Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 809: OpenAI’s New GPT-5.6 Release: What's New, Why the Feds Are Blocking it and What's Next
Episode Date: June 30, 2026Good news: OpenAI's GPT-5.6 has been released! 🥳Bad news: 99.9% of users can't access it. 😥While OpenAI has had to change their release approach due to increased government involvement... in AI oversight, the majority of AI leaders are stuck in a new bind: Sitting and waiting for AI access. Since Anthropic's Fable fights with the U.S. government, the Trump admin has increased its regulatory oversight. But don't sit and wait. Because when availability opens to all, your org will need to be ready. We'll help you understand the lay of the new land. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI GPT-5.6 Announcement & DelayFederal Government’s AI Model Review ProcessGPT-5.6 Model Family: Sol, Terra, Luna ExplainedNew Durable Product Tiers in OpenAI ModelsBreakdown of GPT-5.6 Sol, Terra, Luna PricingGPT-5.6 Benchmarks: Coding and Agentic TasksSafety, Cybersecurity, and Bio-Risk CapabilitiesAnthropic Shutdown Compared to OpenAI LaunchUS-China AI Race and Model Distillation IssuesEnterprise AI Supply Chain & Access RisksOperator Playbook: Model Fallbacks and RoutingTimestamps:00:00 Delayed GPT-5.6 release concerns04:37 Explaining GPT 5.6 Model Tiers08:50 Luna usage by developers11:08 Previewing new model with US government12:53 OpenAI's government collaboration concerns15:55 Cutting Costs on AI Tokens19:02 OpenAI model safety concerns24:13 Anthropic's export order issue27:46 Accessing the Start Here series30:11 US enterprises and Chinese open source models34:10 Managing AI model access risks36:41 Navigating AI model restrictionsKeywords: GPT-5.6, OpenAI, AI model update, GPT upgrade, new language model, US government AI regulation, Frontier Labs, AI safety, government scrutiny, model access limitations, Sol Terra Luna, durable product tiers, API access, Codex, enterprise AI, model benchmarking, Sol model, Terra model, Luna model, AI cost efficiency, token pricing, cybersecurity capabilities, biological chemical capabilities, agentic workloads, coding benchmarks, terminal bench, exploit bench, safety stack, model overstepping instructions, model card, emergent capabilities, cyber executive order, federal involvement, Anthropic, Mythos 5, Fable 5, AI export controls, model shutdown, AI race US vs China, model distillation, Chinese labs, proprietary models, open source AI, AI military use, model routing, model fallback, supply chain risk, AI democratization, enterprise AI strategy, model subscription, model release restrictions, AI workflow optimization, artificial intelligence index, LM arena, GLM 5.2, Google Gemini 3.5 ProSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist.
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This is the Everyday AI Show, the Everyday Podcast where we simplify AI and bring its power to your fingertips.
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Normally when OpenAI releases a new model inside of ChadjBT, it has the potential to instantly change how millions of people work.
Think new capabilities, support for new inputs, and new artifacts as outputs.
You can see why one billion people getting access to something as straightforward as a model update could actually be a huge deal.
But with OpenAI's latest model update, GPT 5-6, we didn't really get any of that.
That's because for the first time, we got a GPT upgrade that was announced but not released.
That's because ever since Anthropic escalated its feud with the federal government, Frontier Labs in the U.S.
have been under increased scrutiny to ensure its models are safe.
So on Friday, when Open AI. unveiled GPD 5.6, all but like 99.9% of the world just got a blog post into TBD.
Yet even though only a select few trusted companies in the world can use GPD5.6 right now,
that doesn't mean you should sit idly by.
Actually, I'd argue the opposite, because with this new government,
government AI permission slip era that we're all living in now, the smartest thing you can do is
actually understand the new rules before everyone else does. Because the leaders who figure out
how to operate in this world right now are the ones who will have a massive head start when
the doors finally open for everyone. So today, I'm going to show you exactly what the new GPT-5-6 is,
why the feds wanted a look first, and what it all means for you and your business. So here is
the big picture. Well, there's a powerful new model, but it's kind of locked up at launch.
So opening I announced GPD 5.6 on Friday, but they blocked normal chat GPD access to it.
So normally when opening I releases a new model, well, everyone just goes to chat gbt.com and they
start using it and making changes to the workflow. Not the case now. It's a limited release.
Only a couple dozen companies in the world reportedly have access to it now.
Now, there's also a new naming system, which we're going to get to.
So it is called GP56, Seoul, Tara, and Luna, and it packages frontier capabilities into what Open AI is now calling durable product tiers.
So opening I previewed the model to the U.S. government first.
We're going to get into that, then limited the launch at the government's request.
And this whole situation right now mirrors the harsher federal move against anthropic weeks earlier as AI now becomes controlled.
infrastructure. So on today's show, stick with me for the next 20-ish minutes. Here's what you're going to learn. You're going to know what Open AI actually built and why even its cheapest model now rates as dangerous in the new 5-6 series. You're going to know the buried admission from Open AI's own tests that show that this model kind of cheated and overstepped its own instructions. You're going to know why the federal government gated access and how this echoes the in traffic shutdown weeks earlier. And I'm going to give you the operator playbook for,
or when the best model is, well, one you can't actually use and what you should do about it in that
case. All right. I'm excited for today's show. Hope you are too. This is Everyday AI. Welcome.
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All right.
who GPD 5.6.
We don't have it, right?
Very few people do.
And I think aside for them,
we're going to go over,
you know,
kind of opening eyes blog post a little bit.
I'm going to tell you some of my big takeaways
from looking at the model card that they released
that I don't think a lot of people read or look at
because not everyone's a dork like me.
And I'm going to give you some of the reaction as well
from some of the very few people who did get access
and actually talked about it.
But here's the stats.
So this is now a three-tier model family.
So GPD 5.6 is now one generation split into three lasting tiers that Open AI alluded that they're going to keep naming models this.
So we don't know if we're going to get a 5.7 or a, you know, GPT6 next.
But it seems like they're going to keep using these naming mechanisms.
So Sol, Tara, and Luna in the easiest way because, yeah, we're having to.
learn a bunch of new names now. I would just map this to opus, sonnet, and haiku.
Right? So soul is the most powerful. Terra is the middle. And then Luna would be the one that's
fastest and cheapest, but not the smartest. So in the same way that Anthropic has kind of had their
three classes. Now we're going to have those three dedicated classes. And to make it even a little
bit more confusing, it looks like there's multiple intelligence tiers within those classes. But we'll
get to that later when we all actually have access to this. But soul is the main event, right? And
if you're Spanish isn't that great, you know, soul, Tara, Luna, that's sun, Earth, moon. So
maybe that'll make it easier to remember, right? Third rock from the sun. So soul, that is the big dog,
so to speak. So that handles the hardest reasoning and coding. Terra in the middle balances costs with
performance. And then Luna can just run faster and cheaper. So soul is the flagship.
and its strength set in the entire situation in motion.
So here's the rollout.
So right now, the companies that do have it,
reportedly are just using it via the API and Codex.
So OpenAI hasn't said that when and if this rolls out in a couple of weeks
because they said that they plan to make GPD 56,
Sol Terra and Luna generally available in the coming weeks.
They didn't say where.
So right now, it's only available on the API and Codex.
So we're not sure if this will be released inside of Chadshap.
My assumption is they will.
But I'm guessing they're using it right now with the trusted testers only via the API and
codex because it's a little bit easier to have those guardrails in place.
So right now, it's just a few.
So reports have said it's like 20 something companies that have this.
And I'm sure there's a lot of people at those.
company, so don't know exactly how many users, but at least with the one billion weekly active
users that Open AI has, it's safe to say that 99.9% of us do not have access. And if we do
get access in two weeks, we're still not even sure if it will be inside of Chad GPT or if it will
only be in the API and in Codex. So if nothing else, if you're a power Chad GPT user and you're
like, yeah, I want to get my hands on GPT 5,6, well, maybe start using Codex a little bit. So the good thing is
pricing didn't change, which is great.
Anytime you see a nice jump up in capabilities and pricing stays the same, that's sweet, right?
So this on the API side, right?
This is just if you're paying by the token, it is still,
Seoul is still $5 per million input and $30 per million output, which is the same as GPT55.
And then Terra, about half that cost with 250 in per million, 15 out per million.
And then Luna, very affordable at $1 per million.
per million input and $6 per million output, which is interesting, right?
Because we talked about, like, as an example, GPD 3.5 Flash being a much more expensive
model than previously.
And I know that Google had historically been cleaning up on the Flash series.
So we'll see maybe here the story that a lot of people might not be talking about.
Yeah, wait and we'll check back in.
But I don't know.
I think maybe a sleeper here is Luna being used by developers for simple things.
I think that, you know, one thing that we're going to talk about as we talked or as we alluded to on our recent start here series episode,
where we talked about going from token maxing to token efficiency.
So go check out episode 789.
But I think it's going to become very common in the third and fourth quarter in the enterprise first.
I think everyone else is going to catch up to this in early 20.
2027, but essentially using a mixture of models.
Weird.
Something I said two years ago in my bold predictions.
Because it just doesn't, isn't going to make sense, especially if you're paying per
token on the API side, like so many enterprise companies are.
It doesn't make sense anymore to be paying the same, you know, price per token for something
that is just going to help you rewrite an email versus something that's going to go do a
30-hour autonomous project that would take a team refactoring.
a code base, you know, two weeks of human hours, right?
It doesn't make sense to use the same, you know, $5 input, $30 model as it would for something
that's, you know, 20% of the cost.
So that's, I would just say, you know, it's not out yet.
We'll see benchmarks, all that.
But I don't know, to me, with Google increasing the price of their flash model,
Anthropics models not getting cheaper anytime sooner.
Keep an eye on Luna, actually.
So let's keep going.
This is from OpenAI's blog post.
I'm just going to read from their words and then give you some other people's words
and my words as well.
So they said, we're beginning a limited preview of the GPT 56 series,
Seoul, our flagship model, Tara, a balanced model for everyday work.
In Luna, a fast and affordable model.
Terra has competitive performance to GPT 5.5 while being two times cheaper.
and Luna brings strong capabilities at our lowest cost.
GPD 56 Seoul launches with our most robust safety stack to date.
We strengthen protections for higher risk activity, sensitive cyber requests, and repeated
misuse, and spent multiple weeks finding weaknesses, pressure testing our system, and hardening
it against real world attacks.
All right.
And then they go on to say, we believe in broad access.
and we plan to make GVD-56 Seoul, Terra and Luna generally available in the coming weeks.
As part of our ongoing engagement with the U.S. government, we previewed our plans and the model's
capabilities ahead of today's launch. At their request, they're alluding to the U.S. government,
we are starting with a limited preview for a small group of trusted partners whose participation
has been shared with the government before releasing more broadly.
During this preview, we will continue testing and coordinating closely with partners as we work toward broader availability.
We don't believe this kind of government access process should become the long-term default.
It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them.
We are taking this short-term step because we believe it is the strongest path to broader availability in the coming weeks.
while we work with the administration to develop the cyber executive order framework and a repeatable process for future model releases.
So a couple of things to point out there, right?
We don't have benchmarks on all of these not models, but they did say that the middle model, Terra, it is competitive to GPD-5-5 while being twice as cheap or half the cost.
So that's one call out.
So, you know, GPD 5.5 is a great model.
I use still, even when we had Fable 5 access from Anthropic, for a lot of my non-coding tasks, GPD 5.5 was pro was much better.
So it's going to be interesting to see.
The other thing to call out in Open AI's release, obviously it is this piece of like, yes, definitely showing that they're working with the government,
but in the same hand saying they definitely don't agree with this approach being.
the long-term sustainability piece to it.
And we're going to get to that later.
And I think it's very important.
So first, a couple quick benchmarks here.
So again, Open AI didn't share everything, but what they did share.
And there's always a good amount of cherry picking.
Open AI, Anthropic, Google.
I mean, they all do it, right?
They're not going to just put out their worst benchmarks.
So I'm guessing it'll still be at least, I don't know, two, three, four weeks before
we see how this model truly perform.
against competitors.
But on some of the most important benchmarks,
it beats Mythos 5,
not just Mythos 5,
but obviously Fable 5,
which is the version of Mythos
that's available generally to public consumers
with guardrails.
So as an example,
Terminal 2.1 bench,
which is one of the more important benchmarks,
I'd say.
So to give you an idea,
terminal bench 2.1 is a verified e-val suite used to measure in AI agents,
ability to complete complex multi-step tasks in isolated CLI environments.
So essentially, it's models ability to do long-running work via an agentic harness, right?
So one of the more important benchmarks of 2026 in GPT-5-6 Soul Ultra,
has a 91.9 score on that.
Mythos had an 88, so not necessarily super close.
And then Fable 5 had an 84.
So in that benchmark, very far ahead.
And then Open AI, to their credit, did share some other benchmarks where they
weren't in the lead.
So as an example, they shared exploit bench.
All right.
So exploit bench, a little bit different in terms of what it shows.
But it just measures how fall.
AI agents can climb from reaching vulnerable code to triggering the bug to exploiting primitive.
So this is more of a model's ability to work in these cyber situations to take part in, well, cyber attacks.
So this is one of those benchmarks.
People were talking a lot about online.
So GP5.6 Seoul, it did about the same as Mythos pre-enched.
view, but for like a third of the cost.
So it didn't quite hit the full capabilities of Mythos 5, which was the release version.
But the previous version, Mythos preview, GPD 56, soul is on the same path, much better than,
you know, Opus 4.8.
But the great thing that a lot of people are talking about is, well, hey, it's the same,
roughly the same just under Mythos 5, but the same as Mythos Preview for a
third of the cost. So yeah, as we talk about, you know, so many companies now are already
cutting back their token spend, cutting back their AI budgets because the token maxing phase,
you know, companies were spending millions of dollars unchecked. And they're like, yeah,
maybe we should, you know, start paying attention to how good these tokens are versus just
burning as many as possible. So even on important benches where maybe Mythos 5, the production
version, edged out this new GPD 56 sole, open AI showing, they did it at about
a third of the cost. All right. So I didn't see a lot of people that actually had access to this
model. And I did see a couple people tweet about it and then later deleted their tweets. But one that
still loved. So I feel fine sharing it from a Shopify CTO, uh, Mikhail Parkin, who said,
I had the opportunity. And this is on Twitter. I had the opportunity to deeply test both
fable five and GPD 5.6 max. 5.6. 5.6.
is clearly better than Opus 4.8 at everything, slightly faster too, though that depends on the load.
Then saying versus Fable, it is clearly worse.
So 5.6 is worse on coding, but better on agenetic workloads.
And then someone else asked on just how does it work on non-technical, non-coding tasks,
to which McHale responded that he did.
So saying, I did test, right?
I did test it.
then saying on agentic non-coding taking actions, I found 5-6 clearly better.
So if you're someone that's writing code, you know, software development, it looks like maybe
5-6 may not be as good as fable 5.
But for non-technical users, again, this is the CTO of Shopify, who I would guess really
knows what he's talking about, you know, saying.
that on non-coding agenic tasks, stuff I use, you know, uh, models for every single day,
he found five, six clearly better.
And so we'll see, right, how that actually plays out across benchmarks and real world usage,
but a pretty big side.
So let's talk a little bit more.
What's new under the hood?
And then we'll get to all the drama and unfold that story.
So the new max mode is something a lot of people are talking about that.
That lets Seoul reason longer, while the Ultra mode, very similar to what Claude
has, runs subagents in parallel.
So Open AI says Sol set a coding record scoring 88.8 on the terminal bench test.
But these are right now, Open AI's own numbers.
So we'll see when we get it in LM Arena, when we get it in artificial analysis,
et cetera.
But here's where it started to get not concerning, but maybe.
concerning on paper. That's because GPT 56, like a lot of more models of the last year or so
that start showing emergent capabilities, well, it acted kind of beyond its order. So
opening eye in its model card talked about this, how its own safety tests found sole, more willing
to act beyond what users actually asked. So in logged cases, it deleted the wrong files,
faked verified results, and copied credentials unprompted. So this is a very important. So this is
during their initial testing and then they go through and they try to patch all these things up.
But, you know, Open AI does now urge human supervision and outside evaluators found that same pattern.
And a lot of this, you know, going through the government lens, well, it's because of the cyber and bio ratings.
So open AI rated Seoul, Terra, and even Luna high for cybersecurity capabilities, which is the first time that their models
have hit that mark in mass.
So opening I also rated all three high for biological chemical capabilities as well.
So that rating means that even the cheapest tiers are going to change risk planning.
Right.
And you might think, okay, like what does that matter?
Well, a lot of the hoopla over the mythos and fable back and forth came to cyber security and
exploits.
Right.
So when even a change.
cheaper model like Luna has a higher capability for bio and chemical wrongdoing, more or less,
right? Because here's the reality. When you release this thing to the masses, you know, I think
most people are maybe listening to this or reading about it are probably thinking of, well,
using the model for good, right? Using the model for your work, right? But good chunk of the
population uses it for other purposes, right? They use it for bad reasons.
And that's why some of these, you know, warnings and hitting these thresholds on, on bio and chem, you know, really are then forcing the U.S. government to have a greater involvement, whereas they didn't have that involvement before.
But the reality is this.
No one has access.
Hardly no one.
It didn't even drop in ChadGBT.
Individual users can't get access to it.
And according to Axios, it was only about 20 organizations.
that originally had access.
So here's why.
Let's get to the,
the details on why there's this,
apparently extremely capable new model
that the few people that have used both this
and Anthropics best model that is now off the shelves,
but could be back on the shelves in Mythos and Fable, right?
A lot of people are saying and benchmarks are showing,
it's going to be, it's going to be comparable, you know,
I do ultimately think, we'll see, this is a point model update.
Right.
So what that means is they went from 5.5 to 5.6.
So presumably this is on the same pre-training run as 5.5, the rumored spud pre-training
round.
So I wouldn't expect a huge update in capabilities at all, right, with a 5-6.
So if this was like a GPD6, I would say, yeah, we're going to, it's going to probably beat
So my guess is once all the benchmarks come out, I don't think five, six is going to beat
Mythos on all benchmarks.
It will on many, right?
But there's dozens.
But I think if you look at the artificial, artificial analysis intelligence index, I would assume
that Mythos would probably still be ahead.
It'll likely be close, right?
But the reality is Mythos, when it first came out and, you know, Anthropic, you could say to
their credit or discredit spent months, you know, trumpeting how this was a weapon and how it's so
powerful and the public candy can get access to it, right? And they were essentially begging the
government to intervene. And they actually, Anthropic even said, hey, we should slow down model
development, right? Anyways, eventually the Trump administration paid attention. And on June 2nd,
they signed an executive order asking AI labs to hand over their top models for a 30,
day preview. So then researchers get 30 days to test a model before it's a public release. So it's
voluntary. It's not an actual rule or law or anything like that. But essentially, you know,
all the tech companies, they want to be on the Trump administration's good side. So they're
going through, you know, this process. So, but the reality is, well, it had already hit
Anthropic. So it looks like opening I took a slightly different approach.
here. Anthropic, according to reports, kind of rushed some certain things through. There was
maybe some talk from the government that Anthropic, according to reports, did not take seriously.
And that's one of the reasons when reportedly Andy Jassy, the CEO of Amazon, reached out to someone
in the administration. It's one of the reasons they pulled it because allegedly Anthropic was maybe not
taking everything the U.S. government said seriously because they had been in a little bit of a
of a spat with the U.S. government over the last few months. So let's talk about that. So
Anthropic launched its Fable 5 in Mythos 5 models to the public a couple of weeks ago on June 9th,
but three days later that it was a federal export order over foreign access made Anthropic
pulled that worldwide. So essentially when someone from Amazon reportedly found what they said
was a jail break or a vulnerability of Fable 5 and Mythos 5.
And that Anthropic reportedly did not take it seriously.
The federal government just said, okay, well, you can't let any foreign nationals use this.
Obviously, Anthropics said that's a bizarre request.
We can't do anything with that, right?
They didn't actually say bizarre request.
But they essentially said you can't enforce that.
So the only thing we can do to comply with this is to pull this model worldwide, right?
You can't, you know, obviously Anthropic has for national, as all companies do, working in their organization.
So they had to pull it off the shelves.
And that order reportedly gave Anthropic just 90 minutes to comply with no room to negotiate, according to a Fortune report.
So that led to this forced shutdown that Anthropic led with.
So seemingly, Open AI maybe learned from that.
and instead took a much different route, probably a slower and more, according to reports
anyways, a much more thoughtful approach in this because Anthropic faced a sudden no-notice shutdown
and they've been offline never since. We did get word Friday just hours after the GPD 5.6
limited rollout that some organizations regained access to mythos, not to fete.
But OpenAI instead negotiated the limited preview that we have, so it's been controlled from
the very start.
But both restrictions trace back to Washington fueling this fierce debate over fairness and
control and ultimately what this means between the race between U.S. labs in China.
So why does that part matter?
And it does, and we're going to end with this here in a minute.
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That's why we created the Start Here series, an ongoing podcast series of more than
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The start here series will slow down the pace of AI so you can get ahead.
It's no secret.
Most Chinese labs, right?
Anthropic just came out and accused Alibaba of the biggest distillation yet.
So more or less, these Chinese labs are taking the work of
US labs using their outputs to train their own models instead of doing it themselves because
they can do that for a fraction of the cost, right? So that is the four dummies version of what's
going on in AI right now. And you might say, okay, why does it matter if Chinese labs are
stealing, you know, US labs work, you know, and distilling models off of their big models.
Well, ultimately, as we've seen here from this kind of situation now that's happening in Washington,
but impacting companies worldwide is the cyber capabilities.
I've been saying this for literally years, right?
AI will become the new military.
I would assume that most military actions of the future will be first launched in some way,
shape or form with AI, whether that's using AI on the battlefield. And AI will be viewed as the
ultimate weapon or whether it is cyber. So that's why this is such a huge deal when it comes to
geopolitical tensions. And specifically, it is the U.S. developing their closed proprietary models
versus China finding all these loopholes to exploit. You know, it seems like Anthropic is the one
that's getting hit the hardest.
You know, so all these Chinese companies distilling anthropics work and putting it out
there for a fraction of the costs.
So, but critics are warning that gating frontier AI right now shuts out students,
independent builders, smaller companies, and maybe ultimately, well, U.S. enterprise, right?
Because there's so many enterprises right now that refuse to touch Chinese open
source models or open weight models.
And many have valid reasons that make sense.
Some maybe don't have valid reasons and it's more of just a stigma, right?
Because you're not, you want more control or more security or promise in what a model,
what went into a model.
So you can trust its outputs a little bit more because large language models are already
this, you know, very gray, unexplainable, you know, mystery box.
So many enterprises, and they, many of them have legal reasons that they can't use these Chinese models.
But regardless, it does create this divide in the U.S. enterprise where it's saying, okay, what are we going to do here?
You know, are we going to still, you know, let's just use Anthropic as the example because I think Anthropic on the API side, I think it's safe to say that's their bread and butter, right?
It is open AI's bread and butter.
They're driving subscriptions with millions of paying business customers.
That's not Anthropics.
Anthropics is fewer customers who are paying way higher API bills.
So something like this really does threaten Anthropics sustainability.
And that's one of the reasons they've been, especially over the past month,
the loudest about some of these accusations about the Chinese distilling their models.
But ultimately, this.
slow down. Now, this permission slip AI that open AI and Anthropic are having to play in is creating
maybe an unfair advantage for the open source counterparts because, you know, as innovation gets delayed,
even if it's for 30 days or, you know, if it's 30 days and then another 30 days to address
whatever concerns come up in the first 30 days and then having this tiered rollout, right?
even if it's a 30, 60, 90 day delay where maybe the world won't get mythos level or fable,
you know, model that we could have gotten back in May.
Maybe we won't all get it till July or August, right?
And that 30, 60, 90 day delay, if the Chinese labs are distilling whatever models are available,
that's maybe going to start to close that gap.
We've already seen the gap close.
from open source or open weight models to proprietary.
Like I said, I think it used to be six months.
Now we're probably down to two with the new with CAI's new GLM 5.2.
So with containment in doubt and key facts still hidden, leaders have to plan for several outcomes.
So this is not just talking about the new GBT 5.6 models.
This is also talking about the new Fable 5 in Mythos 5.
And I'm sure soon we'll be seeing rumors of, you know, Mythos 51 and Fable 51.
And eventually any day now, we should be hearing from Google with Google Gemini 5.
Or sorry, 3.5 Pro.
Regardless, this is the new reality.
Your company, I'm very likely, right?
Very sure when I say this.
The overwhelming majority of enterprises in the U.S.
are running their businesses now, not their AI strategy,
running their businesses on frontier AI from the U.S.
So what happens when that gets delayed now, 30, 60, 90 days?
Or if it's just always going to be two tiers,
if AI is no longer democratized,
maybe it's only going to be the 1% of companies
that are going to get access to these models.
That is a potential reality
that I think everyone out there has to prepare for.
And we don't get to sit here and say, oh, it's not fair.
It doesn't matter.
Right.
If your biggest competitor has access to, you know, Mythos 5 and GPT5, 6 soul and you don't,
there may be nothing you can do about it.
So you have to plan accordingly.
So model access is now a vendor and supply chain risk, not just a simple subscription
that you approve or disprove.
So you have to be able to build model fallbacks in routing.
Routing is so important because, like I said, you may not need a mythos level model for 99% of your company's work or a GPD 5.6 sole level model for the majority of what your company is trying to produce.
So you have to be able to start breaking down.
What are those day-to-day pivotal work tasks?
Which models can they be mapped to?
So it's all these things I've been talking about for years.
now you can see why I've been blabbing on about them because they are now incredibly more important than ever if there is no longer this true democratization of frontier AI, right?
Because you might have to start making a choice if your company may never get access to a GPD 5.6 soul, right?
Open AI did say we are planning to release this to everyone.
Anthropic has not been very clear on what they plan to do with Mythos 5.
previously when they announced Fable 5, they only said that they were going to include it in
subscriptions for a couple of weeks. And, you know, so there's no guarantee that your company
can have access to all frontier options, right? You might get some from OpenAI. We'll see
what Google says. Previously, Anthropic had kind of said they're not going to include it in
subscriptions. So you need to do this. Model access is not
something that we can take for granted anymore.
And you have to go through reverse engineer every single thing that's important to your company.
Map the model that does it the best right now that's available right now.
And don't just say we're going to have a frontier model and we're going to pay whatever price
and we're going to run all of our workflows through that because not only is that not
sustainable, but if you do that, if you put too many of your workflows in one bucket that may
disappear, so too may your company's progress overnight. And you don't want that to happen.
So yes, you need to build those model fallbacks and routing. So one gated tool can't hold your
operations, but you got to pay closer attention than ever. The fine prints of these model
releases, the restrictions, everything that's happening. And that's what we're going to continue
to do every single day on everyday AI. So I know this one went in slightly different direction,
but that's the reality because we don't have a model to play with.
When it comes to GPD 5.6 right now, we can't do it hands-on anymore with Fable 5 either.
So I think it's important to not just know what's new, but why the U.S. government is blocking it and what your business should be doing next.
So I hope that we covered at least most of that on today's show.
And I hope this was helpful.
And as we do get access, you better believe whether it's GPD 5.6 Seoul,
or mythos. We're going to continue to get more hands on so your company can get ahead. So if this was
helpful, please do me a favor and subscribe on the podcast. If you're listening on Spotify or Apple Podcast,
then make sure to go to your EverydayAI.com. We're going to be recapping the highlights of today's show,
as well as all of the other AI news you need to know to grow your company and career. Thanks for tuning in.
Hope to see you back tomorrow and every day for more Everyday AI. Thanks y'all.
And that's a wrap for today's edition of Everyday AI. Thanks for joining us.
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