No, you're wrong about this. One obvious reason why: I'd have gotten rid of those "justs" myself before models were available; it just would have taken me longer.
You stop relying on the agents following instructions exactly.
You need two pieces:
a) prompts, that tell the agents what to do and how to do it (and ideally, the why, where, etc, the full picture) - that's the positive half, that drives behavior the way you want it.
b) deterministic tooling that prevents negative outcomes, like linters, compilers, static analysis, fuzzing, testing, the more the better. This side should either be firewalled off from the AI or very carefully watched so that it doesn't drift.
The part that you put in the deterministic side is the "never do x" stuff - I have lint for long comments (which AI hits every single time it commits), all my dev scripts are in typescript, precommit hooks, massive CI, and I lint even for things like redirecting error to standard out, tiny stuff, and also e.g. static migration analysis so the AI never ships an exclusive full table lock in a migration, for example.
You can’t deterministically keep them from making even a tiny fraction of all the possible errors they can and do make though.
You can’t keep humans from making those errors either but you also don’t let an error prone human crank out 20k LOC per day without forcing other humans to understand it.
C# Roslyn Analyzers[0], for example, are quite powerful and can identify complex patterns in code. One approach to deterministic enforcement would be to ensure that the project is set up with an analyzers library and mistakes that can be deterministically flagged are
Code analysis can’t detect a sizable fraction of all possible errors because for any Turing complete language the number of possible errors is infinite.
Each of these are just layers of control at different lifecycles of agent code generation. Analyzers are nice because it gives targeted, static analysis that can prevent certain classes of errors very early and at lower iterative cost (e.g. a build)
I don't know if that's necessarily true in practice the way it is in theory. If you knock down 95% of the issues they create over a certain period of time, in practice you'll have better code than a human would write, and it's all upside from there.
I've been using languages with stronger type systems and that's also a huge boon.
Why would that be the case? You can run human written code through the same “linters, compilers, static analysis, fuzzing, testing” as you do agent produced code.
You would be surprised. Humans will do human things like be extremely inconsistent, ignore warnings (if they are not enforced as errors), skip steps because they are lazy (devs often chose to skip our pre-push hooks and preferred to run in CI and babysit the PR).
Agents can also do all of those things, but they are generally more compliant to instruction.
yes, this is a very helpful approach. I take a similar approach, partly because I find bringing up negative directions seem to bring the undesired action/direction into the agent's view and makes it more likely that they will go there
Why couldn't you express all those as test cases rather than instructions?
In test cases i can do anything, a test framework is just a way of discovering and then scheduling functions to run. I can emit useful instructions to the agent from the failed test case: "After walking the AST of all use of state machine X, a branch was found at Y which reused stale state. Ensure stale references are dropped..."
I can force the agent to pass the test suite before it considers itself done. I can reject edits of such test cases to partially mitigate reward hacking. etc etc
You can express them as tests, but you also need a feedback mechanism that creates the rule that when the LLM generates some net new code or performs some refactor, that there are these CAPAs that it needs to cover with test cases.
The CAPA is a learning that sits outside of the mechanism of verification; it is a record of problem:root_cause:preventative_action. I see it as the instruction that would be required to generate the test case to prevent the next occurrence of a class of failures.
In a real-world process, for example, there is usually a QA lead that is verifying that the process is followed by looking at the paperwork and evidence.
> Why couldn't you express all those as test cases rather than instructions?
How would prevent removing the test case and the code that it tests? That's a legitimate thing to do when you're modifying a codebase. My intuition is "corrective and preventative actions (CAPA)" is a level or two up from test cases.
This is a question of context management and I suppose some would classify this as "harness engineering" as the trend of the moment.
One approach, for example, might be to have the a standalone code reviewer agent that is solely responsible for interfacing with the CAPA system (e.g. via a tool, via MCP) and acts as a back stop. When it finds a new type of CAPA, it stores it (and the backend indexes it with enough metadata to support broad types of retrieval). When it reviews a piece of code, it finds past CAPAs. By file locality. By business domain in the application. By keywords.
Same tool and repository available to both building agents and review agents, but use the review agent as a dedicated back stop as part of the verification process.
How is it failure? You use your military to force trade to occur using your tokens. You control the supply of said tokens. You leave some other loser holding the bag for your debts. You win.
Because they cannot force the world to buy their meme token anymore. Either they pay up and joing the world being a good credit-score conscious citizen or they get the boot.
And people still think they don't have a political choice because it is impossible to pay it up. You are all alienated and going to the double down disaster.
Well, if there was an emergent consciousness in the billion transistors, then yes, it'd have feelings, just as there are feelings in a billion neurons connected in complicated ways.
IMO we're clearly nowhere near any sort of intelligence in the machines we have created, but I don't see any clear way to deny intelligence could be created in or transferred to such a substrate, I don't see why you think it differs in principle - because it is man-made or because of the materials used?
Whenever I see comments like this it just reminds me how ignorant people are of neurobiology.
The brain is insanely complicated. The premise that we could realize equivalent or better intelligence than eons of evolutionary development is like claiming you can build an airplane just as good as a modern jet using cardboard and duct tape. It is the apex of hubris.
A paper plane does have some important similarities to a full-sized aircraft, though. I don't think 'biological brains are really complex' makes it obvious that an LLM is conscious or not.
It's the peak of hubris to assume that human brains are the only way to attain intelligence. At the very least there probably are or have been other forms of intelligence with a different biological structure on other planets, and it may be possible to build a similar artificial structure in future with sufficient complexity to allow intelligence to emerge.
Our current machines are IMO nowhere near general intelligence and consciousness. However I don't think that means we can discount substrates other than neurones for intelligence in future. There is no evidence that you could not in theory build an intelligence using a different substrate than human brains.
>like claiming you can build an airplane just as good as a modern jet using cardboard and duct tape.
Like, at least make an analogy that makes sense.
"You can't build a billion dollar airplane by spending 100 billion dollars in tokens"
Because that's more of what we're doing here with AI. And when you say it my way suddenly the idea shifts from "of course that's not possible" to "well, that's a lot of tokens, maybe an evolutionary algorithm could".
Neurobiology has to be complex because we have to keep meat alive, breeding, and evolving in the environment it lives in. This said absolutely nothing about the minimum viable requirements for intelligence or consciousness (or if being conscious is even necessary for a higher intelligence agent).
If they need capital in the short term and were anywhere close to AGI, they could easily generate it, by spinning up their incredibly capable and intelligent agents to generate capital through doing useful work. They could also fire entire departments within their own org and replace them with agents, if they had something close to AGI.
Instead they are selling a dream to the gullible, and advertisements to go along with that dream.
while i suspect youre right, this cannot be concluded with the information we have as of today.
eg its also possible that theyre either close to AGI (or even beyond it) - and its just too expensive to run at scale, making it a novelty from the perspective of profitability for the near to medium future.
you could argue that they could still do it for some positions -- but even that depends on just how expensive this theoretical model is.
"OpenAI released its latest model, GPT-6 Astra, on Thursday, with company President Greg Brockman calling it the beginning of the artificial general intelligence (AGI) era."
But they're still peddling ads instead of improving the world. How odd.
> AGI makes a lot better argument if everyone is in idiocracy.
IIRC, a part of the backstory of Idiocracy is the development of pervasive and good enough AI/automation, which enabled society to get that dumb without immediately collapsing.
They can talk about AGI without claiming the current model is AI. They can talk about emergent intelligence without claiming it’s AGI. And businesses can work on multiple things with different goals without being contradictory.
What if their AGI/ASI told them the road to Humanity betterment (because you know that was OpenAI initial mission, just in case we forgot) was through more efficient ads ? /s
We should just build up enough nuclear deterrent to prevent Russia from attacking us.
We've been dependent on the US for this but this was also by the US' own design. They didn't want many countries to have nukes. So the whole 'Europe is not doing its bit' is not really justified.
We don't need more tanks and soldiers because if we go at Russia like Ukraine does, so many people will die that it doesn't matter who wins. We just need to be able to destroy Russia so thoroughly that they won't think about attacking us, just like they don't attack the US. Mutually assured destruction has kept the world safe for almost a century but now with the US no longer committed to NATO we just need to build our own.
Well what I mean is tanks across the border. Some psyops and a drone here and there is not really cause to go all out. A tank division invading Poland would be, of course.
And Europa has some deterrent but nothing compared to the Russian one. We have a major 'missile gap' right now.
This is not true. UK and FR have them (probably not enough though). UK/FR definitely wouldn't retaliate if Berlin or Warsaw were to be hit by a RU nuke.
Europe is already in a warm-war with Russia. EU has sent hundreds of thousands of drones used to attack Russia - along with training, intelligence and target guidance. EU airspace is used openly by Ukraine to attack Russia. IMHO, war should be openly declared with clear objectives. That way the Russian €200 billion can be openly seized without all the whining.
This puzzles me. If Ukrainian drones have free reign of EU airspace to carry out attacks on Russia, then why can't Russian drones cross EU airspace ? Isn't that just symmetric ? Have any Russian drones caused EU casualties ?
If you want to improve your writing, read more.
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