@yacineMTB
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Tweet analysis: AI is driving a compute-powered economy — faster creation, less friction, broader access. Support 53.85%, Confront 22.27%. Risks and opportunities.
The world is transitioning to a compute-powered economy. The field of software engineering is currently undergoing a renaissance, with AI having dramatically sped up software engineering even over just the past six months. AI is now on track to bring this same transformation to every other kind of work that people do with a computer. Using a computer has always been about contorting yourself to the machine. You take a goal and break it down into smaller goals. You translate intent into instructions. We are moving into a world where you no longer have to micromanage the computer. More and more, it adapts to what you want. Rather doing work with a computer, the computer does work for you. The rate, scale, and sophistication of problem solving it will do for you will be bound by the amount of compute you have access to. Friction is starting to disappear. You can try ideas faster. You can build things you would not have attempted before. Small teams can do what used to require much larger ones, and larger ones may be capable of unprecedented feats. More and more, people can turn intent into software, spreadsheets, presentations, workflows, science, and companies. People are spending less energy managing the tool and more energy focusing on what they are actually trying to create. That shift brings a kind of joy back into work that many people haven’t felt in a long time. Everyone can just build things with these tools. This is disruptive. Institutions will change, and the paths and jobs that people assumed were stable may not hold. We don’t know exactly how it will play out and we need to take mitigating downsides very seriously, as well as figuring out how to support each other as a society and world through this time. But there is something very freeing about this moment. For the first time, far more people can become who they want to become, with fewer barriers between an idea and a reality. OpenAI’s mission implies making sure that, as the tools do more, humans are the ones who set their intent and that the benefits are broadly distributed, rather than empowering just one or a small set of people. We're already seeing this in practice with ChatGPT and Codex. Nearly a billion people are using these systems every week in their personal and work lives. Token usage is growing quickly on many use-cases, as the surface of ways people are getting value from these models keeps expanding. Ten years ago, when we started OpenAI, we thought this moment might be possible. It’s happening on the earlier side, and happening in a much more interesting and empowering way for everyone than we’d anticipated (for example, we are seeing an emerging wave of entrepreneurship that we hadn’t previously been anticipating). And at the same time, we are still so early, and there is so much for everyone to define about how these systems get deployed and used in the world. The next phase will be defined by systems that can do more — reason better, use tools better, plan over longer horizons, and take more useful actions on your behalf. And there are horizons beyond, as AI starts to accelerate science and technology development, which have the potential to truly lift up quality of life for everyone. All of this is starting to happen, in small ways and large, today, and everyone can participate. I feel this shift in my own work every day, and see a roadmap to much more useful and beneficial systems. These systems can truly benefit all of humanity.
Real-time analysis of public opinion and engagement
What the community is saying — both sides
Replies emphasize a fundamental shift from micromanaging machines to stating goals in natural language — English is becoming a high-level programming language.
Multiple voices report 5–10x productivity gains and real examples of one person or a 10-person team shipping work that used to require large orgs.
With execution commoditized, the scarce skill is knowing what to build, how to frame problems, and how to design good intent.
Several replies describe entire workflows becoming obsolete in months and warn about being caught unprepared by the speed of change.
Concerns range from GPU and energy constraints to funding models, token burn, and whether access to compute will concentrate power or be broadly available.
People call for new metrics, open data, runtime governance, and systems that detect drift, hallucination, and limits when agents run under pressure.
Replies urge education, open town halls, policy, and equitable access so the gains aren’t captured by a few and so vulnerable groups aren’t left behind.
Friction removal creates new business types and joy in work, but also forces rethinking deploy pipelines, incident response, user onboarding, and humane, relational AI experiences.
A large, vocal group demands the return of GPT‑4o (and wants it open‑sourced), arguing it was the most capable, multimodal “companion” and that removing it stripped users of joy and power. (#keep4o, #OpenSource4o)
Critics say the “compute‑powered economy” is a cover for selling access and excluding small teams, concentrating AI’s benefits in the hands of the wealthy and corporate interests.
Many accuse the company of using safety to justify downgrading models, routing users to cheaper, inferior options while hiding high‑performance systems behind corporate gates.
People worry AI will let companies do more with fewer employees, worsening unemployment and inequality — “AI means fewer jobs” and “people need money” are repeated refrains.
Users say the narrative outpaces the product: single chat windows, models that don’t follow instructions, frequent shutdowns and degraded trust make the promise of “frictionless creativity” feel hollow.
Technical critics call the compute framing a capex justification — the real limits are feedback loops, model correctness and developer workflows, not raw GW/MW datacenter spend.
A faction urges slowing frontier advances in favor of global AI governance, warning about societal harms, academic burnout and even existential risk if unchecked progress continues.
Replies include harsh moral condemnation and political accusations (donations, enabling harmful policies), reflecting deep distrust of motives beyond technical criticism.
Many argue that promises of broad distribution mean little if users can’t influence what’s built, kept or killed — creators complain their work was erased unless corporately approved.
Most popular replies, ranked by engagement
koding koding koding never stop koding
4o would have written a more compelling essay for you to post. #keep4o #opensource4o #keep4oAPI https://t.co/u58Dsrvxs0
What prompt did you use for this?
Working on @gitlawb for for AI agents frictionless building and collaboration
No one is reading all of that bs Stop yapping and bring back 4.o 🤦🏽♀️👏🏾 #keep4oAPI #keep4o
Fuck reading all that. Give us 4o back! #keep4o
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