something the model does somewhere inside the black box. But with AI agents, parts of that reasoning can actually travel between calls and models as encrypted state.
And researchers behind "Stealing Reasoning Traces from Proprietary LLM APIs" found they could recover some of it without breaking the encryption.
Then they went further and looked at public agent logs. They found passwords, API keys, access tokens and personal information hiding inside these reasoning blocks - sometimes even when the visible conversation looked completely clean.
And there’s another thing I find especially interesting - these blocks can carry instructions too.
→ So hidden reasoning isn’t necessarily just a log of what happened. In an agentic system, it can influence what the system does next.
This means hidden reasoning is also becoming part of the infrastructure of AI agents.
TezLab retweeted
Hey Tesla Family… I know you all use different apps other than just the official Tesla app. I use @TezLabApp to keep track of my FSD miles plus road trips as well. It’s great to have groups in it too.
Whoever uses TezLab and would like to join this group I created, come join, let’s see how big we can make it.
tezlab.group/tesla-fam
TezLab retweeted
The metric I keep coming back to for SpaceX is $/Mbps to orbit
Starlink exists because Falcon 9 dropped bandwidth deployment costs ~10x to ~$6.55/Mbps. That’s about to drop again to just $0.30/Mbps because of Starship.
A business that is doubling users annually with a 63% adjusted EBITDA margin is about to cut their biggest cost by 95%… It really seems like people don't understand the implications of this.
The math assumes a reusable Falcon 9 launch is 17 tonnes at $1,000/kg and 2,600 Gbps per launch. Starship is targeting 100 tonnes at under $185/kg and 61,000 Gbps per launch. That's $17M for 2,600 Gbps ($6.55/Mbps) verse $18.5M for 61,000 Gbps ($0.30/Mbps).
Starship's additional volume allows for larger satellites, enabling simultaneous gains on multiple cost curves. The math suggests V3 satellites are ~600 Mbps/kg vs ~150 Mbps/kg from V2 mini.
Combining the 4x improvement on satellite bandwidth density with a 5x improvement in launch gets you the 20x improvement to 30 cents per Mbps to orbit.
These are fairly conservative assumptions because launch probably comes in even lower as Starship ramps, and satellite improvements probably keep coming. At $0.10 / Mbps, $1 billion spend on launch represents 10,000 Tbps or about 15x the bandwidth of Starlink's constellation today.
$1B is 90 days of operating income for Starlink... at it's current scale...
Yeah, I really don't think people are getting this. Starlink is the internet now.
TezLab retweeted

Beff (e/acc)@beffjezosJun 8
United States
United StatesConnected via United States Android AppAccount-level information, not a live location or per-post device.
Day three of amplifying this.
If this interview doesn't happen I am legitimately going to crash out.
Set is ready @ElonMusk
We built it 25min from downtown Austin and can shoot anytime in the next 7 days on 1h notice.
Humanity is on the verge of becoming a multi-planet species and spacefaring civilization.
My goal with this interview is to help people viscerally feel what that future is going to look like and get everyone excited to help build it.
TezLab retweeted
Tesla Users… who use @TezLabApp? I do. Would love to create a 𝕏 Tesla Fam group of all of you in it. Who would be interested?
Here’s the group link… tezlab.group/tesla-fam
@Tesllatino @wholemars @DirtyTesLa i know you do. I love this app.
My team at @Tesla is hiring a talented 3D generalist to help build the Tesla App!
Looking for a strong portfolio of 3d art, experience with game engines, and an eye for design
You’ll get to ship to real customers, build cool stuff, and work closely with me
TezLab retweeted
We’ve learned how to build skilled agents, but still don’t know how to run them as a team.
Huawei Noah’s Ark Lab proposed OneManCompany (OMC) – an organisational layer for multi-agent systems that treats agents like employees in a real company.
The main idea is to move from Skills → Talents
A Skill is a tool/function inside one agent. But a Talent is a full agent package: role, tools, skills, prompts, configs, and working principles.
So OMC can "hire" a specialist agent.
The system has 3 main pillars:
1. Talent + Container = Employee
Talent = who the agent is: developer, designer, researcher, etc.
Container = where it runs, like Claude Code, LangGraph, scripts, etc.
So different kinds of agents can work together in one organisation through shared interfaces.
2. Talent Market
If the current team lacks a capability, OMC can recruit a new "specialist" from a marketplace of verified agents. The agent team is fully configurable
3. E2R tree search: Explore–Execute–Review loop
- explores how to decompose the task
- assigns subtasks to agents
- executes them
- reviews outputs before they can unblock downstream work
- retries or re-decomposes when something fails
Tasks form a dynamic tree/DAG with review gates, so bad intermediate outputs don’t silently propagate. Plus, agents update their own working principles after tasks and feedback.
There is even an HR-style lifecycle: performance reviews → Performance Improvement Plan (PIP) → offboarding → replacement from the Talent Market.
OMC proved its efficiency, reaching 84.67% success on PRDBench, about 15 percentage points better than previous baselines. So this is a strategy worth taking a closer look at.
TezLab retweeted
FSD 14.3 is two weeks old in our fleet data. Too early for conclusions, but the behavioral signal is clean.
Go-pedal override (median): 1.8%. That's the lowest of any 14.x sub-version we've tracked. For context, 14.2.2.5 sits at 2.8%, 14.2.2.4 at 3.6%.
Hard braking: 10.8 per 1,000 miles vs 15-18 for mature 14.2.x builds.
Whole-drive autonomy is right at 50%, in line with the broader 14.x average.
The caveat: small sample, early adopter bias is real, and two weeks of data isn't a trend. But when go-pedal AND hard braking AND whole-drive all point the same direction from day one, it's worth paying attention.
We'll keep tracking. Gigalytics data. @TezLabApp @munster_gene @wholemars
TezLab retweeted
The FSD subscription flywheel is real, and nobody's tracking it.
Here's what's actually happening inside Tesla's FSD business right now, from our fleet telemetry data at @TezLabApp.
The metric nobody's watching: subscribed % of fleet.
Oct '25: 2.42%
Jan '26: 3.56%
Apr '26: 5.24%
That's more than doubled in six months. And it's accelerating. Subscribed share added almost a full point in March alone (4.34% → 5.13%).
To understand why, you have to go back to what Tesla did over the holidays.
In late November 2025, Tesla pushed a free 40-day FSD v14 trial to roughly 1.5 million HW4 vehicles. Biggest trial deployment they've ever run, timed perfectly for holiday road trips. In our data, December's new subscriber cohort was 84% trial users, just 16% paid. Tesla was betting that seat time would convert free users into paying customers.
That trial expired January 8.
What happened next is the interesting part. Trial volume collapsed. December's cohort was overwhelmingly trial, but January flipped to 78% paid. By March: 97% paid.
April is tracking 96%.
The trial-as-funnel strategy didn't produce mass conversion. But what it did do is clarify the subscriber base.
Look at M1 retention (the percentage still subscribed after one month) by subscriber type:
Paid M1 retention is consistently in the 86–100% range across cohorts with meaningful sample sizes. Remarkably stable.
Trial M1 retention: 81% in October, 41% by March. And by M2 (two months), trial retention drops to single digits. The December holiday cohort, Tesla's biggest bet, retained just 1% at M2. Essentially nobody who got the free trial stuck around.
Here's the thing people will miss. The overall M1 retention number for March looks great at 91.1%. But it looks great because the composition changed, not because retention "improved" in the abstract. When 97% of your cohort is paid subscribers who retain at 92%+, the blended number naturally rises. That's not a retention improvement. It's a base quality improvement. Important distinction.
Then on February 14, Tesla ended outright FSD purchases entirely. No more $8,000 one-time buy option. It's $99/month or nothing. (as of today:)
This is where the compounding kicks in.
The mechanics: new paid subscribers enter each month. They retain at 87%+ even four months in (the October '25 paid cohort, our oldest with M4 data, is still at 87%). Very few leave. Each new month's cohort stacks on top of the ones still there. Since the trial churn cleared in late January, activations have exceeded churns every single week. 12 straight and counting. That's how you get subscribed share doubling.
Meanwhile purchased % peaked around 8.5% in December and has been slowly eroding. 7.78% and declining. Natural attrition as people sell vehicles, trade in, etc. Since Tesla killed the purchase option, that line can only go down from here. The subscribed line can only go up. At the current trajectory, they cross sometime this year. (A few older subscribers transferred FSD to HW4 but that's a very small number.)
One more corroborating signal worth paying attention to: the people who subscribe aren't casual about it. FSD now accounts for 50.5% of driving distance and 63.1% of driving duration among users. These aren't people toggling it on occasionally. FSD is their default driving mode. The gap between distance and duration is itself interesting. FSD overindexes on city and slower-speed driving versus highway, which is where the higher duration percentage comes from. That's consistent with what we see in the whole-drive autonomy data: v14.x users complete 50% of their drives entirely on FSD without intervention.
What this doesn't tell you: whether the holiday trial "failed." You could frame 1.5 million free trials with near-zero conversion as a waste. Or you could frame it as Tesla stress-testing the funnel at massive scale and learning that the product now sells itself to people who are ready to pay. No free taste needed. The fact that Tesla followed the trial by killing outright purchases suggests they're betting on the second interpretation.
Either way, the observable outcome is this: the casual users washed out, the purchase option is gone, and what's left is a subscription base that compounds because retention is high enough that inflows consistently beat outflows.
That's the flywheel. And it's the number to watch going forward.
Exclusive data from @TezLabApp fleet telemetry · gigalytics.io @CernBasher @herbertong @wholemars @DirtyTesLa @farzyness
TezLab retweeted
Neural Computers explained
It looks like a computer running code, but it’s just a model rendering the simulation. No real computation
What is actually happening here - and is this the future of computing or just a very convincing illusion?
TezLab retweeted

Cern Basher@CernBasherApr 2
United States
United StatesConnected via United States App StoreAccount-level information, not a live location or per-post device.
Tesla Q1 Inventories - Relax People
By my calculations, Tesla's global vehicle inventory was ~28 days for Q1, up from just 15 days in Q4.
But 28 days of inventory is not the true picture - it's really lower than that if we take into account "transport days."
1) Transport Days: the number of days needed to transport newly produced vehicles from the factory to the end customer. If we assume that vehicles made in Fremont, Texas and Berlin generally take two weeks to be delivered via rail and/or truck to the customer, and if we assume that vehicles made in Shanghai are split 50/50 between exports and in-country sales then the global average transport time comes to about three weeks (measured as 18 days).
2) True Inventory Days: this is the difference between the total Inventory Days of Supply and the Transport Days - bringing the Q1 2026 number to just 10 days of inventory!
This is a global average. In reality the inventory is likely even lower in the US and higher internationally.
@thejefflutz
TezLab retweeted
FSD 14.3. --> We are and will continue to track all 14.3 releases and share all FSD related information related to trends as they come in. We expect to have clear pictures soon. We'll keep everyone posted. @TezLabApp @wholemars @herbertongg2
TezLab retweeted
We spent a long time building this. FSD tracking that's 100% proprietary — no one else has it because Tesla doesn't expose this data through their API.
Every session. Every takeover. All tracked.
14-day free trial: tezlabapp.com/subscribe

























