AI Hype vs. Reality: What’s Actually Behind the Buzzwords
TL;DR
A new tool called Extra-steps.dev is trying to cut through AI marketing noise by mapping hyped AI concepts directly to their underlying computer science primitives. The idea is simple but potentially powerful: instead of letting vendors dazzle you with buzzwords, you can trace every claim back to foundational CS concepts you already understand. It surfaced on Hacker News with modest but notable attention. If you’ve ever rolled your eyes at an AI pitch deck, this one’s for you.
What the Sources Say
There’s exactly one source here, and it’s worth examining closely for what it reveals — both in content and in community reaction.
A Hacker News “Show HN” submission pointed to extra-steps.dev, describing it as a project that maps AI hype to CS primitives. The pitch is essentially a debunking tool: take the breathless language of modern AI marketing — “autonomous agents,” “reasoning engines,” “memory architectures” — and trace each term back to what it actually is under the hood.
The post received a score of 1 and only 2 comments at the time of data collection. That’s a thin data slice, admittedly. But the concept it represents taps into something that’s been simmering in the developer community for a while.
The Core Idea
The premise of Extra-steps.dev is that a lot of what gets branded as revolutionary AI innovation is, when you strip away the marketing layer, a recombination of decades-old computer science ideas. We’re talking about things like:
- “Memory” in AI agents → often just a database lookup or a key-value store
- “Reasoning” → structured prompting patterns, sometimes with chain-of-thought scaffolding
- “Autonomy” → a while-loop with tool calls
- “Learning” → fine-tuning or retrieval-augmented generation (RAG), which is itself just retrieval + generation stitched together
The promise of a tool like this is that it gives developers and skeptical engineers a shared vocabulary to push back. If a vendor tells you their product has “advanced persistent memory,” you can ask: is that a vector database, a key-value store, or something genuinely novel?
What the Community Reaction Tells Us
A score of 1 with 2 comments isn’t a viral hit, but “Show HN” posts often fly under the radar on their first day. The HN audience is notoriously skeptical of hype — which makes this submission’s premise a natural fit, even if the execution didn’t ignite a thread.
The lack of extensive commentary could mean a few things:
- The tool is early-stage and the implementation didn’t yet match the ambition of the concept
- The idea resonates but the site didn’t give people enough to chew on
- It simply got buried in the HN queue at an unlucky hour
None of these undercut the core idea. The question Extra-steps.dev is asking — what are we actually talking about when we talk about AI? — is one of the most important questions in tech right now.
The Bigger Context: Why “Primitives” Matter
Even with only one source to work from, it’s worth unpacking why mapping AI to CS primitives is a worthwhile project in February 2026.
We’re living through a period of extraordinary AI capability gains, but also extraordinary marketing inflation. The gap between what AI systems actually do and how they’re described has never been wider. Language models like Claude 4.5, GPT-5, and Gemini 2.5 are genuinely impressive — but they’re also getting bundled into products with names like “Cognitive Orchestration Platforms” that could mean almost anything.
For developers and technical buyers, this creates a real problem: how do you evaluate something when the vocabulary is deliberately obscured?
That’s the gap Extra-steps.dev seems to be trying to fill. By anchoring AI concepts to primitives — the building blocks every CS graduate knows — it creates a translation layer. It’s not about dismissing AI as “just statistics” or “it’s just autocomplete” (the reductive takes you see in comment threads). It’s about precision. Good engineering requires precise language, and right now, AI discourse is drowning in imprecise language.
The “Extra Steps” in the Name
The name itself is a subtle dig. The implication is that a lot of AI solutions add extra steps between you and a goal you could have reached with simpler tools. Sometimes those extra steps are worth it — the capabilities are genuinely new. But sometimes? You’re paying a premium for a LangChain wrapper around a SQL query.
This isn’t a new critique. Developers have been making this point since at least 2023, when the first wave of “AI-powered” everything hit. But having a dedicated resource that systematically catalogs these mappings could be genuinely useful — a reference you can link to in a Slack thread or a product review.
Pricing & Alternatives
Since the source package contains no pricing information for Extra-steps.dev, and the site appears to be a free reference tool rather than a commercial product, a traditional pricing table doesn’t apply here.
| Tool/Resource | Type | Cost | Focus |
|---|---|---|---|
| Extra-steps.dev | Reference/Mapping Tool | Unknown (appears free) | AI hype → CS primitives |
| No alternatives listed in sources | — | — | — |
Note: No competitor data was included in the source package. The table above reflects only what’s available from the source.
If you’re looking for similar demystification resources, the general category would include technical AI explainer blogs, ML engineering wikis, and skeptic-friendly communities on Hacker News itself — but those are not part of the source material here.
The Bottom Line: Who Should Care?
If you’re a developer or engineer who’s been nodding politely through AI vendor pitches while internally translating “intelligent orchestration layer” to “it’s a for-loop,” Extra-steps.dev sounds like it was built for you. The ability to point to a clean mapping from hype language to actual primitives is a useful tool in technical conversations.
If you’re a technical buyer or product manager evaluating AI tools, this kind of resource helps you ask better questions. When a vendor claims their product has “adaptive memory,” you can ask whether that means a vector store, a session cache, or something more novel — and actually understand the answer.
If you’re building AI products, this is worth looking at defensively. If your marketing copy would get demolished by a tool like this, that’s either a sign that your copy needs work — or that your product needs work.
If you’re a skeptic who thinks AI is overhyped: this tool aligns with your worldview, but it’s not pure cynicism. Mapping AI to primitives doesn’t say “AI is useless” — it says “let’s be precise about what’s new and what’s repackaging.”
If you’re a non-technical stakeholder: the site may or may not be accessible to you depending on how much CS vocabulary it assumes. Based on the concept alone, it seems aimed squarely at people who already know what a hash map or a message queue is.
The early HN reception was quiet, but the concept has legs. The best technical tools often start with a small, appreciative audience before finding their moment. In a landscape where AI hype shows no signs of cooling, a clear-eyed vocabulary guide could become a go-to reference.
Sources
- Show HN: Extra-steps.dev – AI hype mapped to CS primitives via Hacker News
Article generated from a source package collected on February 19, 2026. Only information from the provided source was used in this article.