Five AI buzzwords decoded for non-engineers. LLMs, Agents, Vibe Coding, Retrieval, Solo Founders.

A short answer first. If you are a manager, a creator, or anyone who is not a programmer, the words flying around AI right now are doing two jobs at once: describing real things, and making you feel like you are behind. You are not behind. The vocabulary just runs faster than the technology, and the technology runs fast. Five words cover roughly 90% of the conversation right now: LLM, Agent, Vibe Coding, Retrieval, and Solo Founders. Learn these five and you can sit in any AI meeting and follow what is happening. The rest is decoration.

I write this for the person who feels the new world touches their work - in management, in creation, in decisions - and is tired of nodding politely while someone says "agentic RAG" for the third time in one call.

TL;DR: the five words on one screen

1. LLM (Large Language Model)

An LLM is a statistical model trained on a huge amount of text. ChatGPT, Claude, Gemini - all LLMs. The thing they actually do, under the hood, is boring: they predict the next word. Then the next one. Then the next one. Do that a few hundred times in a row, and you get an essay, an email, a function, a poem.

It feels like the model "understands" you. Functionally, it does. Mechanically, it is pattern-matching at a scale that has never existed before. That is not a put-down. Pattern-matching at this scale is genuinely new, and the things that fall out of it - reasoning, translation, code - are real.

Two things to keep in your head:

• →It has no eyes, no hands, and no live world access by default. On its own, an LLM cannot see your inbox, your database, your calendar, or what happened yesterday. It only knows what was in its training data, or what you paste into the prompt.
• →It is confidently wrong sometimes. "Hallucination" is the polite word. The model fills in plausible-sounding text when it does not actually know. Useful for brainstorming. Dangerous for compliance.

If you remember nothing else: the LLM is the brain in a jar. Powerful, articulate, no body, no calendar, no access to anything you did not give it.

2. Agent

An Agent is an LLM with tools. That is the whole idea. You take the brain in a jar, and you give it limbs: the ability to call an API, run a search, send an email, write to a database, open a browser, execute code.

The model decides when to call which tool. You ask "book me a flight to Berlin next Tuesday under $400." A chatbot writes a paragraph about flights. An agent opens the booking tool, searches, filters, picks one, and asks you to confirm. Same brain. Different limbs.

This is the shift everyone in enterprise software is still paying for. A chatbot talks. An agent does. The hard part is not the model. The hard part is everything around the model: which tools, with which permissions, in which order, with which guardrails, reporting to which human.

I wrote about this at length in the Salesforce 99.9% gap piece - if you want the enterprise version of the agent story, start there.

3. Vibe Coding

Andrej Karpathy coined the term. Vibe coding is writing software by describing what you want in plain English while the AI writes, edits, and runs the code for you. You stop typing functions. You start typing intent.

"Make me a landing page for a Tel Aviv coffee shop, dark mode, one signup form, mobile-first." You hit enter. The AI writes the code, runs it, shows you the result. You squint at it, say "the button is ugly, make it round and orange." The AI changes it. You ship.

Two things people get wrong about vibe coding:

• →It is not "no skill required." The skill moved. You still need taste, direction, the ability to read what the AI produced and notice the bug. What you do not need is to remember the syntax. That is a real shift, and it is real democratization, but it is not magic.
• →It is not only for toys. Real companies are shipping real production systems this way. Not all of them. Not for everything. But "I cannot code, so I cannot build" is not true anymore. It is now "I cannot articulate what I want, so I cannot build," which is a much smaller club. By 2026 even Andrej Karpathy, who coined "vibe coding," argues the disciplined, reviewed end of the practice has matured into what people now call "agentic engineering."

If you are a manager, the vibe-coding shift means your team can prototype in a day what used to take a sprint. Use that. Do not wait for it to be perfect.

4. Retrieval (RAG)

Retrieval-Augmented Generation. The mouthful is unfortunate. The idea is simple: before the model answers, you fetch the most relevant documents from your private data and stuff them into the prompt. Then the model answers using what you just gave it.

Why this matters: the LLM was trained on the public internet up to some cutoff date. It does not know your contracts, your internal wiki, your customer support tickets, last quarter's board deck, or what your CFO said in the all-hands. Retrieval is how you let the model answer questions about data it was never trained on.

The flow, in plain English:

1. 01You index your data. Chunk it up, store it in a vector database so it can be searched by meaning, not by exact words.
2. 02A user asks a question. You search your data for the chunks most relevant to that question.
3. 03You feed those chunks to the model. Along with the original question. The model answers using only what you handed it.

Important nuance: retrieval is not training. The model does not "learn" your data. It reads it, once, fresh, every time you ask. That is good for privacy and recency, and it is the architecture behind most useful enterprise AI you have seen in the last two years.

5. Solo Founders

Solo Founders are people running real companies alone - or with one or two others - by using AI to do the work that used to require a team of ten. This is genuinely new. It is a 2025 phenomenon, and it is not a vibe. There are real companies, with real revenue, run by one person and a stack of models.

How it works in practice: the founder writes the code with an AI pair (vibe coding). The customer support runs through an agent. The content gets drafted by an LLM and edited by the founder. The bookkeeping is software. The legal is templates plus a lawyer on retainer. The marketing is one person with very fast tools. What used to require a CTO, a CMO, a head of customer success, three engineers, and a content marketer is now one person and a $200/month software stack.

This does not mean every business should be solo. It means the lower bound just moved. Things that used to need ten people to be viable can now be viable with one. That changes which businesses get built, who builds them, and what the next decade of small companies looks like.

If you are managing a larger company: the people you are competing with for talent now have the option to leave and run a viable business alone. Plan accordingly.

Why this matters if you are not a programmer

You do not have to know how a transformer works to use a calculator. You do not have to know how an LLM is trained to use one well. But you do need the vocabulary, because the vocabulary is how decisions get made.

When your team says "let's build an agent for this," you should be able to ask: which tools does it need, what is it allowed to do without a human, and how do we know when it is wrong. When a vendor says "we have a custom RAG," you should be able to ask: what data, indexed how, evaluated against what. When a candidate says "I am a solo founder," you should know what to expect.

You cannot influence what you do not understand. So understand the five words. The rest is just longer versions of these five.

FAQ

Written by Michael Fleicher, Principal at Bina Labs. Two-time CTO. This is the first piece in a series I am calling "Michael Tries to Explain the New World" - plain-English explanations of AI concepts for the people who run companies, make decisions, and build things, but do not write code. If you want to talk about how any of this lands inside your team, start here.