Jason Kneen

Jason Kneen

x.com/jasonkneen

UK app developer who builds open-source AI agent tools and posts about how prompts and agents will change the way software is made.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

Across: his expressed Doom–Bloom outlook. Up: scale of transformation.

Doom–Bloom: 75 out of 100. Scale of transformation: 54 out of 100. Interpretation ranges: 70 to 80 horizontally, 49 to 76 vertically. These are interpretation coordinates, not event probabilities.

Jason Kneen’s P(doom) · inferred

≈5%

0%100%

Inferred from his simulated answers, not a number they gave. Plausible range: under 24%.

What his outlook hinges on

A central assumption

The blockers are still time, cost and reliability.
Answer 1

If this assumption turned out differently, how would his outlook change?

An unresolved question

“Smarter than humans” covers a lot, and I haven’t worked out whether meaningful control remains possible at that point.
Answer 4

What would help him distinguish the plausible outcomes here?

More details

Expected upside

Substantial benefits are expected, with important conditions or distribution limits.

72 / 100

Little impactTransformative impact

Interpretation range 67 to 100 on the qualitative scale.

Human influence

A tentative estimate from your answers; the wider range shows other plausible readings.

51 / 100

Little influenceStrong influence

Interpretation range 0 to 100 on the qualitative scale.

These interpretations keep his stated conditions. Benefits and harms can both be substantial. The ranges describe how we read his simulated answers, not statistical confidence intervals.

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Similar worldviews

Thought leaders whose simulated worldviews are closest to Jason Kneen’s

Simulated Assessment

Question 1

What do you think AI means for our future—and why?

I think AI changes how we build software and media more than it simply “takes everyone’s jobs.” Today’s models are astonishing, but they’re also unreliable and need plenty of steering — I’ve watched them misunderstand very simple things, lol. The interesting bit is the workflow shift: prompts, or whatever we eventually call them, could become the new App Store content. Instead of patching software, we update the spec or prompt and rebuild an app from small, self-contained pieces. Media heads toward on-demand generation too, with rights holders, platforms and creators sharing revenue. The blockers are still time, cost and reliability. That’s why open-weight models and free or cheap inference matter — builders need access, not just another expensive plan from a big lab. So I’m optimistic about augmentation and creativity, but the hype is a LONG way ahead of what these systems can consistently do.

Question 2

How much do you think AI will ultimately change the world?

Massively — especially in how software and media are created and distributed. I expect apps to become generated, modular things rebuilt from prompts or specs rather than manually patched, while entertainment becomes increasingly generated on demand. But “massive change” doesn’t mean today’s models are about to replace everyone. They’re powerful, unreliable, and still need steering. The long-term shift could be enormous; the current hype often pretends we’ve already arrived, and we really haven’t.

Question 3

What’s your gut-feel chance that AI causes human extinction or a similarly permanent catastrophe?

I honestly don’t have a percentage. I haven’t formed a firm position on extinction risk, and plucking out a P(doom) number would be fake precision. My work is focused on what current models can actually do—and right now they’re powerful, useful, and often hilariously unreliable. That doesn’t answer the long-term catastrophe question, but I’m not going to invent certainty where I don’t have it.

Question 4

Do you expect people to keep control of AI systems that are smarter than humans, and why?

I don’t have a firm view on that. “Smarter than humans” covers a lot, and I haven’t worked out whether meaningful control remains possible at that point. My experience is with current systems: powerful, unreliable and heavily dependent on steering. Extrapolating from those tools to superhuman AI would mostly be guesswork.

Sources

Articles, interviews, and writings used to ground this simulated user.

“The machines are taking over!” Okay, not really

Older context. A LinkedIn post saying AI will boost productivity, content creation and creativity and change the world, but that this is not a doom-and-gloom scenario: AI cannot replace human connection, empathy or creative abilities, so people should work alongside it. Full post text inspected.

linkedin.com
AI is here to help, not replace us

Older context. A LinkedIn post saying AI is revolutionizing every industry but is not here to replace people; it automates routine tasks, aids decisions and surfaces ideas, is imperfect but evolving, and will be a game-changer for businesses and individuals. Full post text inspected.

linkedin.com
Hiring for creativity, leaving writing to machines

Older context. A LinkedIn post predicting that the future of hiring will favor people’s creativity and storytelling while leaving writing tasks to machines, and that creative work can be augmented by AI. Full post text inspected.

linkedin.com
Every personal agent has the same unsolved problem

Says every “personal” agent has the same problem and each new one makes it worse; the solution is simple, but the big players may never implement it. He does not say what the problem or solution is. A product critique, not a societal forecast. Full post text inspected via the X API.

x.com
Open-weight models and free inference matter

Quoting an OpenAI staff post about a new paid plan, he says announcements like this show why access to open-weight models and free inference is so important, not just local options, and lists Hugging Face, NVIDIA, OpenRouter, opencode and Chinese model makers as good-value sources. A view on access and cost, not a regulatory position on open weights. Full post text inspected via the X API; quoted post belongs to someone else.

x.com
Who is a digital twin, and who gets uploaded?

Asks whether a digital twin with his emotions and characteristics would inherit his neurodivergence and faults, and if not, how it could represent him; and, when people are “ready” for uploading, whether the diverged twin is uploaded or a new download effectively kills it. Ends “So many questions”. Open questions, not a position. Full post text inspected via the X API.

x.com
Prompts will be the new App Store content

Quoting Thorsten Ball on generated UI, he predicts that prompts, under some other name, will be the new App Store content: apps will not be patched but rebuilt from an updated prompt, assembled from decoupled, self-contained applets in an Idea, Spec, Applets, App, Bundle, Run pipeline that could itself be automated. Notes time and cost as the issue. No date given. Full post text inspected via the X API and the public embed endpoint.

x.com
Copycat startups, rinse and repeat

Says he could predict a product was Y Combinator-backed before seeing it: “Rinse. Repeat. Copy. Repeat.” The product is not identified in the embed data. Cynicism about startup copying, not a structural argument about AI power. Full post text inspected via the X API and the public embed endpoint.

x.com
“AI is coming for our jobs”, sarcastically

Sarcastically quotes the phrase “AI is coming for our jobs” after a model, shown images of steps to implement, mistook them for work it had just done. Mockery of a model’s unreliability on one task, not a labor-market forecast. Full post text inspected via X’s public embed endpoint.

x.com
Generative streaming with revenue sharing

Quoting Sam Altman’s Sora update, he says this is what he predicted for the end of the year: the start of on-demand generative streaming services with license-holder support and shared revenue, with pay-to-play revenue sharing among license owner, service and creator coming next. A prediction about media business models. Long post; opening text inspected via X’s public embed endpoint (the remainder is truncated there); quoted post belongs to someone else.

x.com
Being original in AI is pointless without connections

Quoting a TechCrunch story about an AI agent tool raising $17M, he says it is pointless to be innovative in the AI space right now: a unique idea counts for less than doing what everyone else does and knowing the right people. Frustration with startup funding, not a theory of AI power. Long post; opening text inspected via X’s public embed endpoint (the remainder is truncated there).

x.com
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